no code implementations • LREC 2022 • Liang Zhao, Eleanor Chodroff
In the present paper, we introduce the ManDi Corpus, a spoken corpus of regional Mandarin dialects and Standard Mandarin.
no code implementations • 5 Feb 2025 • Zining Zhu, Liang Zhao, Kangheng Lin, Jinze Yang, En Yu, Chenglong Liu, Haoran Wei, Jianjian Sun, Zheng Ge, Xiangyu Zhang
This paper presents Perceptual Preference Optimization (PerPO), a perception alignment method aimed at addressing the visual discrimination challenges in generative pre-trained multimodal large language models (MLLMs).
no code implementations • 5 Feb 2025 • Yawen Chen, Jiande Sun, Jinhui Wang, Liang Zhao, Xinmin Song, Linbo Zhai
To this end, this study integrates the results of machine learning-based student performance prediction with tiered instruction, aiming to enhance student outcomes in target course, which is significant for the application of educational data mining in contemporary teaching scenarios.
1 code implementation • 3 Feb 2025 • Dazhou Yu, Genpei Zhang, Liang Zhao
This study proposes \textbf{PolyhedronNet}, a general framework tailored for learning representations of 3D polyhedral objects.
no code implementations • 25 Jan 2025 • Yuntong Hu, Zhihan Lei, Zhongjie Dai, Allen Zhang, Abhinav Angirekula, Zheng Zhang, Liang Zhao
In this paper, we introduce Contextualized Graph Retrieval-Augmented Generation (CG-RAG), a novel framework that integrates sparse and dense retrieval signals within graph structures to enhance retrieval efficiency and subsequently improve generation quality for research question answering.
2 code implementations • 22 Jan 2025 • DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, Xingkai Yu, Yu Wu, Z. F. Wu, Zhibin Gou, Zhihong Shao, Zhuoshu Li, Ziyi Gao, Aixin Liu, Bing Xue, Bingxuan Wang, Bochao Wu, Bei Feng, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Qu, Hui Li, JianZhong Guo, Jiashi Li, Jiawei Wang, Jingchang Chen, Jingyang Yuan, Junjie Qiu, Junlong Li, J. L. Cai, Jiaqi Ni, Jian Liang, Jin Chen, Kai Dong, Kai Hu, Kaige Gao, Kang Guan, Kexin Huang, Kuai Yu, Lean Wang, Lecong Zhang, Liang Zhao, Litong Wang, Liyue Zhang, Lei Xu, Leyi Xia, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Meng Li, Miaojun Wang, Mingming Li, Ning Tian, Panpan Huang, Peng Zhang, Qiancheng Wang, Qinyu Chen, Qiushi Du, Ruiqi Ge, Ruisong Zhang, Ruizhe Pan, Runji Wang, R. J. Chen, R. L. Jin, Ruyi Chen, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shiyu Wang, Shuiping Yu, Shunfeng Zhou, Shuting Pan, S. S. Li, Shuang Zhou, Shaoqing Wu, Shengfeng Ye, Tao Yun, Tian Pei, Tianyu Sun, T. Wang, Wangding Zeng, Wanjia Zhao, Wen Liu, Wenfeng Liang, Wenjun Gao, Wenqin Yu, Wentao Zhang, W. L. Xiao, Wei An, Xiaodong Liu, Xiaohan Wang, Xiaokang Chen, Xiaotao Nie, Xin Cheng, Xin Liu, Xin Xie, Xingchao Liu, Xinyu Yang, Xinyuan Li, Xuecheng Su, Xuheng Lin, X. Q. Li, Xiangyue Jin, Xiaojin Shen, Xiaosha Chen, Xiaowen Sun, Xiaoxiang Wang, Xinnan Song, Xinyi Zhou, Xianzu Wang, Xinxia Shan, Y. K. Li, Y. Q. Wang, Y. X. Wei, Yang Zhang, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Wang, Yi Yu, Yichao Zhang, Yifan Shi, Yiliang Xiong, Ying He, Yishi Piao, Yisong Wang, Yixuan Tan, Yiyang Ma, Yiyuan Liu, Yongqiang Guo, Yuan Ou, Yuduan Wang, Yue Gong, Yuheng Zou, Yujia He, Yunfan Xiong, Yuxiang Luo, Yuxiang You, Yuxuan Liu, Yuyang Zhou, Y. X. Zhu, Yanhong Xu, Yanping Huang, Yaohui Li, Yi Zheng, Yuchen Zhu, Yunxian Ma, Ying Tang, Yukun Zha, Yuting Yan, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhean Xu, Zhenda Xie, Zhengyan Zhang, Zhewen Hao, Zhicheng Ma, Zhigang Yan, Zhiyu Wu, Zihui Gu, Zijia Zhu, Zijun Liu, Zilin Li, Ziwei Xie, Ziyang Song, Zizheng Pan, Zhen Huang, Zhipeng Xu, Zhongyu Zhang, Zhen Zhang
We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1.
Ranked #1 on
Mathematical Reasoning
on AIME24
no code implementations • 6 Jan 2025 • Manh V. Nguyen, Liang Zhao, Bobin Deng, Shaoen Wu
Spiking Neural Networks (SNNs), which offer exceptional energy efficiency for inference, and Federated Learning (FL), which offers privacy-preserving distributed training, is a rising area of interest that highly beneficial towards Internet of Things (IoT) devices.
no code implementations • 30 Dec 2024 • Haoran Wei, Youyang Yin, Yumeng Li, Jia Wang, Liang Zhao, Jianjian Sun, Zheng Ge, Xiangyu Zhang, Daxin Jiang
Recently, "visual o1" began to enter people's vision, with expectations that this slow-thinking design can solve visual reasoning tasks, especially geometric math problems.
1 code implementation • 27 Dec 2024 • DeepSeek-AI, Aixin Liu, Bei Feng, Bing Xue, Bingxuan Wang, Bochao Wu, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J. L. Cai, Jian Liang, JianZhong Guo, Jiaqi Ni, Jiashi Li, Jiawei Wang, Jin Chen, Jingchang Chen, Jingyang Yuan, Junjie Qiu, Junlong Li, Junxiao Song, Kai Dong, Kai Hu, Kaige Gao, Kang Guan, Kexin Huang, Kuai Yu, Lean Wang, Lecong Zhang, Lei Xu, Leyi Xia, Liang Zhao, Litong Wang, Liyue Zhang, Meng Li, Miaojun Wang, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Mingming Li, Ning Tian, Panpan Huang, Peiyi Wang, Peng Zhang, Qiancheng Wang, Qihao Zhu, Qinyu Chen, Qiushi Du, R. J. Chen, R. L. Jin, Ruiqi Ge, Ruisong Zhang, Ruizhe Pan, Runji Wang, Runxin Xu, Ruoyu Zhang, Ruyi Chen, S. S. Li, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shaoqing Wu, Shengfeng Ye, Shirong Ma, Shiyu Wang, Shuang Zhou, Shuiping Yu, Shunfeng Zhou, Shuting Pan, T. Wang, Tao Yun, Tian Pei, Tianyu Sun, W. L. Xiao, Wangding Zeng, Wanjia Zhao, Wei An, Wen Liu, Wenfeng Liang, Wenjun Gao, Wenqin Yu, Wentao Zhang, X. Q. Li, Xiangyue Jin, Xianzu Wang, Xiao Bi, Xiaodong Liu, Xiaohan Wang, Xiaojin Shen, Xiaokang Chen, Xiaokang Zhang, Xiaosha Chen, Xiaotao Nie, Xiaowen Sun, Xiaoxiang Wang, Xin Cheng, Xin Liu, Xin Xie, Xingchao Liu, Xingkai Yu, Xinnan Song, Xinxia Shan, Xinyi Zhou, Xinyu Yang, Xinyuan Li, Xuecheng Su, Xuheng Lin, Y. K. Li, Y. Q. Wang, Y. X. Wei, Y. X. Zhu, Yang Zhang, Yanhong Xu, Yanping Huang, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Li, Yaohui Wang, Yi Yu, Yi Zheng, Yichao Zhang, Yifan Shi, Yiliang Xiong, Ying He, Ying Tang, Yishi Piao, Yisong Wang, Yixuan Tan, Yiyang Ma, Yiyuan Liu, Yongqiang Guo, Yu Wu, Yuan Ou, Yuchen Zhu, Yuduan Wang, Yue Gong, Yuheng Zou, Yujia He, Yukun Zha, Yunfan Xiong, Yunxian Ma, Yuting Yan, Yuxiang Luo, Yuxiang You, Yuxuan Liu, Yuyang Zhou, Z. F. Wu, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhean Xu, Zhen Huang, Zhen Zhang, Zhenda Xie, Zhengyan Zhang, Zhewen Hao, Zhibin Gou, Zhicheng Ma, Zhigang Yan, Zhihong Shao, Zhipeng Xu, Zhiyu Wu, Zhongyu Zhang, Zhuoshu Li, Zihui Gu, Zijia Zhu, Zijun Liu, Zilin Li, Ziwei Xie, Ziyang Song, Ziyi Gao, Zizheng Pan
We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token.
no code implementations • 18 Dec 2024 • Xin Wang, Boyan Gao, Yi Dai, Lei Cao, Liang Zhao, Yibo Yang, David Clifton
We further study the benefits brought by the proposed Cognition Chain format by utilising it as a synthetic dataset generation template for LLMs instruction-tuning and introduce CogInstruct, an instruction-tuning dataset for stress detection.
1 code implementation • 13 Dec 2024 • Zhiyu Wu, Xiaokang Chen, Zizheng Pan, Xingchao Liu, Wen Liu, Damai Dai, Huazuo Gao, Yiyang Ma, Chengyue Wu, Bingxuan Wang, Zhenda Xie, Yu Wu, Kai Hu, Jiawei Wang, Yaofeng Sun, Yukun Li, Yishi Piao, Kang Guan, Aixin Liu, Xin Xie, Yuxiang You, Kai Dong, Xingkai Yu, Haowei Zhang, Liang Zhao, Yisong Wang, Chong Ruan
We present DeepSeek-VL2, an advanced series of large Mixture-of-Experts (MoE) Vision-Language Models that significantly improves upon its predecessor, DeepSeek-VL, through two key major upgrades.
