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2020 – today
- 2024
[c14]Bo Peng, Xinyuan Chen, Yaohui Wang, Chaochao Lu, Yu Qiao:
ConditionVideo: Training-Free Condition-Guided Video Generation. AAAI 2024: 4459-4467- [c13]Yuewen Sun, Erli Wang, Biwei Huang, Chaochao Lu, Lu Feng, Changyin Sun, Kun Zhang:
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation. AAAI 2024: 15193-15201 - [c12]Sirui Chen, Mengying Xu, Kun Wang, Xingyu Zeng, Rui Zhao, Shengjie Zhao, Chaochao Lu:
CLEAR: Can Language Models Really Understand Causal Graphs? EMNLP (Findings) 2024: 6247-6265 - [c11]Meiqi Chen, Yixin Cao, Yan Zhang, Chaochao Lu:
Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective. EMNLP (Findings) 2024: 16449-16469 - [c10]Meiqi Chen, Bo Peng, Yan Zhang, Chaochao Lu:
CELLO: Causal Evaluation of Large Vision-Language Models. EMNLP 2024: 22353-22374 - [i16]Chaochao Lu, Chen Qian, Guodong Zheng, Hongxing Fan, Hongzhi Gao, Jie Zhang, Jing Shao, Jingyi Deng, Jinlan Fu, Kexin Huang, Kunchang Li, Lijun Li, Limin Wang, Lu Sheng
, Meiqi Chen, Ming Zhang, Qibing Ren, Sirui Chen, Tao Gui, Wanli Ouyang, Yali Wang, Yan Teng, Yaru Wang, Yi Wang, Yinan He, Yingchun Wang, Yixu Wang, Yongting Zhang, Yu Qiao, Yujiong Shen, Yurong Mou, Yuxi Chen, Zaibin Zhang, Zhelun Shi, Zhenfei Yin, Zhipin Wang:
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities. CoRR abs/2401.15071 (2024) - [i15]Heyang Gong, Chaochao Lu, Yu Zhang:
Distribution-consistency Structural Causal Models. CoRR abs/2401.15911 (2024) - [i14]Meiqi Chen, Yixin Cao, Yan Zhang, Chaochao Lu:
Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective. CoRR abs/2403.18346 (2024) - [i13]Sirui Chen, Bo Peng, Meiqi Chen, Ruiqi Wang, Mengying Xu, Xingyu Zeng, Rui Zhao, Shengjie Zhao, Yu Qiao, Chaochao Lu:
Causal Evaluation of Language Models. CoRR abs/2405.00622 (2024) - [i12]Sirui Chen, Mengying Xu, Kun Wang, Xingyu Zeng, Rui Zhao, Shengjie Zhao, Chaochao Lu:
CLEAR: Can Language Models Really Understand Causal Graphs? CoRR abs/2406.16605 (2024) - [i11]Meiqi Chen, Bo Peng, Yan Zhang, Chaochao Lu:
CELLO: Causal Evaluation of Large Vision-Language Models. CoRR abs/2406.19131 (2024) - [i10]Jinfan Hu, Jinjin Gu, Shiyao Yu, Fanghua Yu, Zheyuan Li, Zhiyuan You, Chaochao Lu, Chao Dong:
Interpreting Low-level Vision Models with Causal Effect Maps. CoRR abs/2407.19789 (2024) - 2023
- [c9]Junda Wu, Rui Wang, Handong Zhao, Ruiyi Zhang, Chaochao Lu, Shuai Li, Ricardo Henao:
Few-Shot Composition Learning for Image Retrieval with Prompt Tuning. AAAI 2023: 4729-4737 - [c8]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. NeurIPS 2023 - [i9]Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao:
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding. CoRR abs/2306.04933 (2023) - [i8]Bo Peng, Xinyuan Chen, Yaohui Wang, Chaochao Lu, Yu Qiao:
ConditionVideo: Training-Free Condition-Guided Text-to-Video Generation. CoRR abs/2310.07697 (2023) - 2022
- [c7]Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang:
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. ICLR 2022 - [c6]Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf:
Invariant Causal Representation Learning for Out-of-Distribution Generalization. ICLR 2022 - [c5]Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang:
Action-Sufficient State Representation Learning for Control with Structural Constraints. ICML 2022: 9260-9279 - 2021
- [i7]Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf:
Nonlinear Invariant Risk Minimization: A Causal Approach. CoRR abs/2102.12353 (2021) - [i6]Biwei Huang, Fan Feng, Chaochao Lu, Sara Magliacane, Kun Zhang:
AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning. CoRR abs/2107.02729 (2021) - [i5]Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang:
Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR abs/2110.05721 (2021) - 2020
- [i4]Chaochao Lu, Richard E. Turner, Yingzhen Li, Nate Kushman:
Interpreting Spatially Infinite Generative Models. CoRR abs/2007.12411 (2020) - [i3]Chaochao Lu, Biwei Huang, Ke Wang, José Miguel Hernández-Lobato, Kun Zhang, Bernhard Schölkopf:
Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation. CoRR abs/2012.09092 (2020)
2010 – 2019
- 2018
- [i2]Chaochao Lu, Bernhard Schölkopf, José Miguel Hernández-Lobato:
Deconfounding Reinforcement Learning in Observational Settings. CoRR abs/1812.10576 (2018) - 2017
- [c4]Chaochao Lu, Michael Hirsch, Bernhard Schölkopf:
Flexible Spatio-Temporal Networks for Video Prediction. CVPR 2017: 2137-2145 - 2015
- [c3]Chaochao Lu, Xiaoou Tang:
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace. AAAI 2015: 3811-3819 - 2014
- [c2]Chaochao Lu, Xiaoou Tang:
Learning the Face Prior for Bayesian Face Recognition. ECCV (4) 2014: 119-134 - [i1]Chaochao Lu, Xiaoou Tang:
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace. CoRR abs/1404.3840 (2014) - 2013
- [c1]Chaochao Lu, Deli Zhao, Xiaoou Tang:
Face Recognition Using Face Patch Networks. ICCV 2013: 3288-3295
Coauthor Index
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