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20232026
most citedExploring Large Language Models for Communication Games: An Empirical Study on Werewolf

23 citations · 26 across the 17 of their papers we have counts for

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cs.CL2025

Thinking with Visual Abstract: Enhancing Multimodal Reasoning via Visual Abstraction

Dairu Liu, Ziyue Wang, Minyuan Ruan +4

Images usually convey richer detail than text, but often include redundant information, which potentially downgrades multimodal reasoning performance. When faced with lengthy or co…

cs.CL2025

Perspective Transition of Large Language Models for Solving Subjective Tasks

Xiaolong Wang, Yuanchi Zhang, Ziyue Wang +5

Large language models (LLMs) have revolutionized the field of natural language processing, enabling remarkable progress in various tasks. Different from objective tasks such as com…

cs.CL2024

Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models

Xiaolong Wang, Yile Wang, Yuanchi Zhang +4

Large Language Models (LLMs) have achieved remarkable performance in objective tasks such as open-domain question answering and mathematical reasoning, which can often be solved th…

cs.CL2024

Browse and Concentrate: Comprehending Multimodal Content via prior-LLM Context Fusion

Ziyue Wang, Chi Chen, Yiqi Zhu +7

With the bloom of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) that incorporate LLMs with pre-trained vision models have recently demonstrated impressive…

cs.CL2023★ 23 cited

Exploring Large Language Models for Communication Games: An Empirical Study on Werewolf

Yuzhuang Xu, Shuo Wang, Peng Li +4

Communication games, which we refer to as incomplete information games that heavily depend on natural language communication, hold significant research value in fields such as econ…