Ranked #1 on
Referring Expression Comprehension
on RefCOCOg-test
1 code implementation • 13 Dec 2024 • Liang Zhao, Zehan Bao, Yi Xie, Hong Chen, Yaohui Chen, Weifu Li
Recent advances in Gaussian Splatting have significantly advanced the field, achieving both panoptic and interactive segmentation of 3D scenes.
no code implementations • 13 Dec 2024 • Nobel Dhar, Bobin Deng, Md Romyull Islam, Kazi Fahim Ahmad Nasif, Liang Zhao, Kun Suo
To obtain the benefits of activation sparsity, we provide a guideline for the system architect for LLM prediction and prefetching.
no code implementations • 11 Dec 2024 • Hongning Ruan, Yulin Shao, Qianqian Yang, Liang Zhao, Zhaoyang Zhang, Dusit Niyato
Our approach employs two coordinate-based neural networks to implicitly represent a voxelized point cloud: the first determines the occupancy status of a voxel, while the second predicts the attributes of occupied voxels.
no code implementations • 9 Dec 2024 • Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong
In recent years, large language models (LLMs) have been widely adopted in political science tasks such as election prediction, sentiment analysis, policy impact assessment, and misinformation detection.
no code implementations • 20 Nov 2024 • Yifei Zhang, Tianxu Jiang, Bo Pan, Jingyu Wang, Guangji Bai, Liang Zhao
A Visual Explanation Distribution Consistency loss further reinforces visual coherence by aligning the generated visual explanations with dataset-level patterns, enabling the model to effectively learn from incomplete multimodal supervision.
1 code implementation • 19 Nov 2024 • Shipeng Liu, Liang Zhao, Dengfeng Chen
As an essential visual attribute, image complexity affects human image comprehension and directly influences the performance of computer vision tasks.
1 code implementation • 12 Nov 2024 • Yiyang Ma, Xingchao Liu, Xiaokang Chen, Wen Liu, Chengyue Wu, Zhiyu Wu, Zizheng Pan, Zhenda Xie, Haowei Zhang, Xingkai Yu, Liang Zhao, Yisong Wang, Jiaying Liu, Chong Ruan
To further improve the performance of our unified model, we adopt two key strategies: (i) decoupling the understanding and generation encoders, and (ii) aligning their representations during unified training.
Ranked #197 on
Visual Question Answering
on MM-Vet
no code implementations • 27 Oct 2024 • Longyan Li, Chao Ning, Guangsheng Pan, Leiqi Zhang, Wei Gu, Liang Zhao, Wenli Du, Mohammad Shahidehpour
Based upon this model, a data-driven RAJIT scheme is developed for the real-time rolling optimization of AHMGs.
no code implementations • 23 Oct 2024 • Xiguang Li, Jiafu Chen, Yunhe Sun, Na Lin, Ammar Hawbani, Liang Zhao
With the rapid advancement of autonomous driving technology, efficient and accurate object detection capabilities have become crucial factors in ensuring the safety and reliability of autonomous driving systems.
no code implementations • 20 Oct 2024 • Bo Pan, Zhen Xiong, Guanchen Wu, Zheng Zhang, Yifei Zhang, Liang Zhao
Despite advancements in TAG learning methodologies, challenges remain in explainability due to the black-box nature of existing TAG representation learning models.
no code implementations • 18 Oct 2024 • Guangji Bai, Yijiang Li, Zilinghan Li, Liang Zhao, Kibaek Kim
Large Language Models (LLMs) achieve state-of-the-art performance but are challenging to deploy due to their high computational and storage demands.
no code implementations • 17 Oct 2024 • Lei Huang, Xiaocheng Feng, Weitao Ma, Liang Zhao, Yuchun Fan, Weihong Zhong, Dongliang Xu, Qing Yang, Hongtao Liu, Bing Qin
Teaching large language models (LLMs) to generate text with citations to evidence sources can mitigate hallucinations and enhance verifiability in information-seeking systems.
no code implementations • 2 Oct 2024 • Yuntong Hu, Zhuofeng Li, Zheng Zhang, Chen Ling, Raasikh Kanjiani, Boxin Zhao, Liang Zhao
In this work, we present HiReview, a novel framework for hierarchical taxonomy-driven automatic literature review generation.
no code implementations • 19 Sep 2024 • Manh V. Nguyen, Liang Zhao, Bobin Deng, William Severa, Honghui Xu, Shaoen Wu
Spiking Neural Networks (SNNs) have recently gained significant interest in on-chip learning in embedded devices and emerged as an energy-efficient alternative to conventional Artificial Neural Networks (ANNs).
no code implementations • 18 Sep 2024 • Cuiwei Liu, Siang Xu, Huaijun Qiu, Jing Zhang, Zhi Liu, Liang Zhao
Within this framework, a noise-aware generative replay module is developed to fine-tune local models with a balance of new and replay data, while generating synthetic data of new classes to further expand the replay buffer for future tasks.
class-incremental learning
Few-Shot Class-Incremental Learning
+3
1 code implementation • 6 Sep 2024 • Muniba Batool, Naveed Ahmed Azam, Jianshen Zhu, Kazuya Haraguchi, Liang Zhao, Tatsuya Akutsu
Aqueous solubility (AS) is a key physiochemical property that plays a crucial role in drug discovery and material design.
1 code implementation • 4 Sep 2024 • Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang
Multiobjective optimization problems (MOPs) are prevalent in machine learning, with applications in multi-task learning, learning under fairness or robustness constraints, etc.
no code implementations • 3 Sep 2024 • Haoran Wei, Chenglong Liu, Jinyue Chen, Jia Wang, Lingyu Kong, Yanming Xu, Zheng Ge, Liang Zhao, Jianjian Sun, Yuang Peng, Chunrui Han, Xiangyu Zhang
As an OCR-2. 0 model, GOT can handle all the above "characters" under various OCR tasks.
no code implementations • 3 Sep 2024 • Daosong Hu, Ruomeng Wang, Liang Zhao, Mingyue Cui, Song Ding, Kai Huang
In this paper, we propose a method for generating a 4D coronary artery trees, which maps the systole to the diastole through deformation field prediction, interpolates on the timeline, and the motion trajectory of points are obtained.
no code implementations • 16 Aug 2024 • Zheng Zhang, Allen Zhang, Ruth Nelson, Giorgio Ascoli, Liang Zhao
Geometric trees are characterized by their tree-structured layout and spatially constrained nodes and edges, which significantly impacts their topological attributes.
