no code implementations • ICML 2020 • Shuang Li, Lu Wang, Ruizhi Zhang, xiaofu Chang, Xuqin Liu, Yao Xie, Yuan Qi, Le Song
We propose a modeling framework for event data, which excels in small data regime with the ability to incorporate domain knowledge.
no code implementations • EMNLP 2020 • Liqiang Xiao, Lu Wang, Hao He, Yaohui Jin
Previous work is mostly based on statistical methods that estimate word-level salience, which does not consider semantics and larger context when quantifying importance.
no code implementations • 4 Nov 2024 • Yudi Zhang, Pei Xiao, Lu Wang, Chaoyun Zhang, Meng Fang, Yali Du, Yevgeniy Puzyrev, Randolph Yao, Si Qin, QIngwei Lin, Mykola Pechenizkiy, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
In-context learning (ICL) and Retrieval-Augmented Generation (RAG) have gained attention for their ability to enhance LLMs' reasoning by incorporating external knowledge but suffer from limited contextual window size, leading to insufficient information injection.
no code implementations • 1 Nov 2024 • Chenghua Huang, Zhizhen Fan, Lu Wang, Fangkai Yang, Pu Zhao, Zeqi Lin, QIngwei Lin, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
Reinforcement Learning from Human Feedback (RLHF) is a crucial technique for aligning language models with human preferences, playing a pivotal role in the success of conversational models like GPT-4, ChatGPT, and Llama 2.
no code implementations • 29 Oct 2024 • Farima Fatahi Bayat, Lechen Zhang, Sheza Munir, Lu Wang
These prompts form FactBench, a dataset of 1K prompts across 150 fine-grained topics.
no code implementations • 27 Oct 2024 • Lu Wang, Hongchan Chen, Bing Wang, Qian Li, Qun Luo, Yuexing Han
This framework integrates both elemental composition and microstructural features to accurately predict the Vickers hardness of solid-solution Mg-Gd alloys.
no code implementations • 16 Oct 2024 • Mengze Hong, Yuanfeng Song, Di Jiang, Lu Wang, Zichang Guo, Chen Jason Zhang
To accommodate potential variations in how a customer's query may be expressed, it emerges as the favored solution to augment these QA pairs with similar questions that are possibly diverse while remaining semantic consistency.
1 code implementation • 10 Oct 2024 • Inderjeet Nair, Jiaye Tan, Xiaotian Su, Anne Gere, Xu Wang, Lu Wang
However, it remains unclear whether the feedback generated by these models is truly effective in enhancing the quality of student revisions.
no code implementations • 7 Oct 2024 • Xinliang Frederick Zhang, Nick Beauchamp, Lu Wang
In this work, we first study an essential task of temporal reasoning -- temporal graph generation, to unveil LLMs' inherent, global reasoning capabilities.
1 code implementation • 28 Sep 2024 • Dongyue Li, Ziniu Zhang, Lu Wang, Hongyang R. Zhang
We study the problem of fine-tuning a language model (LM) for a target task by optimally using the information from $n$ auxiliary tasks.
no code implementations • 25 Sep 2024 • Junting Lu, Zhiyang Zhang, Fangkai Yang, Jue Zhang, Lu Wang, Chao Du, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
This framework also facilitates the creation and expansion of APIs through automated exploration of applications.
no code implementations • 12 Sep 2024 • Lu Wang, Tianyuan Zhang, Yikai Han, Muyang Fang, Ting Jin, Jiaqi Kang
We conduct large-scale experiments on the full-stack autonomous driving model and demonstrate that our attack method outperforms previous attack methods.
no code implementations • 11 Sep 2024 • Tianyuan Zhang, Lu Wang, Jiaqi Kang, Xinwei Zhang, Siyuan Liang, Yuwei Chen, Aishan Liu, Xianglong Liu
Recent advances in deep learning have markedly improved autonomous driving (AD) models, particularly end-to-end systems that integrate perception, prediction, and planning stages, achieving state-of-the-art performance.
no code implementations • 20 Aug 2024 • Howe Tissue, Venus Wang, Lu Wang
We find that the cross-entropy loss curves of neural language models empirically adhere to a scaling law with learning rate (LR) annealing over training steps: $$L(s) = L_0 + A\cdot S_1^{-\alpha} - C\cdot S_2,$$ where $L(s)$ is the validation loss at step $s$, $S_1$ is the area under the LR curve, $S_2$ is the LR annealing area, and $L_0$, $A$, $C$, $\alpha$ are constant parameters.
no code implementations • 19 Aug 2024 • Yuhong He, Long Peng, Qiaosi Yi, Chen Wu, Lu Wang
Image restoration endeavors to reconstruct a high-quality, detail-rich image from a degraded counterpart, which is a pivotal process in photography and various computer vision systems.
no code implementations • 5 Aug 2024 • Weide Liu, Xingxing Wang, Lu Wang, Jun Cheng, Fayao Liu, Xulei Yang
In this paper, we introduce a novel Gaussian mixture based evidential learning solution for robust stereo matching.
no code implementations • 31 Jul 2024 • Ziya Zhou, Yuhang Wu, Zhiyue Wu, Xinyue Zhang, Ruibin Yuan, Yinghao Ma, Lu Wang, Emmanouil Benetos, Wei Xue, Yike Guo
Yet scant research explores the details of how these LLMs perform on advanced music understanding and conditioned generation, especially from the multi-step reasoning perspective, which is a critical aspect in the conditioned, editable, and interactive human-computer co-creation process.
