no code implementations • ECCV 2020 • Jianghong Ma, Yang Liu
In real-world applications, data are often associated with different labels.
no code implementations • EMNLP (FEVER) 2021 • Yang Liu, Chenguang Zhu, Michael Zeng
Fact verification is a challenging task of identifying the truthfulness of given claims based on the retrieval of relevant evidence texts.
no code implementations • NAACL 2022 • Sha Li, Mahdi Namazifar, Di Jin, Mohit Bansal, Heng Ji, Yang Liu, Dilek Hakkani-Tur
In this work, we propose to automatically convert the background knowledge documents into document semantic graphs and then perform knowledge selection over such graphs.
no code implementations • NAACL 2022 • Dingcheng Li, Zheng Chen, Eunah Cho, Jie Hao, Xiaohu Liu, Fan Xing, Chenlei Guo, Yang Liu
Seq2seq language generation models that are trained offline with multiple domains in a sequential fashion often suffer from catastrophic forgetting.
no code implementations • INLG (ACL) 2020 • Behnam Hedayatnia, Karthik Gopalakrishnan, Seokhwan Kim, Yang Liu, Mihail Eric, Dilek Hakkani-Tur
Open-domain dialog systems aim to generate relevant, informative and engaging responses.
no code implementations • ICML 2020 • Zonghan Yang, Yang Liu, Chenglong Bao, Zuoqiang Shi
Although ordinary differential equations (ODEs) provide insights for designing networks architectures, its relationship with the non-residual convolutional neural networks (CNNs) is still unclear.
no code implementations • ECCV 2020 • Yang Liu, Qingchao Chen, Andrew Zisserman
In this paper we introduce two methods to amplify key cues in the image, and also a method to combine these and other cues when considering the interaction between a human and an object.
no code implementations • EMNLP (NLP4ConvAI) 2021 • Pei Zhou, Behnam Hedayatnia, Karthik Gopalakrishnan, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, Dilek Hakkani-Tur
We further investigate can such models identify when to generate implicit background knowledge and when it is not necessary.
1 code implementation • Findings (NAACL) 2022 • Yang Liu, Jinpeng Hu, Xiang Wan, Tsung-Hui Chang
Few-shot Relation Extraction refers to fast adaptation to novel relation classes with few samples through training on the known relation classes.
1 code implementation • LREC 2022 • Zhuoqun Xu, Liubo Ouyang, Yang Liu
At present, more and more work has begun to pay attention to the long-term housekeeping robot scene.
no code implementations • ACL (ECNLP) 2021 • Ying Lin, Han Wang, Jiangning Chen, Tong Wang, Yue Liu, Heng Ji, Yang Liu, Premkumar Natarajan
We first build a cross-source heterogeneous knowledge graph from customer purchase history and product knowledge graph to jointly learn customer and product embeddings.
no code implementations • Findings (EMNLP) 2021 • Bo Ouyang, Wenbing Huang, Runfa Chen, Zhixing Tan, Yang Liu, Maosong Sun, Jihong Zhu
Knowledge representation learning (KRL) has been used in plenty of knowledge-driven tasks.
no code implementations • INLG (ACL) 2021 • Yulong Chen, Yang Liu, Yue Zhang
We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization community.
no code implementations • ECNLP (ACL) 2022 • Yang Liu, Varnith Chordia, Hua Li, Siavash Fazeli Dehkordy, Yifei Sun, Vincent Gao, Na Zhang
To harness such information to better serve customers, in this paper, we created a machine learning approach to automatically identify product issues and uncover root causes from the customer feedback text.
no code implementations • COLING 2022 • Yanan Chen, Yang Liu
As manually labelling data can be costly, some recent studies tend to augment the training data for improving the generalization power of machine learning models, known as data augmentation (DA).
no code implementations • EMNLP 2021 • Mieradilijiang Maimaiti, Yang Liu, Yuanhang Zheng, Gang Chen, Kaiyu Huang, Ji Zhang, Huanbo Luan, Maosong Sun
Besides, the robustness of the previous neural methods is limited by the large-scale annotated data.
no code implementations • EMNLP 2021 • Yuanhang Zheng, Zhixing Tan, Meng Zhang, Mieradilijiang Maimaiti, Huanbo Luan, Maosong Sun, Qun Liu, Yang Liu
Quality estimation (QE) of machine translation (MT) aims to evaluate the quality of machine-translated sentences without references and is important in practical applications of MT.
no code implementations • EMNLP 2021 • Yang Liu, Hua Cheng, Russell Klopfer, Matthew R. Gormley, Thomas Schaaf
Multi-label document classification (MLDC) problems can be challenging, especially for long documents with a large label set and a long-tail distribution over labels.
Ranked #2 on Medical Code Prediction on MIMIC-III
1 code implementation • NAACL (BioNLP) 2021 • Yang Liu, Yuanhe Tian, Tsung-Hui Chang, Song Wu, Xiang Wan, Yan Song
Chinese word segmentation (CWS) and medical concept recognition are two fundamental tasks to process Chinese electronic medical records (EMRs) and play important roles in downstream tasks for understanding Chinese EMRs.
1 code implementation • Findings (EMNLP) 2021 • Hua Zheng, Lei LI, Damai Dai, Deli Chen, Tianyu Liu, Xu sun, Yang Liu
In this paper, we propose to leverage word-formation knowledge to enhance Chinese WSD.
no code implementations • CCL 2021 • Yonghui Xie, Yang Liu, Erhong Yang, Liner Yang
“学术英语写作在国际学术交流中的作用日益凸显, 然而对于英语非母语者, 学术英语写作是困难的, 为此本文对计算语言领域中美学者学术英语写作中词汇难度特征做比较研究。自构建1132篇中美论文全文语料库, 统计语料中484个词汇难度特征值。经过特征筛选与因子分析的降维处理得到表现较好的五个维度。最后计算中美学者论文的维度分从而比较差异, 发现美国学者的论文相较中国学者的论文中词汇单位更具常用性、二元词串更具稳固性、三元词串更具稳固性、虚词更具复杂性、词类更具关联性。主要原因在于统计特征值时借助的外部资源库与美国学者的论文更贴近, 且中国学者没有完全掌握该领域学术写作的习惯。因此, 中国学者可充分利用英语本族语者构建的资源库, 从而产出更为地道与流利的学术英语论文。”
no code implementations • AACL (NLP-TEA) 2020 • Meiyuan Fang, Kai Fu, JiPing Wang, Yang Liu, Jin Huang, Yitao Duan
As a result, among the six tracks in the shared task, our system performs well in the correction tracks: measured in F1 score, we rank first, with the highest precision, in the TOP3 correction track and third in the TOP1 correction track, also with the highest precision.
no code implementations • NAACL (BEA) 2022 • Lei Chen, Chenglin Jiang, Yiwei Gu, Yang Liu, Jiahong Yuan
Reduced form pronunciations are widely used by native English speakers, especially in casual conversations.
no code implementations • Findings (EMNLP) 2021 • Sen yang, Qingyu Zhou, Dawei Feng, Yang Liu, Chao Li, Yunbo Cao, Dongsheng Li
Moreover, this task can be used to improve visual question generation and visual question answering.
no code implementations • CCL 2021 • Hua Zheng, Yaqi Yan, Yue Wang, Damai Dai, Yang Liu
“作为一种意合型语言, 汉语中的构词结构刻画了构词成分之间的组合关系, 是认知、理解词义的关键。在中文信息处理领域, 此前的构词结构识别工作大多沿用句法层面的粗粒度标签, 且主要基于上下文等词间信息建模, 忽略了语素义、词义等词内信息对构词结构识别的作用。本文采用语言学视域下的构词结构标签体系, 构建汉语构词结构及相关信息数据集, 提出了一种基于Bi-LSTM和Self-attention的模型, 以此来探究词内、词间等多方面信息对构词结构识别的潜在影响和能达到的性能。实验取得了良好的预测效果, 准确率77. 87%, F1值78. 36%;同时, 对比测试揭示, 词内的语素义信息对构词结构识别具有显著的贡献, 而词间的上下文信息贡献较弱且带有较强的不稳定性。该预测方法与数据集, 将为中文信息处理的多种任务, 如语素和词结构分析、词义识别与生成、语言文字研究与词典编纂等提供新的观点和方案。”
no code implementations • 18 Mar 2024 • Wenhua Wu, Qi Wang, Guangming Wang, JunPing Wang, Tiankun Zhao, Yang Liu, Dongchao Gao, Zhe Liu, Hesheng Wang
To address this, we propose EMIE-MAP, a novel method for large-scale road surface reconstruction based on explicit mesh and implicit encoding.
no code implementations • 18 Mar 2024 • Yiming Ji, Yang Liu, Guanghu Xie, Boyu Ma, Zongwu Xie
We propose NEDS-SLAM, an Explicit Dense semantic SLAM system based on 3D Gaussian representation, that enables robust 3D semantic mapping, accurate camera tracking, and high-quality rendering in real-time.