1 code implementation • 9 Aug 2024 • Bowen Song, Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Tatsuya Akutsu
In this paper, we propose a novel family of descriptors of chemical graphs, named cycle-configuration (CC), that can be used in the standard "two-layered (2L) model" of mol-infer, a molecular inference framework based on mixed integer linear programming (MILP) and machine learning (ML).
no code implementations • 6 Aug 2024 • Shipeng Liu, Liang Zhao, Dengfeng Chen, Zhanping Song
The results demonstrate that the performance of CLIC is comparable to that of state-of-the-art supervised methods.
no code implementations • 23 Jul 2024 • Liang Zhao, Qing Guo, Xiaoguang Li, Song Wang
In this work, we identify the visual-text inpainting task to achieve high-quality scene text image restoration and text completion: Given a scene text image with unknown missing regions and the corresponding text with unknown missing characters, we aim to complete the missing information in both images and text by leveraging their complementary information.
no code implementations • 11 Jul 2024 • Liang Zeng, Liangjun Zhong, Liang Zhao, Tianwen Wei, Liu Yang, Jujie He, Cheng Cheng, Rui Hu, Yang Liu, Shuicheng Yan, Han Fang, Yahui Zhou
In this paper, we investigate the underlying factors that potentially enhance the mathematical reasoning capabilities of large language models (LLMs).
1 code implementation • 30 Jun 2024 • Dazhou Yu, Yuntong Hu, Yun Li, Liang Zhao
Finally, we introduce Multipolygon-GNN, a novel model tailored to leverage the spatial and semantic heterogeneity inherent in the visibility graph.
1 code implementation • 30 Jun 2024 • Weihong Zhong, Xiaocheng Feng, Liang Zhao, Qiming Li, Lei Huang, Yuxuan Gu, Weitao Ma, Yuan Xu, Bing Qin
To mitigate this, we further propose a training-free method called Residual Visual Decoding, where we revise the output distribution of LVLMs with the one derived from the residual visual input, providing models with direct access to the visual information.
1 code implementation • 30 Jun 2024 • Dazhou Yu, Xiaoyun Gong, Yun Li, Meikang Qiu, Liang Zhao
Existing models in this area often fall short due to their domain-specific nature and lack a strategy for integrating information from various sources in the absence of ground truth labels.
1 code implementation • 21 Jun 2024 • Mengdan Zhu, Raasikh Kanjiani, Jiahui Lu, Andrew Choi, Qirui Ye, Liang Zhao
Deep generative models like VAEs and diffusion models have advanced various generation tasks by leveraging latent variables to learn data distributions and generate high-quality samples.
no code implementations • 18 Jun 2024 • Jixue Liu, Jiuyong Li, Stefan Peters, Liang Zhao
To show the advantages of the proposed model, the paper presents extensive results for various possible model architectures improving UNet and draws interesting conclusions including that adding more modules to a model does not always lead to a better performance.
no code implementations • 16 Jun 2024 • Shuwen Zheng, Zhou Fang, Liang Zhao
With BTMP, we further propose an uncertainty-guided active survey framework, which dynamically formulates survey questions representing travel mode choice scenarios with high prediction uncertainty.
1 code implementation • 14 Jun 2024 • Zhuofeng Li, Zixing Gou, Xiangnan Zhang, Zhongyuan Liu, Sirui Li, Yuntong Hu, Chen Ling, Zheng Zhang, Liang Zhao
To address this gap, we introduce Textual-Edge Graphs Datasets and Benchmark (TEG-DB), a comprehensive and diverse collection of benchmark textual-edge datasets featuring rich textual descriptions on nodes and edges.
1 code implementation • 3 Jun 2024 • Tianwen Wei, Bo Zhu, Liang Zhao, Cheng Cheng, Biye Li, Weiwei Lü, Peng Cheng, Jianhao Zhang, XiaoYu Zhang, Liang Zeng, Xiaokun Wang, Yutuan Ma, Rui Hu, Shuicheng Yan, Han Fang, Yahui Zhou
In this technical report, we introduce the training methodologies implemented in the development of Skywork-MoE, a high-performance mixture-of-experts (MoE) large language model (LLM) with 146 billion parameters and 16 experts.
no code implementations • 2 Jun 2024 • Liang Zhao, Tianwen Wei, Liang Zeng, Cheng Cheng, Liu Yang, Peng Cheng, Lijie Wang, Chenxia Li, Xuejie Wu, Bo Zhu, Yimeng Gan, Rui Hu, Shuicheng Yan, Han Fang, Yahui Zhou
We introduce LongSkywork, a long-context Large Language Model (LLM) capable of processing up to 200, 000 tokens.
no code implementations • 27 May 2024 • Zheng Zhang, Yuntong Hu, Bo Pan, Chen Ling, Liang Zhao
Text-Attributed Graphs (TAGs) enhance graph structures with natural language descriptions, enabling detailed representation of data and their relationships across a broad spectrum of real-world scenarios.