no code implementations • 10 Jul 2024 • Ruolin Li, Lu Wang, Tingting Yang, Lisheng Xu, Bingyang Ma, Yongchun Li, Hongchao Wei
To enable the model to more effectively separate features, we utilize the extracted motion features and the texture features from the onset frame to reconstruct the apex frame.
no code implementations • 27 Jun 2024 • Jia Fu, Xiaoting Qin, Fangkai Yang, Lu Wang, Jue Zhang, QIngwei Lin, Yubo Chen, Dongmei Zhang, Saravan Rajmohan, Qi Zhang
Recent advancements in Large Language Models have transformed ML/AI development, necessitating a reevaluation of AutoML principles for the Retrieval-Augmented Generation (RAG) systems.
no code implementations • 19 Jun 2024 • Kaikai An, Fangkai Yang, Liqun Li, Junting Lu, Sitao Cheng, Shuzheng Si, Lu Wang, Pu Zhao, Lele Cao, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang, Baobao Chang
Recent advances in retrieval-augmented generation have significantly improved the performance of question-answering systems, particularly on factoid '5Ws' questions.
no code implementations • 19 Jun 2024 • Xin Liu, Farima Fatahi Bayat, Lu Wang
Built on top of ActCab, we further propose CoDec, a confidence-guided decoding strategy to elicit truthful answers with high confidence from LMs.
no code implementations • 10 Jun 2024 • Shuyang Cao, Lu Wang
Verifiable generation requires large language models (LLMs) to cite source documents supporting their outputs, thereby improve output transparency and trustworthiness.
no code implementations • 3 Jun 2024 • Tianyuan Zhang, Lu Wang, Hainan Li, Yisong Xiao, Siyuan Liang, Aishan Liu, Xianglong Liu, DaCheng Tao
For the first time, this paper studies the potential threats caused by these environmental illusions to LD and establishes the first comprehensive benchmark LanEvil for evaluating the robustness of LD against this natural corruption.
no code implementations • 29 May 2024 • Gaoxiang Zhao, Lu Wang, Xiaoqiang Wang
The effectiveness of anomaly signal detection can be significantly undermined by the inherent uncertainty of relying on one specified model.
1 code implementation • 26 May 2024 • Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, QIngwei Lin, Alois Knoll, Ming Jin
In numerous reinforcement learning (RL) problems involving safety-critical systems, a key challenge lies in balancing multiple objectives while simultaneously meeting all stringent safety constraints.
Multi-Objective Reinforcement Learning reinforcement-learning +1
no code implementations • 13 May 2024 • Mu-Huan Miles Chung, Sharon Li, Jaturong Kongmanee, Lu Wang, Yuhong Yang, Calvin Giang, Khilan Jerath, Abhay Raman, David Lie, Mark Chignell
We also recommend that the information gain maximizing sample method (based on expert confidence) should be used in early stages of Active Learning, providing that well-calibrated confidence can be obtained.
1 code implementation • 8 May 2024 • Inderjeet Nair, Lu Wang
We study the task of conducting structured reasoning as generating a reasoning graph from natural language input using large language models (LLMs).
no code implementations • 4 May 2024 • Xiang Chen, Lu Wang, Beibei Wang
Thanks to the regularity and repetitiveness of woven fabric patterns, our network can encode fabric patterns and parameters as a small latent vector, which is later interpreted by a small decoder, enabling the representation of different types of fabrics.
3 code implementations • 2 May 2024 • Shangding Gu, Bilgehan Sel, Yuhao Ding, Lu Wang, QIngwei Lin, Ming Jin, Alois Knoll
Ensuring the safety of Reinforcement Learning (RL) is crucial for its deployment in real-world applications.
1 code implementation • 1 May 2024 • Farima Fatahi Bayat, Xin Liu, H. V. Jagadish, Lu Wang
The adaptive nature of LITO counters the limitations of one-size-fits-all intervention methods, maximizing truthfulness by reflecting the model's internal knowledge only when it is confident.
no code implementations • 27 Apr 2024 • Dapeng Li, Hang Dong, Lu Wang, Bo Qiao, Si Qin, QIngwei Lin, Dongmei Zhang, Qi Zhang, Zhiwei Xu, Bin Zhang, Guoliang Fan
The entire framework has a message module and an action module.
Multi-agent Reinforcement Learning reinforcement-learning +1
1 code implementation • 26 Apr 2024 • Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, Lu Wang
Self-correction has emerged as a promising solution to boost the reasoning performance of large language models (LLMs), where LLMs refine their solutions using self-generated critiques that pinpoint the errors.
1 code implementation • 1 Apr 2024 • Muhammad Khalifa, David Wadden, Emma Strubell, Honglak Lee, Lu Wang, Iz Beltagy, Hao Peng
We investigate the problem of intrinsic source citation, where LLMs are required to cite the pretraining source supporting a generated response.
no code implementations • 22 Mar 2024 • Minghui Qiu, Yandao Huang, Lin Chen, Lu Wang, Kaishun Wu
In recent years, emerging research on mobile sensing has led to novel scenarios that enhance daily life for humans, but dynamic usage conditions often result in performance degradation when systems are deployed in real-world settings.
