Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. - Guiliang Liu; Oliver Schulte; Wang Zhu 001; Qingcan Li (ECML/PKDD (2), 2018)

Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. - Guiliang Liu; Wang Zhu 001; Oliver Schulte (MLSA@PKDD/ECML, 2018)

BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. - Wang Zhu 001; Hexiang Hu; Jiacheng Chen; Zhiwei Deng; Vihan Jain; Eugene Ie; Fei Sha (ACL, 2020)

Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks. - Wang Zhu 001; Peter Shaw 004; Tal Linzen; Fei Sha (CoRR, 2021)

Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems. - Wang Zhu 001; Jesse Thomason; Robin Jia (EMNLP (Findings), 2022)

Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning. - Yejia Liu; Wang Zhu 001; Shaolei Ren (NeurIPS, 2022)

Iterative Vision-and-Language Navigation. - Jacob Krantz; Shurjo Banerjee; Wang Zhu 001; Jason J. Corso; Peter Anderson; Stefan Lee; Jesse Thomason (CVPR, 2023)

Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering. - Wang Zhu 001; Jesse Thomason; Robin Jia (EMNLP, 2023)

Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions? - Wang Zhu 001; Ishika Singh; Yuan Huang; Robin Jia; Jesse Thomason (CoRR, 2023)

Efficient End-to-End Visual Document Understanding with Rationale Distillation. - Wang Zhu 001; Alekh Agarwal; Mandar Joshi; Robin Jia; Jesse Thomason; Kristina Toutanova (NAACL-HLT, 2024)

Language Models can Infer Action Semantics for Classical Planners from Environment Feedback. - Wang Zhu 001; Ishika Singh; Robin Jia; Jesse Thomason (CoRR, 2024)

VisualLens: Personalization through Visual History. - Wang Bill Zhu; Deqing Fu; Kai Sun; Yi Lu; Zhaojiang Lin; Seungwhan Moon; Kanika Narang; Mustafa Canim; Yue Liu; Anuj Kumar; Xin Luna Dong (CoRR, 2024)

MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks. - Jiacheng Chen; Tianhao Liang; Sherman Siu; Zhengqing Wang; Kai Wang 068; Yubo Wang; Yuansheng Ni; Ziyan Jiang; Wang Zhu 001; Bohan Lyu 001; Dongfu Jiang; Xuan He; et al. (ICLR, 2025)

TLDR: Token-Level Detective Reward Model for Large Vision Language Models. - Deqing Fu; Tong Xiao; Rui Wang; Wang Zhu 001; Pengchuan Zhang; Guan Pang; Robin Jia; Lawrence Chen 002 (ICLR, 2025)

Language Models Can Infer Action Semantics for Symbolic Planners from Environment Feedback. - Wang Bill Zhu; Ishika Singh; Robin Jia; Jesse Thomason (NAACL (Long Papers), 2025)

Cancer-Myth: Evaluating AI Chatbot on Patient Questions with False Presuppositions. - Wang Bill Zhu; Tianqi Chen; Ching Ying Lin; Jade Law; Mazen Jizzini; Jorge J. Nieva; Ruishan Liu; Robin Jia (CoRR, 2025)

Zero-Shot Iterative Formalization and Planning in Partially Observable Environments. - Liancheng Gong; Wang Zhu 001; Jesse Thomason; Li Zhang (CoRR, 2025)

PSALM-V: Automating Symbolic Planning in Interactive Visual Environments with Large Language Models. - Wang Bill Zhu; Miaosen Chai; Ishika Singh; Robin Jia; Jesse Thomason (CoRR, 2025)

Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning. - Ang Li; Charles Wang; Kaiyu Yue; Zikui Cai; Ollie Liu; Deqing Fu; Peng Guo; Wang Bill Zhu; Vatsal Sharan; Robin Jia; Willie Neiswanger; Furong Huang; et al. (CoRR, 2025)