no code implementations • 26 May 2024 • Lei Zhang, Zhiqian Chen, Chang-Tien Lu, Liang Zhao
Network interdiction problems are combinatorial optimization problems involving two players: one aims to solve an optimization problem on a network, while the other seeks to modify the network to thwart the first player's objectives.
no code implementations • 26 May 2024 • Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, Liang Zhao
Naive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation graphs, social media, and knowledge graphs.
no code implementations • 25 May 2024 • Qilong Zhao, Shiyu Wang, Guangji Bai, Bo Pan, Zhaohui Qin, Liang Zhao
This is due to the long-lasting challenge of jointly identifying key latent variables, their causal relations, and their correlation with properties of interest, as well as how to leverage their discoveries toward causally controlled data generation.
1 code implementation • 25 May 2024 • Zekun Cai, Guangji Bai, Renhe Jiang, Xuan Song, Liang Zhao
Temporal Domain Generalization (TDG) addresses the challenge of training predictive models under temporally varying data distributions.
1 code implementation • 23 May 2024 • Chenglong Liu, Haoran Wei, Jinyue Chen, Lingyu Kong, Zheng Ge, Zining Zhu, Liang Zhao, Jianjian Sun, Chunrui Han, Xiangyu Zhang
Modern LVLMs still struggle to achieve fine-grained document understanding, such as OCR/translation/caption for regions of interest to the user, tasks that require the context of the entire page, or even multiple pages.
no code implementations • 19 May 2024 • Hongning Ruan, Yulin Shao, Qianqian Yang, Liang Zhao, Dusit Niyato
By feeding the coordinates of these voxels into the respective networks, we reconstruct the geometry and attribute components of the original point cloud.
4 code implementations • 7 May 2024 • DeepSeek-AI, Aixin Liu, Bei Feng, Bin Wang, Bingxuan Wang, Bo Liu, Chenggang Zhao, Chengqi Dengr, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Hanwei Xu, Hao Yang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J. L. Cai, Jian Liang, JianZhong Guo, Jiaqi Ni, Jiashi Li, Jin Chen, Jingyang Yuan, Junjie Qiu, Junxiao Song, Kai Dong, Kaige Gao, Kang Guan, Lean Wang, Lecong Zhang, Lei Xu, Leyi Xia, Liang Zhao, Liyue Zhang, Meng Li, Miaojun Wang, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Mingming Li, Ning Tian, Panpan Huang, Peiyi Wang, Peng Zhang, Qihao Zhu, Qinyu Chen, Qiushi Du, R. J. Chen, R. L. Jin, Ruiqi Ge, Ruizhe Pan, Runxin Xu, Ruyi Chen, S. S. Li, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shaoqing Wu, Shengfeng Ye, Shirong Ma, Shiyu Wang, Shuang Zhou, Shuiping Yu, Shunfeng Zhou, Size Zheng, T. Wang, Tian Pei, Tian Yuan, Tianyu Sun, W. L. Xiao, Wangding Zeng, Wei An, Wen Liu, Wenfeng Liang, Wenjun Gao, Wentao Zhang, X. Q. Li, Xiangyue Jin, Xianzu Wang, Xiao Bi, Xiaodong Liu, Xiaohan Wang, Xiaojin Shen, Xiaokang Chen, Xiaosha Chen, Xiaotao Nie, Xiaowen Sun, Xiaoxiang Wang, Xin Liu, Xin Xie, Xingkai Yu, Xinnan Song, Xinyi Zhou, Xinyu Yang, Xuan Lu, Xuecheng Su, Y. Wu, Y. K. Li, Y. X. Wei, Y. X. Zhu, Yanhong Xu, Yanping Huang, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Li, Yaohui Wang, Yi Zheng, Yichao Zhang, Yiliang Xiong, Yilong Zhao, Ying He, Ying Tang, Yishi Piao, Yixin Dong, Yixuan Tan, Yiyuan Liu, Yongji Wang, Yongqiang Guo, Yuchen Zhu, Yuduan Wang, Yuheng Zou, Yukun Zha, Yunxian Ma, Yuting Yan, Yuxiang You, Yuxuan Liu, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhen Huang, Zhen Zhang, Zhenda Xie, Zhewen Hao, Zhihong Shao, Zhiniu Wen, Zhipeng Xu, Zhongyu Zhang, Zhuoshu Li, Zihan Wang, Zihui Gu, Zilin Li, Ziwei Xie
MLA guarantees efficient inference through significantly compressing the Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse computation.
1 code implementation • 6 May 2024 • Junxiang Wang, Liang Zhao
We introduce GraphSL, a new library for studying the graph source localization problem.
2 code implementations • 23 Apr 2024 • Xiongxiao Xu, Canyu Chen, Yueqing Liang, Baixiang Huang, Guangji Bai, Liang Zhao, Kai Shu
To meet the objectives, we propose a multi-scale hybrid Mamba-Transformer experts model State Space Transformer (SST).
1 code implementation • 16 Apr 2024 • Ke Zhu, Zheng Ge, Liang Zhao, Xiangyu Zhang
We generate chosen and rejected responses with regard to the original and augmented image pairs, and conduct preference alignment with direct preference optimization.
Ranked #103 on
Visual Question Answering
on MM-Vet
1 code implementation • 15 Apr 2024 • Jinyue Chen, Lingyu Kong, Haoran Wei, Chenglong Liu, Zheng Ge, Liang Zhao, Jianjian Sun, Chunrui Han, Xiangyu Zhang
To address this, we propose OneChart: a reliable agent specifically devised for the structural extraction of chart information.
no code implementations • 1 Apr 2024 • Zheng Zhang, Fan Yang, Ziyan Jiang, Zheng Chen, Zhengyang Zhao, Chengyuan Ma, Liang Zhao, Yang Liu
Recent advances in large language models (LLMs) have enhanced their ability to process long input contexts.
no code implementations • 16 Mar 2024 • Qilong Zhao, Yifei Zhang, Mengdan Zhu, Siyi Gu, Yuyang Gao, Xiaofeng Yang, Liang Zhao
Explanation supervision aims to enhance deep learning models by integrating additional signals to guide the generation of model explanations, showcasing notable improvements in both the predictability and explainability of the model.
2 code implementations • 28 Feb 2024 • Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao
The transformative impact of large language models (LLMs) like LLaMA and GPT on natural language processing is countered by their prohibitive computational demands.
1 code implementation • 24 Feb 2024 • Nguyen Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai
Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network.
no code implementations • 20 Feb 2024 • Yifei Zhang, Bo Pan, Chen Ling, Yuntong Hu, Liang Zhao
The deployment and application of Large Language Models (LLMs) is hindered by their memory inefficiency, computational demands, and the high costs of API inferences.
no code implementations • 19 Feb 2024 • Bo Pan, Zheng Zhang, Yifei Zhang, Yuntong Hu, Liang Zhao
To address the inherent gaps between LLMs (generative models for texts) and graph models (discriminative models for graphs), we propose first to let LLMs teach an interpreter with rich textual rationale and then let a student model mimic the interpreter's reasoning without LLMs' textual rationale.
no code implementations • 16 Feb 2024 • Mingchen Li, Chen Ling, Rui Zhang, Liang Zhao
To address this, in this work, we introduce a Condensed Transition Graph Framework for Zero-Shot Link Prediction (CTLP), which encodes all the paths' information in linear time complexity to predict unseen relations between entities, attaining both efficiency and information preservation.
1 code implementation • 15 Feb 2024 • Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen
Existing works have been devoted to quantifying the uncertainty in LLM's response, but they often overlook the complex nature of LLMs and the uniqueness of in-context learning.
1 code implementation • 6 Feb 2024 • Renato Tinós, Liang Zhao, Francisco Chicano, Darrell Whitley
Mutation operators, a partition crossover, and a local search strategy are proposed, all using information about the relationship between decision variables.
no code implementations • 2 Feb 2024 • Mengdan Zhu, Zhenke Liu, Bo Pan, Abhinav Angirekula, Liang Zhao
Learning interpretable representations of data generative latent factors is an important topic for the development of artificial intelligence.
no code implementations • 29 Jan 2024 • Nahyun Kwon, Tong Sun, Yuyang Gao, Liang Zhao, Xu Wang, Jeeeun Kim, Sungsoo Ray Hong
While troubleshooting plays an essential part of 3D printing, the process remains challenging for many remote novices even with the help of well-developed online sources, such as online troubleshooting archives and online community help.
no code implementations • 23 Jan 2024 • Haoran Wei, Lingyu Kong, Jinyue Chen, Liang Zhao, Zheng Ge, En Yu, Jianjian Sun, Chunrui Han, Xiangyu Zhang
In Vary-toy, we introduce an improved vision vocabulary, allowing the model to not only possess all features of Vary but also gather more generality.
Ranked #209 on
Visual Question Answering
on MM-Vet
no code implementations • 16 Jan 2024 • Jiayu Chang, Shiyu Wang, Chen Ling, Zhaohui Qin, Liang Zhao
The intricate relationship between genetic variation and human diseases has been a focal point of medical research, evidenced by the identification of risk genes regarding specific diseases.
1 code implementation • 1 Jan 2024 • Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Xinyuan Song, Carl Yang, Yue Cheng, Liang Zhao
We categorize methods based on their optimization focus: computational, memory, energy, financial, and network resources and their applicability across various stages of an LLM's lifecycle, including architecture design, pretraining, finetuning, and system design.
no code implementations • 28 Dec 2023 • Liang Zhao, Xiachong Feng, Xiaocheng Feng, Weihong Zhong, Dongliang Xu, Qing Yang, Hongtao Liu, Bing Qin, Ting Liu
Built upon the Transformer, large language models (LLMs) have captured worldwide attention due to their remarkable abilities.
no code implementations • 19 Dec 2023 • Junxiang Wang, Guangji Bai, Wei Cheng, Zhengzhang Chen, Liang Zhao, Haifeng Chen
In order to tackle these challenges simultaneously, in this paper, we introduce PrOmpt-based domaiN Discrimination (POND), the first framework to utilize prompts for time series domain adaptation.
1 code implementation • 17 Dec 2023 • Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao
Besides, existing spatial network representation learning methods can only consider networks embedded in Euclidean space, and can not well exploit the rich geometric information carried by irregular and non-uniform non-Euclidean space.
1 code implementation • 11 Dec 2023 • Haoran Wei, Lingyu Kong, Jinyue Chen, Liang Zhao, Zheng Ge, Jinrong Yang, Jianjian Sun, Chunrui Han, Xiangyu Zhang
Accordingly, we propose Vary, an efficient and effective method to scale up the vision vocabulary of LVLMs.
Ranked #144 on
Visual Question Answering
on MM-Vet
no code implementations • 30 Nov 2023 • En Yu, Liang Zhao, Yana Wei, Jinrong Yang, Dongming Wu, Lingyu Kong, Haoran Wei, Tiancai Wang, Zheng Ge, Xiangyu Zhang, Wenbing Tao
Then, FIT requires MLLMs to first predict trajectories of related objects and then reason about potential future events based on them.
Ranked #160 on
Visual Question Answering
on MM-Vet
1 code implementation • 30 Oct 2023 • Tianwen Wei, Liang Zhao, Lichang Zhang, Bo Zhu, Lijie Wang, Haihua Yang, Biye Li, Cheng Cheng, Weiwei Lü, Rui Hu, Chenxia Li, Liu Yang, Xilin Luo, Xuejie Wu, Lunan Liu, Wenjun Cheng, Peng Cheng, Jianhao Zhang, XiaoYu Zhang, Lei Lin, Xiaokun Wang, Yutuan Ma, Chuanhai Dong, Yanqi Sun, Yifu Chen, Yongyi Peng, Xiaojuan Liang, Shuicheng Yan, Han Fang, Yahui Zhou
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3. 2 trillion tokens drawn from both English and Chinese texts.
1 code implementation • 25 Oct 2023 • Liu Yang, Haihua Yang, Wenjun Cheng, Lei Lin, Chenxia Li, Yifu Chen, Lunan Liu, Jianfei Pan, Tianwen Wei, Biye Li, Liang Zhao, Lijie Wang, Bo Zhu, Guoliang Li, Xuejie Wu, Xilin Luo, Rui Hu
Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning.
no code implementations • 18 Oct 2023 • Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
In this work, we leverage pre-trained language models to iteratively retrieve reasoning paths on the external knowledge base, which does not require task-specific supervision.
no code implementations • 14 Oct 2023 • Liang Zhao, Xiongfei Wang, Zheming Jin
This paper presents an analytical approach to explore the damping effect of inner loops on grid-forming converters.
1 code implementation • 12 Oct 2023 • Yifei Zhang, Siyi Gu, Bo Pan, Guangji Bai, Meikang Qiu, Xiaofeng Yang, Liang Zhao
However, in many real-world situations, it is usually desired to prompt the model with visual attention without model retraining.
no code implementations • 12 Oct 2023 • Yifei Zhang, Siyi Gu, James Song, Bo Pan, Guangji Bai, Liang Zhao
Our proposed benchmarks facilitate a fair evaluation and comparison of visual explanation methods.
no code implementations • 11 Oct 2023 • Bo Pan, Zhenke Liu, Yifei Zhang, Liang Zhao
Explainable AI seeks to bring light to the decision-making processes of black-box models.
no code implementations • 11 Oct 2023 • Bo Pan, Muran Qin, Shiyu Wang, Yifei Zhang, Liang Zhao
To address these challenges, in this paper, we propose a general framework to enhance VAE-based data generators with property controllability and ensure disentanglement.
no code implementations • 7 Oct 2023 • Zheng Zhang, Chen Zheng, Da Tang, Ke Sun, Yukun Ma, Yingtong Bu, Xun Zhou, Liang Zhao
This paper introduces a multifaceted methodology for fine-tuning and evaluating large language models (LLMs) for specialized monetization tasks.
no code implementations • 7 Oct 2023 • Zheng Zhang, Liang Zhao
Deep learning has shown remarkable success in the field of clustering recently.
no code implementations • 7 Oct 2023 • Zheng Zhang, Hossein Amiri, Zhenke Liu, Andreas Züfle, Liang Zhao
Identifying anomalous human spatial trajectory patterns can indicate dynamic changes in mobility behavior with applications in domains like infectious disease monitoring and elderly care.
no code implementations • 7 Oct 2023 • Yuntong Hu, Zheng Zhang, Liang Zhao
Large language models (LLMs) have achieved impressive performance on many natural language processing tasks.
1 code implementation • 6 Oct 2023 • Guangji Bai, Qilong Zhao, Xiaoyang Jiang, Yifei Zhang, Liang Zhao
Continual Learning is a burgeoning domain in next-generation AI, focusing on training neural networks over a sequence of tasks akin to human learning.
no code implementations • 3 Oct 2023 • Xiangru Li, Yifei Zhang, Liang Zhao
The Segment Anything Model (SAM) is a powerful foundation model that introduced revolutionary advancements in natural image segmentation.
1 code implementation • 20 Sep 2023 • Runpei Dong, Chunrui Han, Yuang Peng, Zekun Qi, Zheng Ge, Jinrong Yang, Liang Zhao, Jianjian Sun, HongYu Zhou, Haoran Wei, Xiangwen Kong, Xiangyu Zhang, Kaisheng Ma, Li Yi
This paper presents DreamLLM, a learning framework that first achieves versatile Multimodal Large Language Models (MLLMs) empowered with frequently overlooked synergy between multimodal comprehension and creation.
Ranked #5 on
Visual Question Answering
on MMBench
no code implementations • 7 Sep 2023 • Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
Open Information Extraction (OIE) task aims at extracting structured facts from unstructured text, typically in the form of (subject, relation, object) triples.
