14 citations · 46 across the 26 of their papers we have counts for
29 papers
DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph
Zhihao Xiao, Mengting Li, Xintao Wang +4
Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accurate role-playing of establish…
HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing
Chengyu Du, Xintao Wang, Aili Chen +11
LLM role-playing, i.e., using LLMs to simulate specific personas, has emerged as a key capability in various applications, such as companionship, content creation and digital games…
HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns
Xintao Wang, Jian Yang, Weiyuan Li +8
Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Langu…
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…
PERSONA: A Reproducible Testbed for Pluralistic Alignment
Louis Castricato, Nathan Lile, Rafael Rafailov +2
The rapid advancement of language models (LMs) necessitates robust alignment with diverse user values. However, current preference optimization approaches often fail to capture the…
MINDECHO: Role-Playing Language Agents for Key Opinion Leaders
Rui Xu, Dakuan Lu, Xiaoyu Tan +5
Large language models~(LLMs) have demonstrated impressive performance in various applications, among which role-playing language agents (RPLAs) have engaged a broad user base. Now,…
Ground Every Sentence: Improving Retrieval-Augmented LLMs with Interleaved Reference-Claim Generation
Sirui Xia, Xintao Wang, Jiaqing Liang +5
Retrieval-Augmented Generation (RAG) has been widely adopted to enhance Large Language Models (LLMs) in knowledge-intensive tasks. To enhance credibility and verifiability in RAG s…
Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs
Yifei Zhang, Xintao Wang, Jiaqing Liang +3
Large Language Models (LLMs) have exhibited impressive proficiency in various natural language processing (NLP) tasks, which involve increasingly complex reasoning. Knowledge reaso…
Light Up the Shadows: Enhance Long-Tailed Entity Grounding with Concept-Guided Vision-Language Models
Yikai Zhang, Qianyu He, Xintao Wang +3
Multi-Modal Knowledge Graphs (MMKGs) have proven valuable for various downstream tasks. However, scaling them up is challenging because building large-scale MMKGs often introduces…
Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals
Lida Chen, Zujie Liang, Xintao Wang +7
Large language models (LLMs) have achieved great success, but their occasional content fabrication, or hallucination, limits their practical application. Hallucination arises becau…
Capturing Minds, Not Just Words: Enhancing Role-Playing Language Models with Personality-Indicative Data
Yiting Ran, Xintao Wang, Rui Xu +4
Role-playing agents (RPA) have been a popular application area for large language models (LLMs), attracting significant interest from both industry and academia.While existing RPAs…
SurveyAgent: A Conversational System for Personalized and Efficient Research Survey
Xintao Wang, Jiangjie Chen, Nianqi Li +6
In the rapidly advancing research fields such as AI, managing and staying abreast of the latest scientific literature has become a significant challenge for researchers. Although p…
From Persona to Personalization: A Survey on Role-Playing Language Agents
Jiangjie Chen, Xintao Wang, Rui Xu +15
Recent advancements in large language models (LLMs) have significantly boosted the rise of Role-Playing Language Agents (RPLAs), i.e., specialized AI systems designed to simulate a…
Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works
Xinfeng Yuan, Siyu Yuan, Yuhan Cui +5
Large language models (LLMs) have demonstrated impressive performance and spurred numerous AI applications, in which role-playing agents (RPAs) are particularly popular, especially…
Character is Destiny: Can Role-Playing Language Agents Make Persona-Driven Decisions?
Rui Xu, Xintao Wang, Jiangjie Chen +6
Can Large Language Models (LLMs) simulate humans in making important decisions? Recent research has unveiled the potential of using LLMs to develop role-playing language agents (RP…
ConcEPT: Concept-Enhanced Pre-Training for Language Models
Xintao Wang, Zhouhong Gu, Jiaqing Liang +3
Pre-trained language models (PLMs) have been prevailing in state-of-the-art methods for natural language processing, and knowledge-enhanced PLMs are further proposed to promote mod…
Source Prompt: Coordinated Pre-training of Language Models on Diverse Corpora from Multiple Sources
Yipei Xu, Dakuan Lu, Jiaqing Liang +7
Pre-trained language models (PLMs) have established the new paradigm in the field of NLP. For more powerful PLMs, one of the most popular and successful way is to continuously scal…