Li, Chun-Liang

48 publications

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

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