Ranked #6 on
Open Information Extraction
on OIE2016
no code implementations • 6 Sep 2023 • Junruo Gao, Chen Ling, Carl Yang, Liang Zhao
Online health communities (OHCs) are forums where patients with similar conditions communicate their experiences and provide moral support.
no code implementations • 30 Aug 2023 • Yangkun Chen, Joseph Suarez, Junjie Zhang, Chenghui Yu, Bo Wu, HanMo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions.
no code implementations • 30 Aug 2023 • Muhammad Hamza, Ammar Hawbani, Sami Ul Rehman, Xingfu Wang, Liang Zhao
In particular, we propose a Residual Feature Attention Block (RFAB), containing the channel attention, pixel attention, and residual learning mechanism with long and short skip connections.
no code implementations • 25 Aug 2023 • Guangji Bai, Ziyang Yu, Zheng Chai, Yue Cheng, Liang Zhao
It utilizes an offline memory to cache historical information (e. g., node embedding) as an affordable approximation of the exact value and achieves high concurrency.
1 code implementation • IEEE Transactions on Geoscience and Remote Sensing 2023 • Chuangji Meng, Jinghuai Gao, Yajun Tian, Liang Zhao, Haoqi Zhao, Zhiqiang Wang.
The Gaussianization submodule with learnable parameters maps seismic data with the noise of unknown distribution to the one corrupted by Gaussian noise.
no code implementations • 18 Jul 2023 • Liang Zhao, En Yu, Zheng Ge, Jinrong Yang, Haoran Wei, HongYu Zhou, Jianjian Sun, Yuang Peng, Runpei Dong, Chunrui Han, Xiangyu Zhang
Based on precise referring instruction, we propose ChatSpot, a unified end-to-end multimodal large language model that supports diverse forms of interactivity including mouse clicks, drag-and-drop, and drawing boxes, which provides a more flexible and seamless interactive experience.
1 code implementation • 8 Jul 2023 • Tong Steven Sun, Yuyang Gao, Shubham Khaladkar, Sijia Liu, Liang Zhao, Young-Ho Kim, Sungsoo Ray Hong
To mitigate the gap, we designed DeepFuse, the first interactive design that realizes the direct feedback loop between a user and CNNs in diagnosing and revising CNN's vulnerability using local explanations.
no code implementations • 28 Jun 2023 • Yiwen Shi, Ping Ren, Jing Wang, Biao Han, Taha ValizadehAslani, Felix Agbavor, Yi Zhang, Meng Hu, Liang Zhao, Hualou Liang
Specifically, we propose a three-turn iterative prompting approach to food effect summarization in which the keyword-focused and length-controlled prompts are respectively provided in consecutive turns to refine the quality of the generated summary.
no code implementations • 7 Jun 2023 • Hejie Cui, Jiaying Lu, ran Xu, Shiyu Wang, Wenjing Ma, Yue Yu, Shaojun Yu, Xuan Kan, Chen Ling, Liang Zhao, Zhaohui S. Qin, Joyce C. Ho, Tianfan Fu, Jing Ma, Mengdi Huai, Fei Wang, Carl Yang
This comprehensive review aims to provide an overview of the current state of Healthcare Knowledge Graphs (HKGs), including their construction, utilization models, and applications across various healthcare and biomedical research domains.
no code implementations • 6 Jun 2023 • Jiang Liu, Hao Fei, Fei Li, Jingye Li, Bobo Li, Liang Zhao, Chong Teng, Donghong Ji
Few-shot named entity recognition (NER) exploits limited annotated instances to identify named mentions.
1 code implementation • 3 Jun 2023 • Han Yi Chiu, Liang Zhao, Anqi Wu
However, traditional approaches for integrating FC and SC overlook the dynamical variations, which stand a great chance to over-generalize the brain neural network.
no code implementations • 30 May 2023 • Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Dhagash Mehta, Stefano Pasquali, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Jian Pei, Carl Yang, Liang Zhao
In this article, we present a comprehensive survey on domain specification techniques for large language models, an emerging direction critical for large language model applications.
no code implementations • 30 May 2023 • Yun Li, Dazhou Yu, Zhenke Liu, Minxing Zhang, Xiaoyun Gong, Liang Zhao
Graph neural networks (GNNs) have emerged as a powerful tool for modeling and understanding data with dependencies to each other such as spatial and temporal dependencies.
no code implementations • 19 May 2023 • Shiyu Wang, Guangji Bai, Qingyang Zhu, Zhaohui Qin, Liang Zhao
As a result, domain generalization graph transformation that predicts graphs not available in the training data is under-explored, with multiple key challenges to be addressed including (1) the extreme space complexity when training on all input-output mode combinations, (2) difference of graph topologies between the input and the output modes, and (3) how to generalize the model to (unseen) target domains that are not in the training data.
1 code implementation • 1 May 2023 • Chen Ling, Junji Jiang, Junxiang Wang, My Thai, Lukas Xue, James Song, Meikang Qiu, Liang Zhao
Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users.
no code implementations • 27 Apr 2023 • Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu
A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed.
1 code implementation • 25 Mar 2023 • Xiaoxiao He, Chaowei Tan, Bo Liu, Liping Si, Weiwu Yao, Liang Zhao, Di Liu, Qilong Zhangli, Qi Chang, Kang Li, Dimitris N. Metaxas
The supervised learning of the proposed method extracts features from limited labeled data in each client, while the unsupervised data is used to distill both feature and response-based knowledge from a national data repository to further improve the accuracy of the collaborative model and reduce the communication cost.
no code implementations • 4 Feb 2023 • Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao
Knowledge-enhanced neural machine reasoning h