Li, Chun-Liang

50 publications

ICLR 2026 Rethinking JEPA: Compute‑Efficient Video Self-Supervised Learning with Frozen Teachers Xianhang Li, Chen Huang, Chun-Liang Li, Eran Malach, Joshua M. Susskind, Vimal Thilak, Etai Littwin

TMLR 2025 An Expanded Benchmark That Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets Po-Yi Lu, Yi-Jie Cheng, Chun-Liang Li, Hsuan-Tien Lin

CVPR 2025 FastVLM: Efficient Vision Encoding for Vision Language Models Pavan Kumar Anasosalu Vasu, Fartash Faghri, Chun-Liang Li, Cem Koc, Nate true, Albert Antony, Gokula Santhanam, James Gabriel, Peter Grasch, Oncel Tuzel, Hadi Pouransari

ICLRW 2025 FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations Cheng-Yu Hsieh, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Hadi Pouransari

ICLRW 2025 The Delta Learning Hypothesis: Preference Tuning on Weak Data Can Yield Strong Gains Scott Geng, Hamish Ivison, Chun-Liang Li, Maarten Sap, Jerry Li, Ranjay Krishna, Pang Wei Koh

ICLR 2024 Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding 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

NeurIPS 2024 Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel

NeurIPS 2024 The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna

WACV 2023 Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister

CVPR 2023 Hyperbolic Contrastive Learning for Visual Representations Beyond Objects Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs

AAAI 2023 Neural Spline Search for Quantile Probabilistic Modeling Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister

CVPR 2023 Pic2Word: Mapping Pictures to Words for Zero-Shot Composed Image Retrieval Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

CVPR 2023 Prefix Conditioning Unifies Language and Label Supervision Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister

TMLR 2023 SPADE: Semi-Supervised Anomaly Detection Under Distribution Mismatch Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Tomas Pfister

TMLR 2023 TSMixer: An All-MLP Architecture for Time Series Forecast-Ing Si-An Chen, Chun-Liang Li, Sercan O Arik, Nathanael Christian Yoder, Tomas Pfister

WACV 2023 Unifying Distribution Alignment as a Loss for Imbalanced Semi-Supervised Learning Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister

AISTATS 2022 Decoupling Local and Global Representations of Time Series Sana Tonekaboni, Chun-Liang Li, Sercan O. Arik, Anna Goldenberg, Tomas Pfister

ICLR 2022 DISSECT: Disentangled Simultaneous Explanations via Concept Traversals Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind Picard

ECCV 2022 Learning Instance-Specific Adaptation for Cross-Domain Segmentation Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang

TMLR 2022 Self-Supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Chen-Yu Lee, Tomas Pfister

ICLR 2021 $i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee

NeurIPS 2021 A Unified View of cGANs with and Without Classifiers Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin

CVPR 2021 CutPaste: Self-Supervised Learning for Anomaly Detection and Localization Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister

NeurIPSW 2021 Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin

ICLR 2021 Learning and Evaluating Representations for Deep One-Class Classification Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister

NeurIPS 2021 Object-Aware Contrastive Learning for Debiased Scene Representation Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin

ICLR 2021 PseudoSeg: Designing Pseudo Labels for Semantic Segmentation Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister

NeurIPS 2021 Robust Contrastive Learning Using Negative Samples with Diminished Semantics Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs

UAI 2021 Unsupervised Program Synthesis for Images by Sampling Without Replacement Chenghui Zhou, Chun-Liang Li, Barnabás Póczos

NeurIPS 2020 FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin A Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li

NeurIPS 2020 Interpretable Sequence Learning for Covid-19 Forecasting Sercan Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister

NeurIPS 2020 On Completeness-Aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh, Been Kim, Sercan Arik, Chun-Liang Li, Tomas Pfister, Pradeep K. Ravikumar

ICLR 2019 Beyond Pixel Norm-Balls: Parametric Adversaries Using an Analytically Differentiable Renderer Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson

AISTATS 2019 Implicit Kernel Learning Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabas Poczos

ICLR 2019 Kernel Change-Point Detection with Auxiliary Deep Generative Models Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos

CVPR 2019 LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds Chun-Liang Li, Tomas Simon, Jason Saragih, Barnabas Poczos, Yaser Sheikh

ICLRW 2019 Point Cloud GAN Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov

NeurIPS 2018 Nonparametric Density Estimation Under Adversarial Losses Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabas Poczos

ICLR 2018 Sobolev GAN Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng

IJCAI 2017 Data-Driven Random Fourier Features Using Stein Effect Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos

NeurIPS 2017 MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabas Poczos

ICCV 2017 One Network to Solve Them All -- Solving Linear Inverse Problems Using Deep Projection Models J. H. Rick Chang, Chun-Liang Li, Barnabas Poczos, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan

AAAI 2017 Polynomial Optimization Methods for Matrix Factorization Po-Wei Wang, Chun-Liang Li, J. Zico Kolter

AISTATS 2016 High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider

AISTATS 2016 Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu

UAI 2016 Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods Chun-Liang Li, Barnabás Póczos

JMLR 2015 Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013 Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-de Lin, Hsuan-Tien Lin, Chih-Jen Lin

ICML 2014 Condensed Filter Tree for Cost-Sensitive Multi-Label Classification Chun-Liang Li, Hsuan-Tien Lin

JMLR 2014 Effective String Processing and Matching for Author Disambiguation Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin

ACML 2012 Active Learning with Hinted Support Vector Machine Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin