Liu, Yao

31 publications

ICLR 2025 AgentOccam: A Simple yet Strong Baseline for LLM-Based Web Agents Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala

NeurIPS 2025 Ask a Strong LLM Judge When Your Reward Model Is Uncertain Zhenghao Xu, Qin Lu, Qingru Zhang, Liang Qiu, Ilgee Hong, Changlong Yu, Wenlin Yao, Yao Liu, Haoming Jiang, Lihong Li, Hyokun Yun, Tuo Zhao

TMLR 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICLRW 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

IJCAI 2025 D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning Jia Zhang, Chen-Xi Zhang, Yao Liu, Yi-Xuan Jin, Xiao-Wen Yang, Bo Zheng, Yi Liu, Lan-Zhe Guo

ECML-PKDD 2025 Improving Temporal Knowledge Graph Reasoning with Hierarchical Semantic-Aware Contrastive Learning Renning Pang, Yao Liu, Yanglei Gan, Tingting Dai, Yashen Wang, Xiaojun Shi, Tian Lan, Qiao Liu

TMLR 2025 Offline Learning and Forgetting for Reasoning with Large Language Models Tianwei Ni, Allen Nie, Sapana Chaudhary, Yao Liu, Huzefa Rangwala, Rasool Fakoor

CoRL 2024 EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J Lim, Yao Liu, Rasool Fakoor

ICML 2024 Learning the Target Network in Function Space Kavosh Asadi, Yao Liu, Shoham Sabach, Ming Yin, Rasool Fakoor

MLJ 2024 Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task Sherry Ruan, Allen Nie, William Steenbergen, Jiayu He, J. Q. Zhang, Meng Guo, Yao Liu, Kyle Dang Nguyen, Catherine Y. Wang, Rui Ying, James A. Landay, Emma Brunskill

ECML-PKDD 2024 SAGS-DynamicBio: Integrating Semantic-Aware and Graph Structure-Aware Embedding for Dynamic Biological Data with Knowledge Graphs Yao Liu, Yongfei Zhang, Xin Wang

ICLR 2024 TAIL: Task-Specific Adapters for Imitation Learning with Large Pretrained Models Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

MLJ 2024 Towards Adaptive Unknown Authentication for Universal Domain Adaptation by Classifier Paradox Yunyun Wang, Yao Liu, Songcan Chen

AAAI 2024 patchDPCC: A Patchwise Deep Compression Framework for Dynamic Point Clouds Zirui Pan, Mengbai Xiao, Xu Han, Dongxiao Yu, Guanghui Zhang, Yao Liu

NeurIPS 2023 Budgeting Counterfactual for Offline RL Yao Liu, Pratik Chaudhari, Rasool Fakoor

NeurIPSW 2023 TAIL: Task-Specific Adapters for Imitation Learning with Large Pretrained Models Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, Rasool Fakoor

NeurIPS 2023 TD Convergence: An Optimization Perspective Kavosh Asadi, Shoham Sabach, Yao Liu, Omer Gottesman, Rasool Fakoor

ICML 2022 Generalized Federated Learning via Sharpness Aware Minimization Zhe Qu, Xingyu Li, Rui Duan, Yao Liu, Bo Tang, Zhuo Lu

UAI 2022 Offline Policy Optimization with Eligible Actions Yao Liu, Yannis Flet-Berliac, Emma Brunskill

NeurIPS 2022 Provably Sample-Efficient RL with Side Information About Latent Dynamics Yao Liu, Dipendra Misra, Miro Dudik, Robert E. Schapire

AAAI 2021 Asynchronous Teacher Guided Bit-Wise Hard Mining for Online Hashing Sheng Jin, Qin Zhou, Hongxun Yao, Yao Liu, Xian-Sheng Hua

ICML 2020 Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions Omer Gottesman, Joseph Futoma, Yao Liu, Sonali Parbhoo, Leo Celi, Emma Brunskill, Finale Doshi-Velez

NeurIPS 2020 Provably Good Batch Off-Policy Reinforcement Learning Without Great Exploration Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

AAAI 2020 SSAH: Semi-Supervised Adversarial Deep Hashing with Self-Paced Hard Sample Generation Sheng Jin, Shangchen Zhou, Yao Liu, Chao Chen, Xiaoshuai Sun, Hongxun Yao, Xian-Sheng Hua

ICML 2020 Understanding the Curse of Horizon in Off-Policy Evaluation via Conditional Importance Sampling Yao Liu, Pierre-Luc Bacon, Emma Brunskill

ICML 2019 Combining Parametric and Nonparametric Models for Off-Policy Evaluation Omer Gottesman, Yao Liu, Scott Sussex, Emma Brunskill, Finale Doshi-Velez

ICMLW 2019 Off-Policy Policy Gradient with State Distribution Correction Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

UAI 2019 Off-Policy Policy Gradient with Stationary Distribution Correction Yao Liu, Adith Swaminathan, Alekh Agarwal, Emma Brunskill

ACML 2018 A Scalable Heterogeneous Parallel SOM Based on MPI/CUDA Yao Liu, Jun Sun, Qing Yao, Su Wang, Kai Zheng, Yan Liu

NeurIPS 2018 Representation Balancing MDPs for Off-Policy Policy Evaluation Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo A Faisal, Finale Doshi-Velez, Emma Brunskill

IJCAI 2016 A Decision Procedure for a Fragment of Linear Time Mu-Calculus Yao Liu, Zhenhua Duan, Cong Tian