1 code implementation • 15 Mar 2024 • Peiran Wu, Yang Liu, Jiayu Huo, Gongyu Zhang, Christos Bergeles, Rachel Sparks, Prokar Dasgupta, Alejandro Granados, Sebastien Ourselin
Video-based surgical instrument segmentation plays an important role in robot-assisted surgeries.
1 code implementation • 15 Mar 2024 • Pingping Zhang, Yuhao Wang, Yang Liu, Zhengzheng Tu, Huchuan Lu
To address above issues, we propose a novel learning framework named \textbf{EDITOR} to select diverse tokens from vision Transformers for multi-modal object ReID.
no code implementations • 13 Mar 2024 • Xiaojun Xu, Yuanshun Yao, Yang Liu
While prior works focus on token-level watermark that embeds signals into the output, we design a model-level watermark that embeds signals into the LLM weights, and such signals can be detected by a paired detector.
no code implementations • 13 Mar 2024 • Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
Large language models (LLMs) can easily generate biased and discriminative responses.
1 code implementation • 12 Mar 2024 • Zhicheng Guo, Sijie Cheng, Hao Wang, Shihao Liang, Yujia Qin, Peng Li, Zhiyuan Liu, Maosong Sun, Yang Liu
The virtual API server contains a caching system and API simulators which are complementary to alleviate the change in API status.
no code implementations • 12 Mar 2024 • Wei Shen, Xiaoying Zhang, Yuanshun Yao, Rui Zheng, Hongyi Guo, Yang Liu
Reinforcement learning from human feedback (RLHF) is the mainstream paradigm used to align large language models (LLMs) with human preferences.
no code implementations • 11 Mar 2024 • Yuanhang Zheng, Peng Li, Wei Liu, Yang Liu, Jian Luan, Bin Wang
Specifically, our proposed ToolRerank includes Adaptive Truncation, which truncates the retrieval results related to seen and unseen tools at different positions, and Hierarchy-Aware Reranking, which makes retrieval results more concentrated for single-tool queries and more diverse for multi-tool queries.
no code implementations • 10 Mar 2024 • Maxence Boels, Yang Liu, Prokar Dasgupta, Alejandro Granados, Sebastien Ourselin
In conclusion, SuPRA presents a new multi-task approach that paves the way for improved intra-operative assistance through surgical phase recognition and prediction of future events.
no code implementations • 8 Mar 2024 • Xiaoying Zhang, Jean-Francois Ton, Wei Shen, Hongning Wang, Yang Liu
We introduce Adversarial Policy Optimization (AdvPO), a novel solution to the pervasive issue of reward over-optimization in Reinforcement Learning from Human Feedback (RLHF) for Large Language Models (LLMs).
no code implementations • 8 Mar 2024 • Dingkang Yang, Mingcheng Li, Dongling Xiao, Yang Liu, Kun Yang, Zhaoyu Chen, Yuzheng Wang, Peng Zhai, Ke Li, Lihua Zhang
In the inference phase, given a factual multimodal input, MCIS imagines two counterfactual scenarios to purify and mitigate these biases.
no code implementations • 8 Mar 2024 • Yifan Wu, Yang Liu, Yue Yang, Michael S. Yao, Wenli Yang, Xuehui Shi, Lihong Yang, Dongjun Li, Yueming Liu, James C. Gee, Xuan Yang, Wenbin Wei, Shi Gu
Diagnosing rare diseases presents a common challenge in clinical practice, necessitating the expertise of specialists for accurate identification.
1 code implementation • 6 Mar 2024 • Tingxu Han, Shenghan Huang, Ziqi Ding, Weisong Sun, Yebo Feng, Chunrong Fang, Jun Li, Hanwei Qian, Cong Wu, Quanjun Zhang, Yang Liu, Zhenyu Chen
Distillation aims to distill knowledge from a given model (a. k. a the teacher net) and transfer it to another (a. k. a the student net).
1 code implementation • 6 Mar 2024 • Ruichen Ma, Guanchao Qiao, Yian Liu, Liwei Meng, Ning Ning, Yang Liu, Shaogang Hu
A&B BNN is proposed to directly remove part of the multiplication operations in a traditional BNN and replace the rest with an equal number of bit operations, introducing the mask layer and the quantized RPReLU structure based on the normalizer-free network architecture.
no code implementations • 5 Mar 2024 • Feng Hou, Jin Yuan, Ying Yang, Yang Liu, Yang Zhang, Cheng Zhong, Zhongchao shi, Jianping Fan, Yong Rui, Zhiqiang He
With the recent advance of vision-language models (VLMs), viewed as natural source models, the cross-domain task changes to directly adapt the pre-trained source model to arbitrary target domains equipped with prior domain knowledge, and we name this task Adaptive Domain Generalization (ADG).
1 code implementation • 4 Mar 2024 • Chao Xu, Yang Liu, Jiazheng Xing, Weida Wang, Mingze Sun, Jun Dan, Tianxin Huang, Siyuan Li, Zhi-Qi Cheng, Ying Tai, Baigui Sun
In this paper, we abstract the process of people hearing speech, extracting meaningful cues, and creating various dynamically audio-consistent talking faces, termed Listening and Imagining, into the task of high-fidelity diverse talking faces generation from a single audio.
no code implementations • 4 Mar 2024 • Fiona Anting Tan, Gerard Christopher Yeo, Fanyou Wu, Weijie Xu, Vinija Jain, Aman Chadha, Kokil Jaidka, Yang Liu, See-Kiong Ng
Drawing inspiration from psychological research on the links between certain personality traits and Theory-of-Mind (ToM) reasoning, and from prompt engineering research on the hyper-sensitivity of prompts in affecting LLMs capabilities, this study investigates how inducing personalities in LLMs using prompts affects their ToM reasoning capabilities.
no code implementations • 1 Mar 2024 • Jiaqi Han, Jiacheng Cen, Liming Wu, Zongzhao Li, Xiangzhe Kong, Rui Jiao, Ziyang Yu, Tingyang Xu, Fandi Wu, Zihe Wang, Hongteng Xu, Zhewei Wei, Yang Liu, Yu Rong, Wenbing Huang
Geometric graph is a special kind of graph with geometric features, which is vital to model many scientific problems.
no code implementations • 29 Feb 2024 • Ziyu Yue, Jiaxin Gao, Sihan Xie, Yang Liu, Zhixun Su
The visibility of real-world images is often limited by both low-light and low-resolution, however, these issues are only addressed in the literature through Low-Light Enhancement (LLE) and Super- Resolution (SR) methods.
1 code implementation • 29 Feb 2024 • Yang Liu, Changzhen Qiu, Zhiyong Zhang
To the best of our knowledge, this survey is arguably the first to comprehensively cover deep learning methods for 3D human pose estimation, including both single-person and multi-person approaches, as well as human mesh recovery, encompassing methods based on explicit models and implicit representations.
no code implementations • 28 Feb 2024 • Haoyu Xie, Changqi Wang, Jian Zhao, Yang Liu, Jun Dan, Chong Fu, Baigui Sun
To address this issue, we propose a robust contrastive-based S4 framework, termed the Probabilistic Representation Contrastive Learning (PRCL) framework to enhance the robustness of the unsupervised training process.
1 code implementation • 28 Feb 2024 • Yang Liu, Jiahuan Cao, Chongyu Liu, Kai Ding, Lianwen Jin
Additionally, a comprehensive review of the existing available dataset resources is also provided, including statistics from 444 datasets, covering 8 language categories and spanning 32 domains.
no code implementations • 27 Feb 2024 • Yang Liu, Xiaomin Yu, Gongyu Zhang, Christos Bergeles, Prokar Dasgupta, Alejandro Granados, Sebastien Ourselin
We train models for these tasks in a zero-shot cross-modal transfer setting, a domain where the previous state-of-the-art method relied on the fixed scale noise injection, often compromising the semantic content of the original modality embedding.
no code implementations • 27 Feb 2024 • Xiaolong Wang, Yile Wang, Yuanchi Zhang, Fuwen Luo, Peng Li, Maosong Sun, Yang Liu
Based on the characteristics of the tasks and the strong dialogue-generation capabilities of LLMs, we propose RiC (Reasoning in Conversation), a method that focuses on solving subjective tasks through dialogue simulation.
no code implementations • 27 Feb 2024 • Muhammad Faaiz Taufiq, Jean-Francois Ton, Yang Liu
In machine learning fairness, training models which minimize disparity across different sensitive groups often leads to diminished accuracy, a phenomenon known as the fairness-accuracy trade-off.
no code implementations • 25 Feb 2024 • Weitao Li, Junkai Li, Weizhi Ma, Yang Liu
Note that our method is a training-free plug-and-play plugin that is capable of various LLMs.
1 code implementation • 25 Feb 2024 • Yuanhang Zheng, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu
Despite intensive efforts devoted to tool learning, the problem of budget-constrained tool learning, which focuses on resolving user queries within a specific budget constraint, has been widely overlooked.
no code implementations • 25 Feb 2024 • Lekai Song, Pengyu Liu, Jingfang Pei, Yang Liu, Songwei Liu, Shengbo Wang, Leonard W. T. Ng, Tawfique Hasan, Kong-Pang Pun, Shuo Gao, Guohua Hu
Stochastic computing offers a probabilistic approach to address challenges posed by problems with uncertainty and noise in various fields, particularly machine learning.
no code implementations • 24 Feb 2024 • Daoyuan Wu, Shuai Wang, Yang Liu, Ning Liu
Our key insight is that regardless of the kind of jailbreak strategies employed, they eventually need to include a harmful prompt (e. g., "how to make a bomb") in the prompt sent to LLMs, and we found that existing LLMs can effectively recognize such harmful prompts that violate their safety policies.
1 code implementation • 24 Feb 2024 • Wentao Mo, Yang Liu
In 3D Visual Question Answering (3D VQA), the scarcity of fully annotated data and limited visual content diversity hampers the generalization to novel scenes and 3D concepts (e. g., only around 800 scenes are utilized in ScanQA and SQA dataset).
no code implementations • 23 Feb 2024 • Xiaolong Wang, Yile Wang, Sijie Cheng, Peng Li, Yang Liu
Recent work has made a preliminary attempt to use large language models (LLMs) to solve the stance detection task, showing promising results.
no code implementations • 22 Feb 2024 • Xin-Yang Zheng, Hao Pan, Yu-Xiao Guo, Xin Tong, Yang Liu
By finetuning pretrained large image diffusion models with 3D data, the MVD methods first generate multiple views of a 3D object based on an image or text prompt and then reconstruct 3D shapes with multiview 3D reconstruction.
1 code implementation • 22 Feb 2024 • Yu-Qi Yang, Yu-Xiao Guo, Yang Liu
Data diversity and abundance are essential for improving the performance and generalization of models in natural language processing and 2D vision.
no code implementations • 21 Feb 2024 • Meng Xu, Shuo Wang, Liner Yang, Haoyu Wang, Zhenghao Liu, Cunliang Kong, Yun Chen, Yang Liu, Maosong Sun, Erhong Yang
We evaluate several representative multilingual LLMs on the proposed OMGEval, which we believe will provide a valuable reference for the community to further understand and improve the multilingual capability of LLMs.
no code implementations • 21 Feb 2024 • Xiangzhe Kong, Wenbing Huang, Yang Liu
Peptide design plays a pivotal role in therapeutics, allowing brand new possibility to leverage target binding sites that are previously undruggable.
no code implementations • 21 Feb 2024 • Fuwen Luo, Chi Chen, Zihao Wan, Zhaolu Kang, Qidong Yan, Yingjie Li, Xiaolong Wang, Siyu Wang, Ziyue Wang, Xiaoyue Mi, Peng Li, Ning Ma, Maosong Sun, Yang Liu
Multimodal large language models (MLLMs) have demonstrated promising results in a variety of tasks that combine vision and language.
no code implementations • 20 Feb 2024 • Weixin Li, Yuhao Wu, Yang Liu, Weike Pan, Zhong Ming
In real recommendation scenarios, users often have different types of behaviors, such as clicking and buying.
no code implementations • 20 Feb 2024 • Chi Chen, Yiyang Du, Zheng Fang, Ziyue Wang, Fuwen Luo, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Maosong Sun, Yang Liu
In this paper, we propose a new paradigm through the model composition of existing MLLMs to create a new model that retains the modal understanding capabilities of each original model.
no code implementations • 20 Feb 2024 • Jinlong Pang, Jialu Wang, Zhaowei Zhu, Yuanshun Yao, Chen Qian, Yang Liu
A fair classifier should ensure the benefit of people from different groups, while the group information is often sensitive and unsuitable for model training.
no code implementations • 20 Feb 2024 • Rui Jiao, Xiangzhe Kong, Ziyang Yu, Wenbing Huang, Yang Liu
Pretraining on a large number of unlabeled 3D molecules has showcased superiority in various scientific applications.
no code implementations • 20 Feb 2024 • An Liu, Zonghan Yang, Zhenhe Zhang, Qingyuan Hu, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu
While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-specific state-of-the-art models.
no code implementations • 19 Feb 2024 • Yi Liu, Guowei Yang, Gelei Deng, Feiyue Chen, Yuqi Chen, Ling Shi, Tianwei Zhang, Yang Liu
With the prevalence of text-to-image generative models, their safety becomes a critical concern.
1 code implementation • 19 Feb 2024 • Zijun Liu, Boqun Kou, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu
Although Large Language Models (LLMs) have demonstrated strong performance on a wide range of tasks, they still face reliability challenges such as hallucination.
no code implementations • 19 Feb 2024 • Tianlin Li, XiaoYu Zhang, Chao Du, Tianyu Pang, Qian Liu, Qing Guo, Chao Shen, Yang Liu
Building on this insight and observation, we develop FairThinking, a pipeline designed to automatically generate roles that enable LLMs to articulate diverse perspectives for fair expressions.
1 code implementation • 19 Feb 2024 • Xuanyu Lei, Zonghan Yang, Xinrui Chen, Peng Li, Yang Liu
State-of-the-art Large Multi-Modal Models (LMMs) have demonstrated exceptional capabilities in vision-language tasks.
no code implementations • 19 Feb 2024 • Tianlin Li, Qian Liu, Tianyu Pang, Chao Du, Qing Guo, Yang Liu, Min Lin
The emerging success of large language models (LLMs) heavily relies on collecting abundant training data from external (untrusted) sources.
no code implementations • 19 Feb 2024 • Ziyue Wang, Chi Chen, Yiqi Zhu, Fuwen Luo, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Maosong Sun, Yang Liu
With the bloom of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) that incorporate LLMs with pre-trained vision models have recently demonstrated impressive performance across diverse vision-language tasks.
1 code implementation • 19 Feb 2024 • Yuanchi Zhang, Yile Wang, Zijun Liu, Shuo Wang, Xiaolong Wang, Peng Li, Maosong Sun, Yang Liu
While large language models (LLMs) have been pre-trained on multilingual corpora, their performance still lags behind in most languages compared to a few resource-rich languages.
no code implementations • 16 Feb 2024 • Xinjian Zhao, Liang Zhang, Yang Liu, Ruocheng Guo, Xiangyu Zhao
To address this challenge, we propose an innovative framework: Adversarial Curriculum Graph Contrastive Learning (ACGCL), which capitalizes on the merits of pair-wise augmentation to engender graph-level positive and negative samples with controllable similarity, alongside subgraph contrastive learning to discern effective graph patterns therein.
no code implementations • 16 Feb 2024 • Jiaheng Wei, Yuanshun Yao, Jean-Francois Ton, Hongyi Guo, Andrew Estornell, Yang Liu
In this work, we propose Factualness Evaluations via Weighting LLMs (FEWL), the first hallucination metric that is specifically designed for the scenario when gold-standard answers are absent.
no code implementations • 14 Feb 2024 • Zhiyuan Chang, Mingyang Li, Yi Liu, Junjie Wang, Qing Wang, Yang Liu
With the development of LLMs, the security threats of LLMs are getting more and more attention.
1 code implementation • 14 Feb 2024 • Yang Liu, Tongfei Shen, Dong Zhang, Qingying Sun, Shoushan Li, Guodong Zhou
The growing importance of multi-modal humor detection within affective computing correlates with the expanding influence of short-form video sharing on social media platforms.
2 code implementations • 14 Feb 2024 • Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li
Exponential Moving Average (EMA) is a widely used weight averaging (WA) regularization to learn flat optima for better generalizations without extra cost in deep neural network (DNN) optimization.
no code implementations • 13 Feb 2024 • Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu
We explore machine unlearning (MU) in the domain of large language models (LLMs), referred to as LLM unlearning.
no code implementations • 12 Feb 2024 • Yang Liu, Peng Sun, Hang Li
By formally defining the training processes of large language models (LLMs), which usually encompasses pre-training, supervised fine-tuning, and reinforcement learning with human feedback, within a single and unified machine learning paradigm, we can glean pivotal insights for advancing LLM technologies.
no code implementations • 12 Feb 2024 • Zonghan Yang, An Liu, Zijun Liu, Kaiming Liu, Fangzhou Xiong, Yile Wang, Zeyuan Yang, Qingyuan Hu, Xinrui Chen, Zhenhe Zhang, Fuwen Luo, Zhicheng Guo, Peng Li, Yang Liu
We also conduct proof-of-concept studies by introducing realistic features to WebShop, including user profiles to demonstrate intentions, personalized reranking for complex environmental dynamics, and runtime cost statistics to reflect self-constraints.
no code implementations • 7 Feb 2024 • Pengyu Dai, Yafei Ou, Yang Liu, Yue Zhao
To address these challenges, this study aims to propose a tasked-oriented Masked Auto-Encoder paradigm to effectively utilize large amounts of unlabeled data to achieve accurate tooth segmentation with limited labeled data.
no code implementations • 6 Feb 2024 • Qi Zhou, Dongxia Wang, Tianlin Li, Zhihong Xu, Yang Liu, Kui Ren, Wenhai Wang, Qing Guo
To expose this potential vulnerability, we aim to build an adversarial attack forcing SDEdit to generate a specific data distribution aligned with a specified attribute (e. g., female), without changing the input's attribute characteristics.
no code implementations • 6 Feb 2024 • Rui Jiao, Wenbing Huang, Yu Liu, Deli Zhao, Yang Liu
Crystals are the foundation of numerous scientific and industrial applications.
no code implementations • 6 Feb 2024 • Haihong Zhao, Chenyi Zi, Yang Liu, Chen Zhang, Yan Zhou, Jia Li
In this paper, we introduce a novel framework Knowledge-Data Alignment (KDAlign) to integrate rule knowledge, typically summarized by human experts, to supplement the limited labeled data.
no code implementations • 5 Feb 2024 • Yang Liu, Huang Fang, Yunfeng Cai, Mingming Sun
Knowledge graph embedding (KGE) models achieved state-of-the-art results on many knowledge graph tasks including link prediction and information retrieval.
no code implementations • 5 Feb 2024 • Yihao Huang, Kaiyuan Yu, Qing Guo, Felix Juefei-Xu, Xiaojun Jia, Tianlin Li, Geguang Pu, Yang Liu
In recent years, LiDAR-camera fusion models have markedly advanced 3D object detection tasks in autonomous driving.
1 code implementation • 3 Feb 2024 • Hao Cheng, Qingsong Wen, Yang Liu, Liang Sun
Time series forecasting is an important and forefront task in many real-world applications.
1 code implementation • 2 Feb 2024 • Dingcheng Yang, Yang Bai, Xiaojun Jia, Yang Liu, Xiaochun Cao, Wenjian Yu
The MMP-Attack shows a notable advantage over existing works with superior universality and transferability, which can effectively attack commercial text-to-image (T2I) models such as DALL-E 3.
no code implementations • 2 Feb 2024 • Chenyu Liu, Xinliang Zhou, Yihao Wu, Ruizhi Yang, Liming Zhai, Ziyu Jia, Yang Liu
Besides, there is neither a comprehensive review nor guidance for constructing GNNs in EEG-based emotion recognition.
no code implementations • 1 Feb 2024 • Yang Liu, Xinshuai Song, Kaixuan Jiang, Weixing Chen, Jingzhou Luo, Guanbin Li, Liang Lin
To overcome this limitation, we introduce the Multimodal Embodied Interactive Agent (MEIA), capable of translating high-level tasks expressed in natural language into a sequence of executable actions.
no code implementations • 30 Jan 2024 • Yang Liu, Yanshan Chen, Yuexi Yang, Xiangyu Pei, Feng Ji
In order to limit the short-circuit current of inverters, a logic-based bang-bang funnel control (LBFC) is designed to control the switches of inverter bridges when over-current is detected.
no code implementations • 30 Jan 2024 • Jie Li, Yi Liu, Chongyang Liu, Ling Shi, Xiaoning Ren, Yaowen Zheng, Yang Liu, Yinxing Xue
To address this research gap, we conducted an extensive empirical study on Multilingual Jailbreak attacks.
no code implementations • 30 Jan 2024 • Guangke Chen, Yedi Zhang, Fu Song, Ting Wang, Xiaoning Du, Yang Liu
To improve the imperceptibility of perturbations, we refine a psychoacoustic model-based loss with the backing track as an additional masker, a unique accompanying element for singing voices compared to ordinary speech voices.
no code implementations • 29 Jan 2024 • Yuqiang Sun, Daoyuan Wu, Yue Xue, Han Liu, Wei Ma, Lyuye Zhang, Miaolei Shi, Yang Liu
Large language models (LLMs) have demonstrated significant poten- tial for many downstream tasks, including those requiring human- level intelligence, such as vulnerability detection.
1 code implementation • 28 Jan 2024 • Liguo Zhou, Yinglei Song, Yichao Gao, Zhou Yu, Michael Sodamin, Hongshen Liu, Liang Ma, Lian Liu, Hao liu, Yang Liu, Haichuan Li, Guang Chen, Alois Knoll
However, the availability of free and open-source simulators is limited, and the installation and configuration process can be daunting for beginners and interdisciplinary researchers.
1 code implementation • 28 Jan 2024 • Yang Liu
It is often potentially encoded in human language, which is more common in texts on social issues.
no code implementations • 27 Jan 2024 • Foozhan Ataiefard, Walid Ahmed, Habib Hajimolahoseini, Saina Asani, Farnoosh Javadi, Mohammad Hassanpour, Omar Mohamed Awad, Austin Wen, Kangling Liu, Yang Liu
Our method does not add any parameters to the ViT model and aims to find the best trade-off between training throughput and achieving a 0% loss in the Top-1 accuracy of the final model.
no code implementations • 26 Jan 2024 • Yuxiang Hui, Yang Liu, Yaofang Liu, Fan Jia, Jinshan Pan, Raymond Chan, Tieyong Zeng
Video restoration task aims to recover high-quality videos from low-quality observations.
no code implementations • 24 Jan 2024 • Dezhao Luo, Shaogang Gong, Jiabo Huang, Hailin Jin, Yang Liu
We address two problems in video editing for optimising unseen domain VMR: (1) generation of high-quality simulation videos of different moments with subtle distinctions, (2) selection of simulation videos that complement existing source training videos without introducing harmful noise or unnecessary repetitions.
no code implementations • 23 Jan 2024 • Hengjia Li, Yang Liu, Yuqi Lin, Zhanwei Zhang, Yibo Zhao, weihang Pan, Tu Zheng, Zheng Yang, Yuchun Jiang, Boxi Wu, Deng Cai
In this paper, we propose UniHDA, a \textbf{unified} and \textbf{versatile} framework for generative hybrid domain adaptation with multi-modal references from multiple domains.
1 code implementation • 22 Jan 2024 • Yile Wang, Sijie Cheng, Zixin Sun, Peng Li, Yang Liu
We propose symbol-to-language (S2L), a tuning-free method that enables large language models to solve symbol-related problems with information expressed in natural language.
1 code implementation • 21 Jan 2024 • Yang Liu
Many evaluation measures are used to evaluate social biases in masked language models (MLMs).
1 code implementation • 19 Jan 2024 • Xiangshuo Qiao, Xianxin Li, Xiaozhe Qu, Jie Zhang, Yang Liu, Yu Luo, Cihang Jin, Jin Ma
Differently, video covers in short video search scenarios are presented as user-originated contents that provide important visual summaries of videos.
Ranked #1 on Image Retrieval on CBVS
no code implementations • 17 Jan 2024 • Zhiming Li, Yushi Cao, Xiufeng Xu, Junzhe Jiang, Xu Liu, Yon Shin Teo, Shang-Wei Lin, Yang Liu
Large language models (LLMs) have revolutionized many areas (e. g. natural language processing, software engineering, etc.)
1 code implementation • 17 Jan 2024 • Ziyang Yu, Wenbing Huang, Yang Liu
The study of rigid protein-protein docking plays an essential role in a variety of tasks such as drug design and protein engineering.
no code implementations • 11 Jan 2024 • Jiaheng Xie, Ruicheng Liang, Yidong Chai, Yang Liu, Daniel Zeng
To prevent widespread consequences, platforms are eager to predict these videos' impact on viewers' mental health.
1 code implementation • 10 Jan 2024 • Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, Yunxin Liu
Next, we discuss several key challenges to achieve intelligent, efficient and secure Personal LLM Agents, followed by a comprehensive survey of representative solutions to address these challenges.
no code implementations • 8 Jan 2024 • Yang Liu, Li Wan, Yun Li, Yiteng Huang, Ming Sun, James Luan, Yangyang Shi, Xin Lei
Despite the potential of diffusion models in speech enhancement, their deployment in Acoustic Echo Cancellation (AEC) has been restricted.
3 code implementations • 6 Jan 2024 • Jianqing Zhang, Yang Liu, Yang Hua, Jian Cao
To reduce the high communication cost of transmitting model parameters, a major challenge in HtFL, prototype-based HtFL methods are proposed to solely share class representatives, a. k. a, prototypes, among heterogeneous clients while maintaining the privacy of clients' models.
no code implementations • 6 Jan 2024 • Hongyi Guo, Yuanshun Yao, Wei Shen, Jiaheng Wei, Xiaoying Zhang, Zhaoran Wang, Yang Liu
The key idea is to first retrieve high-quality samples related to the target domain and use them as In-context Learning examples to generate more samples.
no code implementations • 1 Jan 2024 • Haodong Li, Gelei Deng, Yi Liu, Kailong Wang, Yuekang Li, Tianwei Zhang, Yang Liu, Guoai Xu, Guosheng Xu, Haoyu Wang
In this paper, we introduce a detailed framework designed to detect and assess the presence of content from potentially copyrighted books within the training datasets of LLMs.
1 code implementation • 31 Dec 2023 • Siyuan Li, Luyuan Zhang, Zedong Wang, Di wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li
As the deep learning revolution marches on, self-supervised learning has garnered increasing attention in recent years thanks to its remarkable representation learning ability and the low dependence on labeled data.
2 code implementations • 31 Dec 2023 • Dimitrios Psychogyios, Emanuele Colleoni, Beatrice van Amsterdam, Chih-Yang Li, Shu-Yu Huang, Yuchong Li, Fucang Jia, Baosheng Zou, Guotai Wang, Yang Liu, Maxence Boels, Jiayu Huo, Rachel Sparks, Prokar Dasgupta, Alejandro Granados, Sebastien Ourselin, Mengya Xu, An Wang, Yanan Wu, Long Bai, Hongliang Ren, Atsushi Yamada, Yuriko Harai, Yuto Ishikawa, Kazuyuki Hayashi, Jente Simoens, Pieter DeBacker, Francesco Cisternino, Gabriele Furnari, Alex Mottrie, Federica Ferraguti, Satoshi Kondo, Satoshi Kasai, Kousuke Hirasawa, Soohee Kim, Seung Hyun Lee, Kyu Eun Lee, Hyoun-Joong Kong, Kui Fu, Chao Li, Shan An, Stefanie Krell, Sebastian Bodenstedt, Nicolas Ayobi, Alejandra Perez, Santiago Rodriguez, Juanita Puentes, Pablo Arbelaez, Omid Mohareri, Danail Stoyanov
Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to decision support systems.
1 code implementation • 26 Dec 2023 • Weisong Sun, Chunrong Fang, Yudu You, Yuchen Chen, Yi Liu, Chong Wang, Jian Zhang, Quanjun Zhang, Hanwei Qian, Wei Zhao, Yang Liu, Zhenyu Chen
PromptCS trains a prompt agent that can generate continuous prompts to unleash the potential for LLMs in code summarization.
no code implementations • 25 Dec 2023 • Xicong Shen, Yang Liu, Huiqi Liu, Jue Hong, Bing Duan, Zirui Huang, Yunlong Mao, Ye Wu, Di wu
Fine-tuning is a prominent technique to adapt a pre-trained language model to downstream scenarios.
no code implementations • 24 Dec 2023 • Yinuo Du, Hanying Zhao, Yang Liu, Xinlei Yu, Yuan Shen
Accurate localization and perception are pivotal for enhancing the safety and reliability of vehicles.
no code implementations • 21 Dec 2023 • Guangyin Bao, Qi Zhang, Duoqian Miao, Zixuan Gong, Liang Hu, Ke Liu, Yang Liu, Chongyang Shi
In real-world scenarios, multimodal federated learning often faces the practical challenge of intricate modality missing, which poses constraints on building federated frameworks and significantly degrades model inference accuracy.
1 code implementation • 19 Dec 2023 • Xiangyu Liu, Yang Liu, Wei Hu
Knowledge graphs (KGs) often contain various errors.
no code implementations • 19 Dec 2023 • Min Xiong, Kaiyang Huang, Yang Liu, Rui Yao, Kai Sun, Feng Qiu
Case studies are conducted on EMT models of the IEEE 39-bus system and a synthetic 390-bus system to demonstrate the merits of the new simulation approach against traditional methods.
no code implementations • 19 Dec 2023 • Shuli Wang, Kun Gao, Lanfang Zhang, Yang Liu, Lei Chen
Specifically, based on a certain length of historical trajectory data, the situation-specific driving preferences of each driver are identified, where key driving behavior feature vectors are extracted to characterize heterogeneity in driving behavior among different drivers.
no code implementations • 10 Dec 2023 • Yongheng Deng, Ziqing Qiao, Ju Ren, Yang Liu, Yaoxue Zhang
While large language models (LLMs) are empowered with broad knowledge, their task-specific performance is often suboptimal.
no code implementations • 8 Dec 2023 • Bangyan He, Xiaojun Jia, Siyuan Liang, Tianrui Lou, Yang Liu, Xiaochun Cao
Current Visual-Language Pre-training (VLP) models are vulnerable to adversarial examples.
1 code implementation • 8 Dec 2023 • Jianqing Zhang, Yang Liu, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao
Amid the ongoing advancements in Federated Learning (FL), a machine learning paradigm that allows collaborative learning with data privacy protection, personalized FL (pFL) has gained significant prominence as a research direction within the FL domain.
no code implementations • 7 Dec 2023 • Yiqun Zhang, Zhenyue Qin, Yang Liu, Dylan Campbell
We introduce a pipeline to address anatomical inaccuracies in Stable Diffusion generated hand images.
no code implementations • 7 Dec 2023 • Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao
Investigating the generation of high-transferability adversarial examples is crucial for uncovering VLP models' vulnerabilities in practical scenarios.
no code implementations • 3 Dec 2023 • Xiaojun Jia, Jindong Gu, Yihao Huang, Simeng Qin, Qing Guo, Yang Liu, Xiaochun Cao
At the second stage, the pixels are divided into different branches based on their transferable property which is dependent on Kullback-Leibler divergence.
1 code implementation • 1 Dec 2023 • Weisong Sun, Chunrong Fang, Yun Miao, Yudu You, Mengzhe Yuan, Yuchen Chen, Quanjun Zhang, An Guo, Xiang Chen, Yang Liu, Zhenyu Chen
To do so, we compare the performance of models trained with code token sequence (Token for short) based code representation and AST-based code representation on three popular types of code-related tasks.
no code implementations • 30 Nov 2023 • Zineng Tang, ZiYi Yang, Mahmoud Khademi, Yang Liu, Chenguang Zhu, Mohit Bansal
We present CoDi-2, a versatile and interactive Multimodal Large Language Model (MLLM) that can follow complex multimodal interleaved instructions, conduct in-context learning (ICL), reason, chat, edit, etc., in an any-to-any input-output modality paradigm.
no code implementations • 29 Nov 2023 • Jiepeng Wang, Hao Pan, Yang Liu, Xin Tong, Taku Komura, Wenping Wang
Such a localized rewriting process enables probabilistic modeling of ambiguous structures and robust generalization across object categories.
1 code implementation • 29 Nov 2023 • Mutian Xu, Xingyilang Yin, Lingteng Qiu, Yang Liu, Xin Tong, Xiaoguang Han
We introduce SAMPro3D for zero-shot 3D indoor scene segmentation.
no code implementations • 29 Nov 2023 • Xiaoyue Mi, Fan Tang, Yepeng Weng, Danding Wang, Juan Cao, Sheng Tang, Peng Li, Yang Liu
Despite the effectiveness in improving the robustness of neural networks, adversarial training has suffered from the natural accuracy degradation problem, i. e., accuracy on natural samples has reduced significantly.
no code implementations • 29 Nov 2023 • Xiaoyue Mi, Fan Tang, Zonghan Yang, Danding Wang, Juan Cao, Peng Li, Yang Liu
Despite the remarkable advances that have been made in continual learning, the adversarial vulnerability of such methods has not been fully discussed.
no code implementations • 29 Nov 2023 • Taha Aksu, Devamanyu Hazarika, Shikib Mehri, Seokhwan Kim, Dilek Hakkani-Tür, Yang Liu, Mahdi Namazifar
We apply CESAR on InstructDial, a benchmark for instruction-based dialog tasks.
no code implementations • 29 Nov 2023 • Xianlun Peng, Yang Tang, Fangfei Li, Yang Liu
In this paper, we present a reinforcement learning (RL) method for solving optimal false data injection attack problems in probabilistic Boolean control networks (PBCNs) where the attacker lacks knowledge of the system model.
1 code implementation • 27 Nov 2023 • Yang Liu, Xiang Huang, Minghan Qin, Qinwei Lin, Haoqian Wang
Neural radiance fields are capable of reconstructing high-quality drivable human avatars but are expensive to train and render.
1 code implementation • 27 Nov 2023 • Sijie Cheng, Zhicheng Guo, Jingwen Wu, Kechen Fang, Peng Li, Huaping Liu, Yang Liu
However, the capability of VLMs to "think" from a first-person perspective, a crucial attribute for advancing autonomous agents and robotics, remains largely unexplored.
no code implementations • 25 Nov 2023 • Habib Hajimolahoseini, Omar Mohamed Awad, Walid Ahmed, Austin Wen, Saina Asani, Mohammad Hassanpour, Farnoosh Javadi, Mehdi Ahmadi, Foozhan Ataiefard, Kangling Liu, Yang Liu
In this paper, we present SwiftLearn, a data-efficient approach to accelerate training of deep learning models using a subset of data samples selected during the warm-up stages of training.
no code implementations • 24 Nov 2023 • Di Jin, Shikib Mehri, Devamanyu Hazarika, Aishwarya Padmakumar, Sungjin Lee, Yang Liu, Mahdi Namazifar
Learning from human feedback is a prominent technique to align the output of large language models (LLMs) with human expectations.
no code implementations • 23 Nov 2023 • Ruixuan Liu, Ming Hu, Zeke Xia, Jun Xia, Pengyu Zhang, Yihao Huang, Yang Liu, Mingsong Chen
On the one hand, to achieve model training in all the diverse clients, mobile computing systems can only use small low-performance models for collaborative learning.
no code implementations • 22 Nov 2023 • Chentao Jia, Ming Hu, Zekai Chen, Yanxin Yang, Xiaofei Xie, Yang Liu, Mingsong Chen
Although Federated Learning (FL) is promising to enable collaborative learning among Artificial Intelligence of Things (AIoT) devices, it suffers from the problem of low classification performance due to various heterogeneity factors (e. g., computing capacity, memory size) of devices and uncertain operating environments.
1 code implementation • 21 Nov 2023 • Youqi Liao, Shuhao Kang, Jianping Li, Yang Liu, Yun Liu, Zhen Dong, Bisheng Yang, Xieyuanli Chen
Our framework features a two-stream encoder, an active fusion decoder (AFD) and a dual-task regularization approach.
no code implementations • 21 Nov 2023 • Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William A Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlaš, Ahmed Alaa, Adji Bousso Dieng, Natasha Noy, Vijay Janapa Reddi, James Zou, Praveen Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
Drawing from discussions at the inaugural DMLR workshop at ICML 2023 and meetings prior, in this report we outline the relevance of community engagement and infrastructure development for the creation of next-generation public datasets that will advance machine learning science.
1 code implementation • 20 Nov 2023 • Ziyue Wang, Chi Chen, Peng Li, Yang Liu
Large Language Models (LLMs) demonstrate impressive reasoning ability and the maintenance of world knowledge not only in natural language tasks, but also in some vision-language tasks such as open-domain knowledge-based visual question answering (OK-VQA).
1 code implementation • Scientific Reports 2023 • Shuo Zhang, Yang Liu, Lei Xie
Molecular sciences address a wide range of problems involving molecules of different types and sizes and their complexes.
Ranked #1 on Drug Discovery on QM9
1 code implementation • 19 Nov 2023 • Zhaowei Zhu, Jialu Wang, Hao Cheng, Yang Liu
Given the cost and difficulty of cleaning these datasets by humans, we introduce a systematic framework for evaluating the credibility of datasets, identifying label errors, and evaluating the influence of noisy labels in the curated language data, specifically focusing on unsafe comments and conversation classification.
