Chun-Liang Li - RankMe

127 papers A* 26A 9C 1Journal 72Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pre-training. EACL (Findings) Jeffrey Li, Joshua P. Gardner, Doug Kang, Fangping Shi, Karanjeet Singh, Chun-Liang Li, Herumb Shandilya, David Leo Wright Hall, Oncel Tuzel, Percy Liang, Ludwig Schmidt, Hadi Pouransari, Fartash Faghri
2026	J	`jnl`	Beyond a Single Extractor: Re-thinking HTML-to-Text Extraction for LLM Pretraining. CoRR Jeffrey Li, Josh Gardner, Doug Kang, Fangping Shi, Karanjeet Singh, Chun-Liang Li, Herumb Shandilya, David Hall, Oncel Tuzel, Percy Liang, Ludwig Schmidt, Hadipour Ansari, Fartash Faghri
2026	J	`jnl`	TrajTok: Learning Trajectory Tokens enables better Video Understanding. CoRR Chenhao Zheng, Jieyu Zhang, Jianing Zhang, Weikai Huang, Ashutosh Kumar, Quan Kong, Oncel Tuzel, Chun-Liang Li, Ranjay Krishna
2025	J	`jnl`	AMUSE: Audio-Visual Benchmark and Alignment Framework for Agentic Multi-Speaker Understanding. CoRR Sanjoy Chowdhury, Karren D. Yang, Xudong Liu, Fartash Faghri, Pavan Kumar Anasosalu Vasu, Oncel Tuzel, Dinesh Manocha, Chun-Liang Li, Raviteja Vemulapalli
2025	J	`jnl`	An Expanded Benchmark that Rediscovers and Affirms the Edge of Uncertainty Sampling for Active Learning in Tabular Datasets. Trans. Mach. Learn. Res. Po-Yi Lu, Yi-Jie Cheng, Chun-Liang Li, Hsuan-Tien Lin
2025	A*	`conf`	FastVLM: Efficient Vision Encoding for Vision Language Models. CVPR 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
2025	J	`jnl`	FocalLens: Instruction Tuning Enables Zero-Shot Conditional Image Representations. CoRR Cheng-Yu Hsieh, Pavan Kumar Anasosalu Vasu, Fartash Faghri, Raviteja Vemulapalli, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Hadi Pouransari
2025	J	`jnl`	Rethinking JEPA: Compute-Efficient Video SSL with Frozen Teachers. CoRR Xianhang Li, Chen Huang, Chun-Liang Li, Eran Malach, Josh M. Susskind, Vimal Thilak, Etai Littwin
2025	J	`jnl`	The Delta Learning Hypothesis: Preference Tuning on Weak Data can Yield Strong Gains. CoRR Scott Geng, Hamish Ivison, Chun-Liang Li, Maarten Sap, Jerry Li, Ranjay Krishna, Pang Wei Koh
2024	A*	`conf`	Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. ICLR 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
2024	J	`jnl`	Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding. CoRR 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
2024	—	`conf`	CodecLM: Aligning Language Models with Tailored Synthetic Data. NAACL-HLT (Findings) Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister
2024	J	`jnl`	CodecLM: Aligning Language Models with Tailored Synthetic Data. CoRR Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, Tomas Pfister
2024	A*	`conf`	Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. NeurIPS Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel
2024	J	`jnl`	Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum. CoRR Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, Pavan Kumar Anasosalu Vasu, Cem Koc, Vaishaal Shankar, Oncel Tuzel
2024	J	`jnl`	FastVLM: Efficient Vision Encoding for Vision Language Models. CoRR 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
2024	J	`jnl`	Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR 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
2024	—	`conf`	Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) 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
2024	J	`jnl`	Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR 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
2024	—	`conf`	MUSCLE: A Model Update Strategy for Compatible LLM Evolution. EMNLP (Findings) Jessica Maria Echterhoff, Fartash Faghri, Raviteja Vemulapalli, Ting-Yao Hu, Chun-Liang Li, Oncel Tuzel, Hadi Pouransari
2024	J	`jnl`	MUSCLE: A Model Update Strategy for Compatible LLM Evolution. CoRR Jessica Maria Echterhoff, Fartash Faghri, Raviteja Vemulapalli, Ting-Yao Hu, Chun-Liang Li, Oncel Tuzel, Hadi Pouransari
2024	A*	`conf`	The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. NeurIPS Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna
2024	J	`jnl`	The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. CoRR Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna
2023	A	`conf`	Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
2023	—	`conf`	Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. ACL (Findings) Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
2023	J	`jnl`	Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
2023	—	`conf`	FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. ACL (1) 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
2023	J	`jnl`	FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. CoRR 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
2023	A*	`conf`	Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CVPR Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
2023	A*	`conf`	Neural Spline Search for Quantile Probabilistic Modeling. AAAI Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister
2023	J	`jnl`	Neural Spline Search for Quantile Probabilistic Modeling. CoRR Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister
2023	A*	`conf`	Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CVPR Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
2023	J	`jnl`	Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CoRR Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
2023	A*	`conf`	Prefix Conditioning Unifies Language and Label Supervision. CVPR Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
2023	J	`jnl`	Re-Benchmarking Pool-Based Active Learning for Binary Classification. CoRR Po-Yi Lu, Chun-Liang Li, Hsuan-Tien Lin
2023	J	`jnl`	SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
2023	J	`jnl`	TSMixer: An All-MLP Architecture for Time Series Forecast-ing. Trans. Mach. Learn. Res. Si-An Chen, Chun-Liang Li, Sercan Ö. Arik, Nathanael C. Yoder, Tomas Pfister
2023	J	`jnl`	TSMixer: An all-MLP Architecture for Time Series Forecasting. CoRR Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister
2023	J	`jnl`	Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
2023	A	`conf`	Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning. WACV Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister
2022	A*	`conf`	DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. ICLR Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard
2022	A	`conf`	Decoupling Local and Global Representations of Time Series. AISTATS Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
2022	J	`jnl`	Decoupling Local and Global Representations of Time Series. CoRR Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister
2022	—	`conf`	FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. ACL (1) Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister
2022	J	`jnl`	FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. CoRR Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister
2022	J	`jnl`	Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CoRR Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs
2022	—	`conf`	Learning Instance-Specific Adaptation for Cross-Domain Segmentation. ECCV (33) Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang
2022	J	`jnl`	Learning Instance-Specific Adaptation for Cross-Domain Segmentation. CoRR Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang
2022	J	`jnl`	Prefix Conditioning Unifies Language and Label Supervision. CoRR Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister
2022	J	`jnl`	SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister
2022	J	`jnl`	Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
2021	A*	`conf`	A Unified View of cGANs with and without Classifiers. NeurIPS Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	J	`jnl`	A Unified View of cGANs with and without Classifiers. CoRR Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	J	`jnl`	A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 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
2021	J	`jnl`	Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister
2021	J	`jnl`	Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling. IEEE Trans. Neural Networks Learn. Syst. Haoran You, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou
2021	A*	`conf`	CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
2021	J	`jnl`	CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister
2021	J	`jnl`	DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. CoRR Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard
2021	J	`jnl`	Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin
2021	A*	`conf`	Learning and Evaluating Representations for Deep One-Class Classification. ICLR Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
2021	A*	`conf`	Object-aware Contrastive Learning for Debiased Scene Representation. NeurIPS Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin
2021	J	`jnl`	Object-aware Contrastive Learning for Debiased Scene Representation. CoRR Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin
2021	A*	`conf`	PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. ICLR Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
2021	—	`conf`	ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. ACL/IJCNLP (2) Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister
2021	J	`jnl`	ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. CoRR Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister
2021	A*	`conf`	Robust Contrastive Learning Using Negative Samples with Diminished Semantics. NeurIPS Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs
2021	J	`jnl`	Robust Contrastive Learning Using Negative Samples with Diminished Semantics. CoRR Songwei Ge, Shlok Mishra, Haohan Wang, Chun-Liang Li, David Jacobs
2021	J	`jnl`	Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister
2021	A	`conf`	Unsupervised program synthesis for images by sampling without replacement. UAI Chenghui Zhou, Chun-Liang Li, Barnabás Póczos
2021	A*	`conf`	i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. ICLR Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
2020	J	`jnl`	A Simple Semi-Supervised Learning Framework for Object Detection. CoRR Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, Tomas Pfister
2020	A*	`conf`	FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. NeurIPS Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li
2020	J	`jnl`	FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. CoRR Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel
2020	J	`jnl`	Interpretable Sequence Learning for COVID-19 Forecasting. CoRR 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
2020	A*	`conf`	Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS 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
2020	J	`jnl`	Kernel Stein Generative Modeling. CoRR Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh, Yiming Yang
2020	—	`—`	Learning Generative Models using Transformations. Chun-Liang Li
2020	J	`jnl`	Learning and Evaluating Representations for Deep One-class Classification. CoRR Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
2020	A*	`conf`	On Completeness-aware Concept-Based Explanations in Deep Neural Networks. NeurIPS Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar
2020	J	`jnl`	PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. CoRR Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister
2020	J	`jnl`	Unsupervised Program Synthesis for Images using Tree-Structured LSTM. CoRR Chenghui Zhou, Chun-Liang Li, Barnabás Póczos
2020	J	`jnl`	i-Mix: A Strategy for Regularizing Contrastive Representation Learning. CoRR Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee
2019	—	`conf`	Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer. ICLR (Poster) Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson
2019	J	`jnl`	Developing Creative AI to Generate Sculptural Objects. CoRR Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, Manzil Zaheer, Barnabás Póczos
2019	J	`jnl`	Getting Topology and Point Cloud Generation to Mesh. CoRR Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang
2019	A	`conf`	Implicit Kernel Learning. AISTATS Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
2019	J	`jnl`	Implicit Kernel Learning. CoRR Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos
2019	—	`conf`	Kernel Change-point Detection with Auxiliary Deep Generative Models. ICLR (Poster) Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
2019	J	`jnl`	Kernel Change-point Detection with Auxiliary Deep Generative Models. CoRR Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
2019	A*	`conf`	LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds. CVPR Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh
2019	J	`jnl`	LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds. CoRR Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh
2019	J	`jnl`	Learned Interpolation for 3D Generation. CoRR Austin Dill, Songwei Ge, Eunsu Kang, Chun-Liang Li, Barnabás Póczos
2019	J	`jnl`	On Concept-Based Explanations in Deep Neural Networks. CoRR Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister
2019	—	`conf`	Point Cloud GAN. DGS@ICLR Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov
2018	J	`jnl`	Adversarial Geometry and Lighting using a Differentiable Renderer. CoRR Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson
2018	J	`jnl`	Bayesian CycleGAN via Marginalizing Latent Sampling. CoRR Haoran You, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou
2018	A	`conf`	Classifier Two Sample Test for Video Anomaly Detections. BMVC Yusha Liu, Chun-Liang Li, Barnabás Póczos
2018	J	`jnl`	Hallucinating Point Cloud into 3D Sculptural Object. CoRR Chun-Liang Li, Eunsu Kang, Songwei Ge, Lingyao Zhang, Austin Dill, Manzil Zaheer, Barnabás Póczos
2018	A*	`conf`	Nonparametric Density Estimation under Adversarial Losses. NeurIPS Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos
2018	J	`jnl`	Nonparametric Density Estimation under Adversarial Losses. CoRR Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos
2018	J	`jnl`	Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond. CoRR Xi Ouyang, Yu Cheng, Yifan Jiang, Chun-Liang Li, Pan Zhou
2018	J	`jnl`	Point Cloud GAN. CoRR Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov
2018	—	`conf`	Sobolev GAN. ICLR (Poster) Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
2017	A*	`conf`	Data-driven Random Fourier Features using Stein Effect. IJCAI Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
2017	J	`jnl`	Data-driven Random Fourier Features using Stein Effect. CoRR Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos
2017	—	`conf`	MMD GAN: Towards Deeper Understanding of Moment Matching Network. NIPS Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos
2017	J	`jnl`	MMD GAN: Towards Deeper Understanding of Moment Matching Network. CoRR Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos
2017	A*	`conf`	One Network to Solve Them All - Solving Linear Inverse Problems Using Deep Projection Models. ICCV Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar
2017	J	`jnl`	One Network to Solve Them All - Solving Linear Inverse Problems using Deep Projection Models. CoRR Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan
2017	A*	`conf`	Polynomial Optimization Methods for Matrix Factorization. AAAI Po-Wei Wang, Chun-Liang Li, J. Zico Kolter
2017	J	`jnl`	Sobolev GAN. CoRR Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng
2016	J	`jnl`	Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM. CoRR Chun-Liang Li, Siamak Ravanbakhsh, Barnabás Póczos
2016	A	`conf`	High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider
2016	A	`conf`	Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
2016	A	`conf`	Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods. UAI Chun-Liang Li, Barnabás Póczos
2015	J	`jnl`	Active Learning Using Hint Information. Neural Comput. Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
2015	J	`jnl`	Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013. J. Mach. Learn. Res. 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
2015	J	`jnl`	Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. CoRR Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu
2014	A*	`conf`	Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. ICML Chun-Liang Li, Hsuan-Tien Lin
2014	J	`jnl`	Effective string processing and matching for author disambiguation. J. Mach. Learn. Res. 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
2014	A*	`conf`	POSTER: Scanning-free Personalized Malware Warning System by Learning Implicit Feedback from Detection Logs. CCS Jyun-Yu Jiang, Chun-Liang Li, Chun-Pai Yang, Chung-Tsai Su
2013	—	`conf`	Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. KDD Cup 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
2013	—	`conf`	Effective string processing and matching for author disambiguation. KDD Cup Wei-Sheng Chin, Yu-Chin Juan, Yong Zhuang, 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
2012	—	`conf`	A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. KDD Cup Po-Lung Chen, Chen-Tse Tsai, Yao-Nan Chen, Ku-Chun Chou, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Yu-Cheng Chou, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Rong-Bing Chiu, Chieh-Yen Lin, Chien-Chih Wang, Po-Wei Wang, Wei-Lun Su, Chen-Hung Wu, Tsung-Ting Kuo, Todd G. McKenzie, Ya-Hsuan Chang, Chun-Sung Ferng, Chia-Mau Ni, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin
2012	C	`conf`	Active Learning with Hinted Support Vector Machine. ACML Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
2012	—	`conf`	Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation. KDD Cup Todd G. McKenzie, Chun-Sung Ferng, Yao-Nan Chen, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Ya-Hsuan Chang, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Chieh-Yen Lin, Po-Wei Wang, Chia-Mau Ni, Wei-Lun Su, Tsung-Ting Kuo, Chen-Tse Tsai, Po-Lung Chen, Rong-Bing Chiu, Ku-Chun Chou, Yu-Cheng Chou, Chien-Chih Wang, Chen-Hung Wu, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin