14 citations · 46 across the 26 of their papers we have counts for
8 papers · 1 filter
ORIGAMISPACE: Benchmarking Multimodal LLMs in Multi-Step Spatial Reasoning with Mathematical Constraints
Rui Xu, Dakuan Lu, Zicheng Zhao +5
Spatial reasoning is a key capability in the field of artificial intelligence, especially crucial in areas such as robotics, computer vision, and natural language understanding. Ho…
Curse of Knowledge: When Complex Evaluation Context Benefits yet Biases LLM Judges
Weiyuan Li, Xintao Wang, Siyu Yuan +5
As large language models (LLMs) grow more capable, they face increasingly diverse and complex tasks, making reliable evaluation challenging. The paradigm of LLMs as judges has emer…
ARIA: Training Language Agents with Intention-Driven Reward Aggregation
Ruihan Yang, Yikai Zhang, Aili Chen +5
Large language models (LLMs) have enabled agents to perform complex reasoning and decision-making through free-form language interactions. However, in open-ended language action en…
Can LLMs Learn to Map the World from Local Descriptions?
Sirui Xia, Aili Chen, Xintao Wang +4
Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in tasks such as code and mathematics. However, their potential to internalize structured spat…
BookWorld: From Novels to Interactive Agent Societies for Creative Story Generation
Yiting Ran, Xintao Wang, Tian Qiu +3
Recent advances in large language models (LLMs) have enabled social simulation through multi-agent systems. Prior efforts focus on agent societies created from scratch, assigning a…
Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents
Rui Xu, MingYu Wang, XinTao Wang +4
Recent advances in LLM-based role-playing language agents (RPLAs) have attracted broad attention in various applications. While chain-of-thought reasoning has shown importance in m…
PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention
Lida Chen, Dong Xu, Chenxin An +8
Large Language Models (LLMs) face efficiency bottlenecks due to the quadratic complexity of the attention mechanism when processing long contexts. Sparse attention methods offer a…
CoSER: A Comprehensive Literary Dataset and Framework for Training and Evaluating LLM Role-Playing and Persona Simulation
Xintao Wang, Heng Wang, Yifei Zhang +9
Role-playing language agents (RPLAs) have emerged as promising applications of large language models (LLMs). However, simulating established characters presents a challenging task…