Wang Zhu - RankMe

23 papers A* 6Journal 13Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks. ICLR Jiacheng Chen, Tianhao Liang, Sherman Siu, Zhengqing Wang, Kai Wang, Yubo Wang, Yuansheng Ni, Ziyan Jiang, Wang Zhu, Bohan Lyu, Dongfu Jiang, Xuan He, Yuan Liu, Hexiang Hu, Xiang Yue, Wenhu Chen
2025	A*	`conf`	TLDR: Token-Level Detective Reward Model for Large Vision Language Models. ICLR Deqing Fu, Tong Xiao, Rui Wang, Wang Zhu, Pengchuan Zhang, Guan Pang, Robin Jia, Lawrence Chen
2025	J	`jnl`	Zero-Shot Iterative Formalization and Planning in Partially Observable Environments. CoRR Liancheng Gong, Wang Zhu, Jesse Thomason, Li Zhang
2024	—	`conf`	Efficient End-to-End Visual Document Understanding with Rationale Distillation. NAACL-HLT Wang Zhu, Alekh Agarwal, Mandar Joshi, Robin Jia, Jesse Thomason, Kristina Toutanova
2024	J	`jnl`	Language Models can Infer Action Semantics for Classical Planners from Environment Feedback. CoRR Wang Zhu, Ishika Singh, Robin Jia, Jesse Thomason
2024	J	`jnl`	MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks. CoRR Jiacheng Chen, Tianhao Liang, Sherman Siu, Zhengqing Wang, Kai Wang, Yubo Wang, Yuansheng Ni, Wang Zhu, Ziyan Jiang, Bohan Lyu, Dongfu Jiang, Xuan He, Yuan Liu, Hexiang Hu, Xiang Yue, Wenhu Chen
2024	J	`jnl`	TLDR: Token-Level Detective Reward Model for Large Vision Language Models. CoRR Deqing Fu, Tong Xiao, Rui Wang, Wang Zhu, Pengchuan Zhang, Guan Pang, Robin Jia, Lawrence Chen
2023	A*	`conf`	Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering. EMNLP Wang Zhu, Jesse Thomason, Robin Jia
2023	J	`jnl`	Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering. CoRR Wang Zhu, Jesse Thomason, Robin Jia
2023	J	`jnl`	Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions? CoRR Wang Zhu, Ishika Singh, Yuan Huang, Robin Jia, Jesse Thomason
2023	J	`jnl`	Efficient End-to-End Visual Document Understanding with Rationale Distillation. CoRR Wang Zhu, Alekh Agarwal, Mandar Joshi, Robin Jia, Jesse Thomason, Kristina Toutanova
2023	A*	`conf`	Iterative Vision-and-Language Navigation. CVPR Jacob Krantz, Shurjo Banerjee, Wang Zhu, Jason J. Corso, Peter Anderson, Stefan Lee, Jesse Thomason
2022	—	`conf`	Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems. EMNLP (Findings) Wang Zhu, Jesse Thomason, Robin Jia
2022	J	`jnl`	Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems. CoRR Wang Zhu, Jesse Thomason, Robin Jia
2022	J	`jnl`	Iterative Vision-and-Language Navigation. CoRR Jacob Krantz, Shurjo Banerjee, Wang Zhu, Jason J. Corso, Peter Anderson, Stefan Lee, Jesse Thomason
2022	A*	`conf`	Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning. NeurIPS Yejia Liu, Wang Zhu, Shaolei Ren
2022	J	`jnl`	Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning. CoRR Yejia Liu, Wang Zhu, Shaolei Ren
2021	J	`jnl`	Learning to Generalize Compositionally by Transferring Across Semantic Parsing Tasks. CoRR Wang Zhu, Peter Shaw, Tal Linzen, Fei Sha
2020	A*	`conf`	BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. ACL Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
2020	J	`jnl`	BabyWalk: Going Farther in Vision-and-Language Navigation by Taking Baby Steps. CoRR Wang Zhu, Hexiang Hu, Jiacheng Chen, Zhiwei Deng, Vihan Jain, Eugene Ie, Fei Sha
2018	—	`conf`	Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL. MLSA@PKDD/ECML Guiliang Liu, Wang Zhu, Oliver Schulte
2018	—	`conf`	Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. ECML/PKDD (2) Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li
2018	J	`jnl`	Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees. CoRR Guiliang Liu, Oliver Schulte, Wang Zhu, Qingcan Li