Chun-Liang Li

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 101

Top Venues

CoRR

NeurIPS

ICLR

CVPR

Publications

Jessica Maria Echterhoff, Fartash Faghri, Raviteja Vemulapalli, Ting-Yao Hu, Chun-Liang Li, Oncel Tuzel, Hadi Pouransari
MUSCLE: A Model Update Strategy for Compatible LLM Evolution. CoRR (2024)
Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh, Louis Béthune, Hadipour Ansari, Pavan Kumar Anasosalu Vasu, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Marco Cuturi
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR (2024)
Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. CoRR (2024)
Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR (2024)
Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel
Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. CoRR (2024)
Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. ICLR (2024)
Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) (2024)
Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister
CodecLM: Aligning Language Models with Tailored Synthetic Data. CoRR (2024)
Zilong Wang, Hao Zhang, Chun-Liang Li, Julian Martin Eisenschlos, Vincent Perot, Zifeng Wang, Lesly Miculicich, Yasuhisa Fujii, Jingbo Shang, Chen-Yu Lee, Tomas Pfister
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. CoRR (2024)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. ACL (Findings) (2023)
Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CVPR (2023)
Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CoRR (2023)
Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
Prefix Conditioning Unifies Language and Label Supervision. CVPR (2023)
Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR (2023)
Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolai Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. CoRR (2023)
Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV (2023)
Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister
Neural Spline Search for Quantile Probabilistic Modeling. CoRR (2023)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. 2023 (2023)
Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister
TSMixer: An all-MLP Architecture for Time Series Forecasting. CoRR (2023)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR (2023)
Si-An Chen, Chun-Liang Li, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister
TSMixer: An All-MLP Architecture for Time Series Forecast-ing. Trans. Mach. Learn. Res. 2023 (2023)
Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister
Neural Spline Search for Quantile Probabilistic Modeling. AAAI (2023)
Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolay Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. ACL (1) (2023)
Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin
Re-Benchmarking Pool-Based Active Learning for Binary Classification. CoRR (2023)
Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CVPR (2023)
Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister
Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning. WACV (2023)
Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. CoRR (2022)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. 2022 (2022)
Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. ACL (1) (2022)
Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
Decoupling Local and Global Representations of Time Series. CoRR (2022)
Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CoRR (2022)
Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
Decoupling Local and Global Representations of Time Series. AISTATS (2022)
Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
Prefix Conditioning Unifies Language and Label Supervision. CoRR (2022)
Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. ECCV (33) (2022)
Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. ICLR (2022)
Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. CoRR (2022)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR (2022)
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. ICLR (2021)
Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR (2021)
Haoran You, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou
Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling. IEEE Trans. Neural Networks Learn. Syst. 32 (10) (2021)
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. ICLR (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
A Unified View of cGANs with and without Classifiers. CoRR (2021)
Chenghui Zhou, Chun-Liang Li, Barnabás Póczos
Unsupervised program synthesis for images by sampling without replacement. UAI (2021)
Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR (2021)
Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR (2021)
Sercan Ö. Arik, Joel Shor, Rajarishi Sinha, Jinsung Yoon, Joseph R. Ledsam, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai, Daisuke Yoneoka, Shuhei Nomura, Hiroaki Miyata, Tomas Pfister
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021)
Songwei Ge, Shlok Mishra, Haohan Wang, Chun-Liang Li, David W. Jacobs
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. CoRR (2021)
Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin
Object-aware Contrastive Learning for Debiased Scene Representation. NeurIPS (2021)
Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. CoRR (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
A Unified View of cGANs with and without Classifiers. NeurIPS (2021)
Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR (2021)
Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. ACL/IJCNLP (2) (2021)
Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin
Object-aware Contrastive Learning for Debiased Scene Representation. CoRR (2021)
Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. NeurIPS (2021)
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Learning and Evaluating Representations for Deep One-Class Classification. ICLR (2021)
Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. CoRR (2021)
Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR (2021)
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Learning and Evaluating Representations for Deep One-class Classification. CoRR (2020)
Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar
On Completeness-aware Concept-Based Explanations in Deep Neural Networks. NeurIPS (2020)
Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, Tomas Pfister
A Simple Semi-Supervised Learning Framework for Object Detection. CoRR (2020)
Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
i-Mix: A Strategy for Regularizing Contrastive Representation Learning. CoRR (2020)
Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR (2020)
Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. CoRR (2020)
Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. CoRR (2020)
Chenghui Zhou, Chun-Liang Li, Barnabás Póczos
Unsupervised Program Synthesis for Images using Tree-Structured LSTM. CoRR (2020)
Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. NeurIPS (2020)
Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS (2020)
Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh, Yiming Yang
Kernel Stein Generative Modeling. CoRR (2020)
Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister
On Concept-Based Explanations in Deep Neural Networks. CoRR (2019)
Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
Implicit Kernel Learning. CoRR (2019)
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
Kernel Change-point Detection with Auxiliary Deep Generative Models. ICLR (Poster) (2019)
Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer. ICLR (Poster) (2019)
Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh
LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds. CVPR (2019)
Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang
Getting Topology and Point Cloud Generation to Mesh. CoRR (2019)
Austin Dill, Songwei Ge, Eunsu Kang, Chun-Liang Li, Barnabás Póczos
Learned Interpolation for 3D Generation. CoRR (2019)
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
Kernel Change-point Detection with Auxiliary Deep Generative Models. CoRR (2019)
Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, Manzil Zaheer, Barnabás Póczos
Developing Creative AI to Generate Sculptural Objects. CoRR (2019)
Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
Implicit Kernel Learning. AISTATS (2019)
Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov
Point Cloud GAN. DGS@ICLR (2019)
Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh
LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds. CoRR (2019)
Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos
Nonparametric Density Estimation under Adversarial Losses. NeurIPS (2018)
Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov
Point Cloud GAN. CoRR (2018)
Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos
Nonparametric Density Estimation under Adversarial Losses. CoRR (2018)
Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
Sobolev GAN. ICLR (Poster) (2018)
Haoran You, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou
Bayesian CycleGAN via Marginalizing Latent Sampling. CoRR (2018)
Chun-Liang Li, Eunsu Kang, Songwei Ge, Lingyao Zhang, Austin Dill, Manzil Zaheer, Barnabás Póczos
Hallucinating Point Cloud into 3D Sculptural Object. CoRR (2018)
Yusha Liu, Chun-Liang Li, Barnabás Póczos
Classifier Two Sample Test for Video Anomaly Detections. BMVC (2018)
Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson
Adversarial Geometry and Lighting using a Differentiable Renderer. CoRR (2018)
Xi Ouyang, Yu Cheng, Yifan Jiang, Chun-Liang Li, Pan Zhou
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond. CoRR (2018)
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos
MMD GAN: Towards Deeper Understanding of Moment Matching Network. NIPS (2017)
Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
Sobolev GAN. CoRR (2017)
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
Data-driven Random Fourier Features using Stein Effect. CoRR (2017)
Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos
MMD GAN: Towards Deeper Understanding of Moment Matching Network. CoRR (2017)
Po-Wei Wang, Chun-Liang Li, J. Zico Kolter
Polynomial Optimization Methods for Matrix Factorization. AAAI (2017)
Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan
One Network to Solve Them All - Solving Linear Inverse Problems using Deep Projection Models. CoRR (2017)
Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
Data-driven Random Fourier Features using Stein Effect. IJCAI (2017)
Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar
One Network to Solve Them All - Solving Linear Inverse Problems Using Deep Projection Models. ICCV (2017)
Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS (2016)
Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS (2016)
Chun-Liang Li, Barnabás Póczos
Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods. UAI (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Chun-Liang Li