1 code implementation • 20 Mar 2024 • Xincheng Yao, Ruoqi Li, Zefeng Qian, Lu Wang, Chongyang Zhang
In this paper, we propose a novel Hierarchical Gaussian mixture normalizing flow modeling method for accomplishing unified Anomaly Detection, which we call HGAD.
no code implementations • 27 Feb 2024 • Kaikai An, Fangkai Yang, Junting Lu, Liqun Li, Zhixing Ren, Hao Huang, Lu Wang, Pu Zhao, Yu Kang, Hua Ding, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
Effective incident management is pivotal for the smooth operation of enterprises-level cloud services.
1 code implementation • 7 Feb 2024 • Yuhong He, Aiwen Jiang, Lingfang Jiang, Zhifeng Wang, Lu Wang
Transformers have recently emerged as a significant force in the field of image deraining.
no code implementations • 3 Feb 2024 • Lu Wang, Li Chang, Ruipeng Zhang, Kexun Li, Yu Wang, Wei Chen, Xuanlin Feng, Mingwei Sun, Qi Wang, Charles Damien Lu, Jun Zeng, Hua Jiang
Excessive energy intake increased mortality rapidly in the early period of the acute phase.
no code implementations • 13 Jan 2024 • Lu Wang, Mayukh Das, Fangkai Yang, Chao Duo, Bo Qiao, Hang Dong, Si Qin, Chetan Bansal, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
We address the challenge of learning safe and robust decision policies in presence of uncertainty in context of the real scientific problem of adaptive resource oversubscription to enhance resource efficiency while ensuring safety against resource congestion risk.
no code implementations • 13 Jan 2024 • Lu Wang, Chao Du, Pu Zhao, Chuan Luo, Zhangchi Zhu, Bo Qiao, Wei zhang, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang, Qi Zhang
To correct the negative sampling bias, we propose a novel contrastive learning method named Positive-Unlabeled Contrastive Learning (PUCL).
no code implementations • 20 Dec 2023 • Zhiguang Yang, Lu Wang, Chun Gan, Liufang Sang, Haoran Wang, Wenlong Chen, Jie He, Changping Peng, Zhangang Lin, Jingping Shao
In this paper, we propose for the first time a novel architecture for online parallel estimation of ads and creatives ranking, as well as the corresponding offline joint optimization model.
1 code implementation • 29 Nov 2023 • Bo Qiao, Liqun Li, Xu Zhang, Shilin He, Yu Kang, Chaoyun Zhang, Fangkai Yang, Hang Dong, Jue Zhang, Lu Wang, Minghua Ma, Pu Zhao, Si Qin, Xiaoting Qin, Chao Du, Yong Xu, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang
TaskWeaver provides support for rich data structures, flexible plugin usage, and dynamic plugin selection, and leverages LLM coding capabilities for complex logic.
1 code implementation • 16 Nov 2023 • Xinliang Frederick Zhang, Winston Wu, Nick Beauchamp, Lu Wang
News media often strive to minimize explicit moral language in news articles, yet most articles are dense with moral values as expressed through the reported events themselves.
1 code implementation • 16 Nov 2023 • Joseph J. Peper, Wenzhao Qiu, Lu Wang
We investigate pre-training techniques for abstractive multi-document summarization (MDS), which is much less studied than summarizing single documents.
1 code implementation • 7 Nov 2023 • Ruomeng Ding, Chaoyun Zhang, Lu Wang, Yong Xu, Minghua Ma, Wei zhang, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
To address these limitations, we introduce a novel thought prompting approach called "Everything of Thoughts" (XoT) to defy the law of "Penrose triangle of existing thought paradigms.
1 code implementation • 30 Oct 2023 • Xin Liu, Muhammad Khalifa, Lu Wang
For evaluation, we construct CaT, a benchmark consisting of eight text generation tasks, covering responses ranging from short phrases to paragraphs.
1 code implementation • 28 Oct 2023 • Kaijian Zou, Xinliang Frederick Zhang, Winston Wu, Nick Beauchamp, Lu Wang
We benchmark PAC to highlight the challenges of this task.
no code implementations • 28 Oct 2023 • Yujian Liu, Xinliang Frederick Zhang, Kaijian Zou, Ruihong Huang, Nick Beauchamp, Lu Wang
Public opinion is shaped by the information news media provide, and that information in turn may be shaped by the ideological preferences of media outlets.
no code implementations • 24 Oct 2023 • Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, QIngwei Lin, Kam-Fai Wong
Currently, there are two main approaches to address jailbreak attacks: safety training and safeguards.
1 code implementation • 22 Oct 2023 • Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
Open-domain question answering (QA) systems are often built with retrieval modules.
no code implementations • 2 Oct 2023 • Lu Wang, Wenjie Liu
In this paper, a quantum segmentation algorithm based on local adaptive threshold for NEQR image is proposed, which can use quantum mechanism to simultaneously compute local thresholds for all pixels in a gray-scale image and quickly segment the image into a binary image.
no code implementations • 2 Oct 2023 • Wenjie Liu, Lu Wang, Mengmeng Cui
The classical image segmentation algorithm based on grayscale morphology can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem will emerge.
no code implementations • 1 Oct 2023 • Wenjie Liu, Lu Wang
However, the existing QSED algorithms only consider two- or four-direction Sobel operator, which leads to a certain loss of edge detail information in some high-definition images.
no code implementations • 1 Oct 2023 • Wenjie Liu, Lu Wang, Qingshan Wu
For a quantum video with $2^m$ frames (every frame is a $2^n\times 2^n$ image with $q$ grayscale levels), the complexity of our algorithm can be reduced to O$(n^2 + q)$.
no code implementations • 30 Sep 2023 • Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
After the model is learned, we can obtain causal relations among states and action variables behind its decisions, exposing policies learned by it.
no code implementations • 19 Sep 2023 • Esha Uboweja, David Tian, Qifei Wang, Yi-Chun Kuo, Joe Zou, Lu Wang, George Sung, Matthias Grundmann
Our framework provides a pre-trained single-hand embedding model that can be fine-tuned for custom gesture recognition.
1 code implementation • 9 Sep 2023 • Yuhong He, Long Peng, Lu Wang, Jun Cheng
Since rain streaks show a variety of shapes and directions, learning the degradation representation is extremely challenging for single image deraining.
1 code implementation • 17 Aug 2023 • Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
The standard approach for ICL is to prompt the LM with concatenated demonstrations followed by the test input.
no code implementations • 11 Aug 2023 • Chao Yang, Lu Wang, Kun Gao, Shuang Li
Leveraging the temporal point process modeling and learning framework, the rule content and weights will be gradually optimized until the likelihood of the observational event sequences is optimal.
no code implementations • 3 Aug 2023 • Fangkai Yang, Wenjie Yin, Lu Wang, Tianci Li, Pu Zhao, Bo Liu, Paul Wang, Bo Qiao, Yudong Liu, Mårten Björkman, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
However, they suffer from poor data quality like data missing in model training and prediction, which limits the performance.
1 code implementation • 1 Aug 2023 • Zhangchi Zhu, Lu Wang, Pu Zhao, Chao Du, Wei zhang, Hang Dong, Bo Qiao, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang
To mitigate the impact of label uncertainty and improve the robustness of learning with positive and unlabeled data, we propose a new robust PU learning method with a training strategy motivated by the nature of human learning: easy cases should be learned first.
no code implementations • 1 Jul 2023 • Shuzhe Chen, Li Li, Zhichao Lin, Ke Zhang, Ying Gong, Lu Wang, Xu Wu, Maokun Li, Yuanlin Song, Fan Yang, Shenheng Xu
A simple convolutional neural network is used for classification.
no code implementations • 25 Jun 2023 • Yiman Zhu, Lu Wang, Jingyi Yuan, Yu Guo
To evenly sample poses of different orientation and distance without collision, a collision-free working space and pose stratified sampling is proposed.
1 code implementation • 13 Jun 2023 • Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
Imitation learning has achieved great success in many sequential decision-making tasks, in which a neural agent is learned by imitating collected human demonstrations.
1 code implementation • 24 May 2023 • Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
To address this issue, we propose Guiding chain-of-thought ReAsoning with a CorrectnEss Discriminator (GRACE), a stepwise decoding approach that steers the decoding process towards producing correct reasoning steps.
1 code implementation • 24 May 2023 • Naihao Deng, Xinliang Frederick Zhang, Siyang Liu, Winston Wu, Lu Wang, Rada Mihalcea
Annotator disagreement is ubiquitous in natural language processing (NLP) tasks.
1 code implementation • 24 May 2023 • Qi Zeng, Mankeerat Sidhu, Ansel Blume, Hou Pong Chan, Lu Wang, Heng Ji
To address this gap, we propose the task of scientific opinion summarization, where research paper reviews are synthesized into meta-reviews.
no code implementations • 24 May 2023 • Shuyang Cao, Lu Wang
Long document summarization systems are critical for domains with lengthy and jargonladen text, yet they present significant challenges to researchers and developers with limited computing resources.
1 code implementation • 19 May 2023 • Fangkai Yang, Pu Zhao, Zezhong Wang, Lu Wang, Jue Zhang, Mohit Garg, QIngwei Lin, Saravan Rajmohan, Dongmei Zhang
Large Language Model (LLM) has gained popularity and achieved remarkable results in open-domain tasks, but its performance in real industrial domain-specific scenarios is average due to its lack of specific domain knowledge.
no code implementations • 19 May 2023 • Liting Chen, Lu Wang, Hang Dong, Yali Du, Jie Yan, Fangkai Yang, Shuang Li, Pu Zhao, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks.
2 code implementations • 19 May 2023 • Xin Liu, Muhammad Khalifa, Lu Wang
Energy-based models (EBMs) have gained popularity for controlled text generation due to their high applicability to a wide range of constraints.
no code implementations • 11 Apr 2023 • Tianyuan Zhang, Yisong Xiao, Xiaoya Zhang, Hao Li, Lu Wang
Thus, virtual simulation experiments can provide a solution to this challenge.
no code implementations • 1 Mar 2023 • Mu-Huan Chung, Lu Wang, Sharon Li, Yuhong Yang, Calvin Giang, Khilan Jerath, Abhay Raman, David Lie, Mark Chignell
In this paper we present research results concerning the application of Active Learning to anomaly detection in redacted emails, comparing the utility of different methods for implementing active learning in this context.
1 code implementation • NeurIPS 2023 • Liting Chen, Jie Yan, Zhengdao Shao, Lu Wang, QIngwei Lin, Saravan Rajmohan, Thomas Moscibroda, Dongmei Zhang
In this paper, we propose Conservative State Value Estimation (CSVE), a new approach that learns conservative V-function via directly imposing penalty on OOD states.
no code implementations • 11 Dec 2022 • Lu Wang, Bofu Tang, Feifei Liu, Zhenyu Jiang, Xianmei Meng
Objective: To systematically evaluate the value of endocytoscopy (ECS) in the diagnosis of early esophageal cancer (EC).
no code implementations • 21 Nov 2022 • Junjie Sheng, Lu Wang, Fangkai Yang, Bo Qiao, Hang Dong, Xiangfeng Wang, Bo Jin, Jun Wang, Si Qin, Saravan Rajmohan, QIngwei Lin, Dongmei Zhang
To address these two limitations, this paper formulates the oversubscription for cloud as a chance-constrained optimization problem and propose an effective Chance Constrained Multi-Agent Reinforcement Learning (C2MARL) method to solve this problem.
Multi-agent Reinforcement Learning reinforcement-learning +2
1 code implementation • 14 Nov 2022 • Joseph J. Peper, Lu Wang
Generative models have demonstrated impressive results on Aspect-based Sentiment Analysis (ABSA) tasks, particularly for the emerging task of extracting Aspect-Category-Opinion-Sentiment (ACOS) quadruples.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2
no code implementations • 4 Nov 2022 • Changyuan Qiu, Winston Wu, Xinliang Frederick Zhang, Lu Wang
In this work, we introduce the task of multimodal ideology prediction, where a model predicts binary or five-point scale ideological leanings, given a text-image pair with political content.
no code implementations • 3 Nov 2022 • Shuyang Cao, Lu Wang
Despite having less performance drop when testing on data drawn from a later time, linear prompts focus more on non-temporal information and are less sensitive to the given timestamps, according to human evaluations and sensitivity analyses.
1 code implementation • 2 Nov 2022 • Xinliang Frederick Zhang, Nick Beauchamp, Lu Wang
We present a novel generative framework to allow the generation of canonical names for entities as well as stances among them.
no code implementations • 7 Oct 2022 • Lu Wang, Luis F. Abanto-Leon, Arash Asadi
Empowering cellular networks with augmented sensing capabilities is one of the key research areas in 6G communication systems.
no code implementations • 9 Sep 2022 • Yushu Chen, Guangwen Yang, Lu Wang, Qingzhong Gan, Haipeng Chen, Quanyong Xu
Atmospheric powered descent guidance can be solved by successive convexification; however, its onboard application is impeded by the sharp increase in computation caused by nonlinear aerodynamic forces.
no code implementations • 31 May 2022 • Marcel Robitaille, HeeBong Yang, Lu Wang, Na Young Kim
Time-fluctuating signals are ubiquitous and diverse in many physical, chemical, and biological systems, among which random telegraph signals (RTSs) refer to a series of instantaneous switching events between two discrete levels from single-particle movements.
2 code implementations • 25 May 2022 • Muhammad Khalifa, Lajanugen Logeswaran, Moontae Lee, Honglak Lee, Lu Wang
To alleviate the need for a large number of labeled question-document pairs for retriever training, we propose PromptRank, which relies on large language models prompting for multi-hop path reranking.
2 code implementations • Findings (NAACL) 2022 • Yujian Liu, Xinliang Frederick Zhang, David Wegsman, Nick Beauchamp, Lu Wang
Ideology is at the core of political science research.
1 code implementation • NAACL 2022 • Xu Wang, Simin Fan, Jessica Houghton, Lu Wang
NLP-powered automatic question generation (QG) techniques carry great pedagogical potential of saving educators' time and benefiting student learning.
no code implementations • 7 Apr 2022 • Nick J. C. Wang, Lu Wang, Yandan Sun, Haimei Kang, Dejun Zhang
We revisit ideas presented by Lugosch et al. using speech pre-training and three-module modeling; however, to ease construction of the end-to-end SLU model, we use as our phoneme module an open-source acoustic-phonetic model from a DNN-HMM hybrid automatic speech recognition (ASR) system instead of training one from scratch.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • Findings (ACL) 2022 • Xinyu Hua, Lu Wang
Combined with transfer learning, substantial F1 score boost (5-25) can be further achieved during the early iterations of active learning across domains.
no code implementations • ACL 2022 • Shuyang Cao, Lu Wang
In this work, we present HIBRIDS, which injects Hierarchical Biases foR Incorporating Document Structure into the calculation of attention scores.
no code implementations • 9 Feb 2022 • Lu Wang, Jie Yang, Masoumeh Zareapoor, ZhongLong Zheng
Cross-modal hashing still has some challenges needed to address: (1) most existing CMH methods take graphs as input to model data distribution.
no code implementations • 24 Nov 2021 • Shiqi Liu, Lu Wang, Jie Lian, Ting Chen, Cong Liu, Xuchen Zhan, Jintao Lu, Jie Liu, Ting Wang, Dong Geng, Hongwei Duan, Yuze Tian
Relative radiometric normalization(RRN) of different satellite images of the same terrain is necessary for change detection, object classification/segmentation, and map-making tasks.
no code implementations • 21 Oct 2021 • Imanol Luengo, Maria Grammatikopoulou, Rahim Mohammadi, Chris Walsh, Chinedu Innocent Nwoye, Deepak Alapatt, Nicolas Padoy, Zhen-Liang Ni, Chen-Chen Fan, Gui-Bin Bian, Zeng-Guang Hou, Heonjin Ha, Jiacheng Wang, Haojie Wang, Dong Guo, Lu Wang, Guotai Wang, Mobarakol Islam, Bharat Giddwani, Ren Hongliang, Theodoros Pissas, Claudio Ravasio, Martin Huber, Jeremy Birch, Joan M. Nunez Do Rio, Lyndon Da Cruz, Christos Bergeles, Hongyu Chen, Fucang Jia, Nikhil KumarTomar, Debesh Jha, Michael A. Riegler, Pal Halvorsen, Sophia Bano, Uddhav Vaghela, Jianyuan Hong, Haili Ye, Feihong Huang, Da-Han Wang, Danail Stoyanov
In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set.
no code implementations • 1 Oct 2021 • Yan Xia, Linhui Jiang, Lu Wang, Xue Chen, Jianjie Ye, Tangyan Hou, Liqiang Wang, Yibo Zhang, Mengying Li, Zhen Li, Zhe Song, Yaping Jiang, Weiping Liu, Pengfei Li, Daniel Rosenfeld, John H. Seinfeld, Shaocai Yu
Our results show that the ORRS measurements, assisted by the machine-learning-based ensemble model developed here, can realize day-to-day supervision of on-road vehicle-specific emissions.
no code implementations • ICLR 2022 • Shuang Li, Mingquan Feng, Lu Wang, Abdelmajid Essofi, Yufeng Cao, Junchi Yan, Le Song
We propose a principled method to learn a set of human-readable logic rules to explain temporal point processes.
3 code implementations • EMNLP 2021 • Shuyang Cao, Lu Wang
We study generating abstractive summaries that are faithful and factually consistent with the given articles.
1 code implementation • 7 Aug 2021 • Hou Pong Chan, Lu Wang, Irwin King
We study controllable text summarization which allows users to gain control on a particular attribute (e. g., length limit) of the generated summaries.
1 code implementation • ACL 2021 • Shuyang Cao, Lu Wang
We first define a new question type ontology which differentiates the nuanced nature of questions better than widely used question words.
no code implementations • 24 Jun 2021 • Cheng Jie, Da Xu, Zigeng Wang, Lu Wang, Wei Shen
With the increasing scale of search engine marketing, designing an efficient bidding system is becoming paramount for the success of e-commerce companies.
no code implementations • 24 Jun 2021 • Shuang Li, Lu Wang, Xinyun Chen, Yixiang Fang, Yan Song
In this paper, we model the propagation of the COVID-19 as spatio-temporal point processes and propose a generative and intensity-free model to track the spread of the disease.
1 code implementation • CVPR 2021 • YuHan Shen, Lu Wang, Ehsan Elhamifar
We address the problem of unsupervised localization of key-steps and feature learning in instructional videos using both visual and language instructions.
61 code implementations • ICLR 2022 • Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen
We propose Low-Rank Adaptation, or LoRA, which freezes the pre-trained model weights and injects trainable rank decomposition matrices into each layer of the Transformer architecture, greatly reducing the number of trainable parameters for downstream tasks.
Ranked #2 on parameter-efficient fine-tuning on HellaSwag (using extra training data)
no code implementations • ACL 2021 • Xinyu Hua, Ashwin Sreevatsa, Lu Wang
To enrich the generation with diverse content, we further propose to use large pre-trained models to predict relevant concepts and to generate claims.
3 code implementations • 17 May 2021 • Lu Wang, xiaofu Chang, Shuang Li, Yunfei Chu, Hui Li, Wei zhang, Xiaofeng He, Le Song, Jingren Zhou, Hongxia Yang
Secondly, on top of the proposed graph transformer, we introduce a two-stream encoder that separately extracts representations from temporal neighborhoods associated with the two interaction nodes and then utilizes a co-attentional transformer to model inter-dependencies at a semantic level.
no code implementations • 25 Apr 2021 • Songmin Dai, Jide Li, Lu Wang, Congcong Zhu, Yifan Wu, Xiaoqiang Li
This paper first introduces a novel method to generate anomalous data by breaking up global structures while preserving local structures of normal data at multiple levels.
no code implementations • NAACL 2021 • Shuyang Cao, Lu Wang
Using attention head masking, we are able to reveal the relation between encoder-decoder attentions and content selection behaviors of summarization models.