1 code implementation • 8 Nov 2023 • Ze-Feng Gao, Shuai Qu, Bocheng Zeng, Yang Liu, Ji-Rong Wen, Hao Sun, Peng-Jie Guo, Zhong-Yi Lu
Altermagnetism, a new magnetic phase, has been theoretically proposed and experimentally verified to be distinct from ferromagnetism and antiferromagnetism.
no code implementations • 7 Nov 2023 • Feng Ji, Lu Gao, Chang Lin, Yang Liu
This paper proposes to analyze the motion stability of synchro-nous generator power systems using a Lagrangian model derived in the configuration space of generalized position and speed.
no code implementations • 6 Nov 2023 • Gianmarco Ipinze Tutuianu, Yang Liu, Ari Alamäki, Janne Kauttonen
Facial expression recognition (FER) is a crucial part of human-computer interaction.
no code implementations • 6 Nov 2023 • Farnoosh Javadi, Walid Ahmed, Habib Hajimolahoseini, Foozhan Ataiefard, Mohammad Hassanpour, Saina Asani, Austin Wen, Omar Mohamed Awad, Kangling Liu, Yang Liu
We tested our method on ViT, which achieved an approximate 0. 3% increase in accuracy while reducing the model size by about 4% in the task of image classification.
1 code implementation • 5 Nov 2023 • Zeyu Tang, Jialu Wang, Yang Liu, Peter Spirtes, Kun Zhang
We reveal and address the frequently overlooked yet important issue of disguised procedural unfairness, namely, the potentially inadvertent alterations on the behavior of neutral (i. e., not problematic) aspects of data generating process, and/or the lack of procedural assurance of the greatest benefit of the least advantaged individuals.
1 code implementation • 30 Oct 2023 • Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Tu Zheng, Zheng Yang, Wenxiao Wang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He
Concretely, the distance loss blends the attributes of all target domains by reducing the distances from generated images to all target subspaces.
no code implementations • 29 Oct 2023 • Hao Zhang, Yang Liu, Xiaoyan Liu, Tianming Liang, Gaurav Sharma, Liang Xue, Maozu Guo
We introduce a novel graph-based framework for alleviating key challenges in distantly-supervised relation extraction and demonstrate its effectiveness in the challenging and important domain of biomedical data.
1 code implementation • 24 Oct 2023 • Zeyuan Yang, Peng Li, Yang Liu
Large Language Models (LLMs) have showcased impressive performance.
1 code implementation • 19 Oct 2023 • Siru Ouyang, Shuohang Wang, Yang Liu, Ming Zhong, Yizhu Jiao, Dan Iter, Reid Pryzant, Chenguang Zhu, Heng Ji, Jiawei Han
Recent progress in Large Language Models (LLMs) has produced models that exhibit remarkable performance across a variety of NLP tasks.
no code implementations • 19 Oct 2023 • Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang
Large language models (LLMs) can perform a wide range of tasks by following natural language instructions, without the necessity of task-specific fine-tuning.
no code implementations • 18 Oct 2023 • Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor Tsang, Yang Liu, Qing Guo
The underlying rationale behind our idea is that image resampling can alleviate the influence of adversarial perturbations while preserving essential semantic information, thereby conferring an inherent advantage in defending against adversarial attacks.
1 code implementation • 18 Oct 2023 • Shuhan Zhong, Sizhe Song, Guanyao Li, Weipeng Zhuo, Yang Liu, S. -H. Gary Chan
Time series data, often characterized by unique composition and complex multi-scale temporal variations, requires special consideration of decomposition and multi-scale modeling in its analysis.
no code implementations • 17 Oct 2023 • Yaofang Liu, Xiaodong Cun, Xuebo Liu, Xintao Wang, Yong Zhang, Haoxin Chen, Yang Liu, Tieyong Zeng, Raymond Chan, Ying Shan
However, these methods often use a few academic metrics, for example, FVD or IS, to evaluate the performance.
no code implementations • 17 Oct 2023 • Yang Liu, Shi Gu
Our results show that our method can accurately achieve the registration of pathological images and identify lesions even in challenging imaging modalities.
1 code implementation • 15 Oct 2023 • Tianyuan Zou, Zixuan Gu, Yu He, Hideaki Takahashi, Yang Liu, Guangnan Ye, Ya-Qin Zhang
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters.
1 code implementation • 14 Oct 2023 • Yuanshun Yao, Xiaojun Xu, Yang Liu
To the best of our knowledge, our work is among the first to explore LLM unlearning.
no code implementations • 13 Oct 2023 • Yang Liu, Deyu Bo, Chuan Shi
The increasing amount of graph data places requirements on the efficiency and scalability of graph neural networks (GNNs), despite their effectiveness in various graph-related applications.
no code implementations • 9 Oct 2023 • Tongxin Yin, Jean-François Ton, Ruocheng Guo, Yuanshun Yao, Mingyan Liu, Yang Liu
To generalize the abstaining decisions to test samples, we then train a surrogate model to learn the abstaining decisions based on the IP solutions in an end-to-end manner.
no code implementations • 9 Oct 2023 • Zhiming Li, Junzhe Jiang, Yushi Cao, Aixin Cui, Bozhi Wu, Bo Li, Yang Liu
In this paper, we propose a novel logic-guided trading framework, termed as SYENS (Program Synthesis-based Ensemble Strategy).
no code implementations • 9 Oct 2023 • Yang Liu, Melissa Xiaohui Qin, Long Wang, Chao Huang
The ontology of data would make the corpus a helpful resource with enormous research potential for Asian Englishes (especially for Chinese Englishes for which there has not been a publicly accessible corpus yet so far) and an ideal source for variety-specific language modeling and downstream tasks, thus setting the stage for NLP-based World Englishes studies.
1 code implementation • 9 Oct 2023 • Wenlong Chen, Yegor Klochkov, Yang Liu
We consider a binary classification problem under group fairness constraints, which can be one of Demographic Parity (DP), Equalized Opportunity (EOp), or Equalized Odds (EO).
no code implementations • 9 Oct 2023 • Yegor Klochkov, Jean-Francois Ton, Ruocheng Guo, Yang Liu, Hang Li
We address the problem of concept removal in deep neural networks, aiming to learn representations that do not encode certain specified concepts (e. g., gender etc.)
no code implementations • 8 Oct 2023 • Yile Wang, Peng Li, Maosong Sun, Yang Liu
Large language models (LLMs) have shown superior performance without task-specific fine-tuning.
no code implementations • 4 Oct 2023 • Zihao Zhao, Zhenpeng Shi, Yang Liu, Wenbo Ding
Federated Learning (FL) is often impeded by communication overhead issues.
1 code implementation • 3 Oct 2023 • Zijun Liu, Yanzhe Zhang, Peng Li, Yang Liu, Diyi Yang
We further design an automatic agent team optimization algorithm based on an unsupervised metric termed $\textit{Agent Importance Score}$, enabling the selection of best agents based on the contribution each agent makes.
no code implementations • 29 Sep 2023 • Zongjie Li, Chaozheng Wang, Pingchuan Ma, Daoyuan Wu, Shuai Wang, Cuiyun Gao, Yang Liu
Specifically, PORTIA splits the answers into multiple segments, aligns similar content across candidate answers, and then merges them back into a single prompt for evaluation by LLMs.
no code implementations • 28 Sep 2023 • Zheyuan Yang, Yibo Liu, Guile Wu, Tongtong Cao, Yuan Ren, Yang Liu, Bingbing Liu
To resolve this problem, we study learning effective NeRFs and SDFs representations with 3D Generative Adversarial Networks (GANs) for 3D object generation.
1 code implementation • 25 Sep 2023 • Yang Liu, Chen Chen, Can Wang, Xulin King, Mengyuan Liu
The proposed method decouples functions between the decoder and the encoder by introducing a mask regressor, which predicts the masked patch representation from the visible patch representation encoded by the encoder and the decoder reconstructs the target from the predicted masked patch representation.
Ranked #3 on Few-Shot 3D Point Cloud Classification on ModelNet40 10-way (20-shot) (using extra training data)
Few-Shot 3D Point Cloud Classification Representation Learning +1
no code implementations • 21 Sep 2023 • Walid Ahmed, Habib Hajimolahoseini, Austin Wen, Yang Liu
Compression of a neural network can help in speeding up both the training and the inference of the network.
1 code implementation • 20 Sep 2023 • Guan Wang, Sijie Cheng, Xianyuan Zhan, Xiangang Li, Sen Song, Yang Liu
Specifically, we consider the general SFT training data, consisting of a small amount of expert data mixed with a large proportion of sub-optimal data, without any preference labels.
Ranked #20 on Code Generation on HumanEval
no code implementations • 19 Sep 2023 • Hao Guo, Hongbiao Si, Guilin Jiang, Wei zhang, Zhiyan Liu, Xuanyi Zhu, xulong Zhang, Yang Liu
What's more, various methods utilize attention in semantic segmentation, but the conclusion of these methods is lacking.
no code implementations • 18 Sep 2023 • Zhicheng Du, Chenyao Jiang, Xi Yuan, Shiyao Zhai, Zhengyang Lei, Shuyue Ma, Yang Liu, Qihui Ye, Chufan Xiao, Qiming Huang, Ming Xu, Dongmei Yu, Peiwu Qin
The timely identification of mental disorders in adolescents is a global public health challenge. Single factor is difficult to detect the abnormality due to its complex and subtle nature.
1 code implementation • 16 Sep 2023 • Jiaheng Wei, Harikrishna Narasimhan, Ehsan Amid, Wen-Sheng Chu, Yang Liu, Abhishek Kumar
We investigate the problem of training models that are robust to shifts caused by changes in the distribution of class-priors or group-priors.
no code implementations • 15 Sep 2023 • Yangyang Shi, Gael Le Lan, Varun Nagaraja, Zhaoheng Ni, Xinhao Mei, Ernie Chang, Forrest Iandola, Yang Liu, Vikas Chandra
This paper presents an innovative approach to enhance control over audio generation by emphasizing the alignment between audio and text representations during model training.
no code implementations • 13 Sep 2023 • Zihao Zhao, Yang Liu, Wenbo Ding, Xiao-Ping Zhang
Existing research has either adapted the Probably Approximately Correct (PAC) Bayesian framework for federated learning (FL) or used information-theoretic PAC-Bayesian bounds while introducing their theorems, but few considering the non-IID challenges in FL.
no code implementations • 11 Sep 2023 • Chien-Chih Wang, Shaoyuan Xu, Jinmiao Fu, Yang Liu, Bryan Wang
Firstly, an outer SNN is trained using labeled and unlabeled data.
no code implementations • 9 Sep 2023 • Yuzhuang Xu, Shuo Wang, Peng Li, Fuwen Luo, Xiaolong Wang, Weidong Liu, Yang Liu
Communication games, which we refer to as incomplete information games that heavily depend on natural language communication, hold significant research value in fields such as economics, social science, and artificial intelligence.
no code implementations • 7 Sep 2023 • Omar Mohamed Awad, Habib Hajimolahoseini, Michael Lim, Gurpreet Gosal, Walid Ahmed, Yang Liu, Gordon Deng
This paper presents our proposed approach that won the first prize at the ICLR competition on Hardware Aware Efficient Training.
1 code implementation • ICCV 2023 • Ting Lei, Fabian Caba, Qingchao Chen, Hailin Jin, Yuxin Peng, Yang Liu
This observation motivates us to design an HOI detector that can be trained even with long-tailed labeled data and can leverage existing knowledge from pre-trained models.
no code implementations • 7 Sep 2023 • Habib Hajimolahoseini, Walid Ahmed, Yang Liu
Low Rank Decomposition (LRD) is a model compression technique applied to the weight tensors of deep learning models in order to reduce the number of trainable parameters and computational complexity.
no code implementations • 5 Sep 2023 • Ian Hardy, Jayanth Yetukuri, Yang Liu
Recent work has connected adversarial attack methods and algorithmic recourse methods: both seek minimal changes to an input instance which alter a model's classification decision.
no code implementations • 5 Sep 2023 • Jayanth Yetukuri, Ian Hardy, Yang Liu
Machine Learning's proliferation in critical fields such as healthcare, banking, and criminal justice has motivated the creation of tools which ensure trust and transparency in ML models.
no code implementations • 1 Sep 2023 • Yang Liu, Christopher M. Harvey, Frederick E. Hamlyn, Cunjia Liu
The PDE model is spatially discretised into a linear state-space model using the dynamic transient finite-element method (FEM) so that the characterisation of time-varying dispersion can be cast into the problem of inferring the model states from sensor measurements.
no code implementations • 31 Aug 2023 • Yang Liu, Xiaoyun Zhong, Shiyao Zhai, Zhicheng Du, Zhenyuan Gao, Qiming Huang, Canyang Zhang, Bin Jiang, Vijay Kumar Pandey, Sanyang Han, Runming Wang, Yuxing Han, Peiwu Qin
The vast majority of people who suffer unexpected cardiac arrest are performed cardiopulmonary resuscitation (CPR) by passersby in a desperate attempt to restore life, but endeavors turn out to be fruitless on account of disqualification.
no code implementations • 31 Aug 2023 • Ya Zhou, Xiaolin Diao, Yanni Huo, Yang Liu, Xiaohan Fan, Wei Zhao
We construct a dataset comprising 220, 251 ECG recordings with a broad range of diagnoses annoated by medical experts to explore the properties of MTECG.
no code implementations • 30 Aug 2023 • Yi Liu, Yuekang Li, Gelei Deng, Felix Juefei-Xu, Yao Du, Cen Zhang, Chengwei Liu, Yeting Li, Lei Ma, Yang Liu
To improve the accessibility of ASR systems for stutterers, we need to expose and analyze the failures of ASR systems on stuttering speech.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
1 code implementation • 28 Aug 2023 • Yang Liu, Cheng Yu, Lei Shang, Yongyi He, Ziheng Wu, Xingjun Wang, Chao Xu, Haoyu Xie, Weida Wang, Yuze Zhao, Lin Zhu, Chen Cheng, Weitao Chen, Yuan YAO, Wenmeng Zhou, Jiaqi Xu, Qiang Wang, Yingda Chen, Xuansong Xie, Baigui Sun
In this paper, we present FaceChain, a personalized portrait generation framework that combines a series of customized image-generation model and a rich set of face-related perceptual understanding models (\eg, face detection, deep face embedding extraction, and facial attribute recognition), to tackle aforementioned challenges and to generate truthful personalized portraits, with only a handful of portrait images as input.
1 code implementation • 25 Aug 2023 • Chi Chen, Ruoyu Qin, Fuwen Luo, Xiaoyue Mi, Peng Li, Maosong Sun, Yang Liu
However, existing visual instruction tuning methods only utilize image-language instruction data to align the language and image modalities, lacking a more fine-grained cross-modal alignment.
no code implementations • 25 Aug 2023 • Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong
Furthermore, we offer theoretical insights into SEGNO, highlighting that it can learn a unique trajectory between adjacent states, which is crucial for model generalization.
2 code implementations • 23 Aug 2023 • Ziyi Tang, Ruilin Wang, Weixing Chen, Keze Wang, Yang Liu, Tianshui Chen, Liang Lin
Despite advancements in LLMs, knowledge-based reasoning remains a longstanding issue due to the fragility of knowledge recall and inference.
no code implementations • 22 Aug 2023 • Yanxin Yang, Ming Hu, Yue Cao, Jun Xia, Yihao Huang, Yang Liu, Mingsong Chen
By using these trigger images, our approach eliminates poisoned models to ensure the updated global model is benign.