1 code implementation • NAACL 2021 • Luyang Huang, Shuyang Cao, Nikolaus Parulian, Heng Ji, Lu Wang
The quadratic computational and memory complexities of large Transformers have limited their scalability for long document summarization.
no code implementations • NAACL 2021 • Shuyang Cao, Lu Wang
How to generate summaries of different styles without requiring corpora in the target styles, or training separate models?
no code implementations • 5 Mar 2021 • Lu Wang, Haoyan Jiang, Mark Chignell
In this paper, we developed a new ensemble machine learning Python package based on multi-task learning (MTL), referred to as the Med-Multi-Task Learning (MD-MTL) package and applied it in predicting disease scores of patients, and in carrying out risk factor analysis on multiple subgroups of patients simultaneously.
no code implementations • 29 Dec 2020 • Lu Wang, Dong Guo, Guotai Wang, Shaoting Zhang
In this paper, we propose an annotation-efficient learning framework for segmentation tasks that avoids annotations of training images, where we use an improved Cycle-Consistent Generative Adversarial Network (GAN) to learn from a set of unpaired medical images and auxiliary masks obtained either from a shape model or public datasets.
no code implementations • 25 Oct 2020 • Wen Sun, Shiyu Lei, Lu Wang, Zhiqiang Liu, Yan Zhang
Industrial Internet of Things (IoT) enables distributed intelligent services varying with the dynamic and realtime industrial devices to achieve Industry 4. 0 benefits.
no code implementations • EMNLP 2020 • Xinyu Hua, Lu Wang
In this work, we present a novel content-controlled text generation framework, PAIR, with planning and iterative refinement, which is built upon a large model, BART.
no code implementations • ACL 2020 • Xingshan Zeng, Jing Li, Lu Wang, Zhiming Mao, Kam-Fai Wong
Trending topics in social media content evolve over time, and it is therefore crucial to understand social media users and their interpersonal communications in a dynamic manner.
no code implementations • ACL 2020 • Prafulla Kumar Choubey, Aaron Lee, Ruihong Huang, Lu Wang
Understanding discourse structures of news articles is vital to effectively contextualize the occurrence of a news event.
Ranked #5 on Text Classification on NewsDiscourse
no code implementations • AKBC 2020 • Xinyu Hua, Lei LI, Lifeng Hua, Lu Wang
We therefore propose a novel model, XREF, that leverages attention mechanisms to (1) pinpoint relevant context within comments, and (2) detect supporting entities from the news article.
no code implementations • 24 Jun 2020 • Yong Chen, Lu Wang, Jiajia Hu, Mingbin Ye
Fall event detection, as one of the greatest risks to the elderly, has been a hot research issue in the solitary scene in recent years.
2 code implementations • NeurIPS 2020 • Lu Wang, Xuanqing Liu, Jin-Feng Yi, Yuan Jiang, Cho-Jui Hsieh
Metric learning is an important family of algorithms for classification and similarity search, but the robustness of learned metrics against small adversarial perturbations is less studied.
no code implementations • 1 Jun 2020 • Xiao-Lei Yin, Dong-Xue Liang, Lu Wang, Jing Qiu, Zhi-Yun Yang, Jun-Hui Xing, Jian-Zeng Dong, Zhao-Yuan Ma
With the help of this technology, doctors can significantly reduce exposure frequency and intensity of the X-ray during coronary angiography.
1 code implementation • 11 May 2020 • Lu Wang, huan zhang, Jin-Feng Yi, Cho-Jui Hsieh, Yuan Jiang
By constraining adversarial perturbations in a low-dimensional subspace via spanning an auxiliary unlabeled dataset, the spanning attack significantly improves the query efficiency of a wide variety of existing black-box attacks.
1 code implementation • ACL 2020 • Luyang Huang, Lingfei Wu, Lu Wang
Sequence-to-sequence models for abstractive summarization have been studied extensively, yet the generated summaries commonly suffer from fabricated content, and are often found to be near-extractive.
no code implementations • 26 Mar 2020 • Lu Wang, Dong-Xue Liang, Xiao-Lei Yin, Jing Qiu, Zhi-Yun Yang, Jun-Hui Xing, Jian-Zeng Dong, Zhao-Yuan Ma
The reconstruction of three-dimensional models of coronary arteries is of great significance for the localization, evaluation and diagnosis of stenosis and plaque in the arteries, as well as for the assisted navigation of interventional surgery.
no code implementations • 26 Mar 2020 • Lu Wang, Dong-Xue Liang, Xiao-Lei Yin, Jing Qiu, Zhi-Yun Yang, Jun-Hui Xing, Jian-Zeng Dong, Zhao-Yuan Ma
This article proposes a new video segmentation framework that can extract the clearest and most comprehensive coronary angiography images from a video sequence, thereby helping physicians to better observe the condition of blood vessels.
no code implementations • 23 Mar 2020 • Tobias Ross, Annika Reinke, Peter M. Full, Martin Wagner, Hannes Kenngott, Martin Apitz, Hellena Hempe, Diana Mindroc Filimon, Patrick Scholz, Thuy Nuong Tran, Pierangela Bruno, Pablo Arbeláez, Gui-Bin Bian, Sebastian Bodenstedt, Jon Lindström Bolmgren, Laura Bravo-Sánchez, Hua-Bin Chen, Cristina González, Dong Guo, Pål Halvorsen, Pheng-Ann Heng, Enes Hosgor, Zeng-Guang Hou, Fabian Isensee, Debesh Jha, Tingting Jiang, Yueming Jin, Kadir Kirtac, Sabrina Kletz, Stefan Leger, Zhixuan Li, Klaus H. Maier-Hein, Zhen-Liang Ni, Michael A. Riegler, Klaus Schoeffmann, Ruohua Shi, Stefanie Speidel, Michael Stenzel, Isabell Twick, Gutai Wang, Jiacheng Wang, Liansheng Wang, Lu Wang, Yu-Jie Zhang, Yan-Jie Zhou, Lei Zhu, Manuel Wiesenfarth, Annette Kopp-Schneider, Beat P. Müller-Stich, Lena Maier-Hein
The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data.
no code implementations • 14 Jan 2020 • Lu Wang, Jie Yang
Due to the superiority in similarity computation and database storage for large-scale multiple modalities data, cross-modal hashing methods have attracted extensive attention in similarity retrieval across the heterogeneous modalities.
no code implementations • 11 Nov 2019 • Lu Wang, Jie Yang
Large-scale cross-modal hashing similarity retrieval has attracted more and more attention in modern search applications such as search engines and autopilot, showing great superiority in computation and storage.
no code implementations • IJCNLP 2019 • Xingshan Zeng, Jing Li, Lu Wang, Kam-Fai Wong
The prevalent use of social media leads to a vast amount of online conversations being produced on a daily basis.
no code implementations • ICLR 2020 • Xinyun Chen, Lu Wang, Yizhe Hang, Heng Ge, Hongyuan Zha
We consider off-policy policy evaluation when the trajectory data are generated by multiple behavior policies.
no code implementations • 4 Oct 2019 • Lu Wang, Wenchao Yu, Wei Wang, Wei Cheng, Wei zhang, Hongyuan Zha, Xiaofeng He, Haifeng Chen
Graph representation learning, aiming to learn low-dimensional representations which capture the geometric dependencies between nodes in the original graph, has gained increasing popularity in a variety of graph analysis tasks, including node classification and link prediction.
1 code implementation • IJCNLP 2019 • Lisa Fan, Marshall White, Eva Sharma, Ruisi Su, Prafulla Kumar Choubey, Ruihong Huang, Lu Wang
The increasing prevalence of political bias in news media calls for greater public awareness of it, as well as robust methods for its detection.
no code implementations • IJCNLP 2019 • Eva Sharma, Luyang Huang, Zhe Hu, Lu Wang
Human judges further rate our system summaries as more informative and coherent than those by popular summarization models.
no code implementations • IJCNLP 2019 • Xinyu Hua, Lu Wang
Building effective text generation systems requires three critical components: content selection, text planning, and surface realization, and traditionally they are tackled as separate problems.
no code implementations • 29 Jul 2019 • Lu Wang, Dongxiao Zhu
Many real-world datasets are labeled with natural orders, i. e., ordinal labels.
1 code implementation • ACL 2019 • Hou Pong Chan, Wang Chen, Lu Wang, Irwin King
To address this problem, we propose a reinforcement learning (RL) approach for keyphrase generation, with an adaptive reward function that encourages a model to generate both sufficient and accurate keyphrases.
1 code implementation • 10 Jun 2019 • Lu Wang, Xuanqing Liu, Jin-Feng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh
Furthermore, we show that dual solutions for these QP problems could give us a valid lower bound of the adversarial perturbation that can be used for formal robustness verification, giving us a nice view of attack/verification for NN models.
no code implementations • ACL 2019 • Eva Sharma, Chen Li, Lu Wang
Most existing text summarization datasets are compiled from the news domain, where summaries have a flattened discourse structure.
1 code implementation • ACL 2019 • Xingshan Zeng, Jing Li, Lu Wang, Kam-Fai Wong
We hypothesize that both the context of the ongoing conversations and the users' previous chatting history will affect their continued interests in future engagement.
no code implementations • ACL 2019 • Hai Ye, Wenjie Li, Lu Wang
Semantic parsing aims to transform natural language (NL) utterances into formal meaning representations (MRs), whereas an NL generator achieves the reverse: producing a NL description for some given MRs.
no code implementations • ICLR 2019 • Shen-Huan Lv, Lu Wang, Zhi-Hua Zhou
Recent research about margin theory has proved that maximizing the minimum margin like support vector machines does not necessarily lead to better performance, and instead, it is crucial to optimize the margin distribution.
no code implementations • NAACL 2019 • Xinyu Hua, Mitko Nikolov, Nikhil Badugu, Lu Wang
Peer-review plays a critical role in the scientific writing and publication ecosystem.
no code implementations • 18 Mar 2019 • Shihua Huang, Lu Wang
Driven by Convolutional Neural Networks, object detection and semantic segmentation have gained significant improvements.
1 code implementation • ICLR 2019 • Shen-Huan Lyu, Lu Wang, Zhi-Hua Zhou
We utilize a convex margin distribution loss function on the deep neural networks to validate our theoretical results by optimizing the margin ratio.
no code implementations • 12 Nov 2018 • Songmin Dai, Xiaoqiang Li, Lu Wang, Pin Wu, Weiqin Tong, Yimin Chen
We get appealing results in both tasks, which shows the independence prior is useful for instance segmentation and it is possible to unsupervisedly learn instance masks with only one image.
no code implementations • 27 Oct 2018 • Dongchi Yu, Lu Wang
Designing and modifying complex hull forms for optimal vessel performances have been a major challenge for naval architects.
no code implementations • 14 Oct 2018 • Lisa Fan, Dong Yu, Lu Wang
Sequence-to-sequence (seq2seq) neural models have been actively investigated for abstractive summarization.