2 citations · 3 across the 12 of their papers we have counts for
14 papers
Through the Lens of Character: Resolving Modality-Role Interference in Multimodal Role-Playing Agent
Yihong Tang, Kehai Chen, Xuefeng Bai +1
The advancement of Multimodal Large Language Models (MLLMs) has expanded Role-Playing Agents (RPAs) into visually grounded environments. However, human vision is inherently subject…
Character-R1: Enhancing Role-Aware Reasoning in Role-Playing Agents via RLVR
Yihong Tang, Kehai Chen, Xuefeng Bai +4
Current role-playing agents (RPAs) are typically constructed by imitating surface-level behaviors, but this approach lacks internal cognitive consistency, often causing out-of-char…
Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agents
Yihong Tang, Kehai Chen, Liang Yue +11
With the rise of large language models (LLMs), LLM agents capable of autonomous reasoning, planning, and executing complex tasks have become a frontier in artificial intelligence.…
MASTER: Enhancing Large Language Model via Multi-Agent Simulated Teaching
Liang Yue, Yihong Tang, Kehai Chen +2
Instruction fine-tuning is crucial in NLP tasks, enhancing pretrained models' instruction-following capabilities and task-specific performance. However, obtaining high-quality fine…
ORPP: Self-Optimizing Role-playing Prompts to Enhance Language Model Capabilities
Yifan Duan, Yihong Tang, Kehai Chen +2
High-quality prompts are crucial for eliciting outstanding performance from large language models (LLMs) on complex tasks. Existing research has explored model-driven strategies fo…
Thinking in Character: Advancing Role-Playing Agents with Role-Aware Reasoning
Yihong Tang, Kehai Chen, Muyun Yang +4
The advancement of Large Language Models (LLMs) has spurred significant interest in Role-Playing Agents (RPAs) for applications such as emotional companionship and virtual interact…
The Rise of Darkness: Safety-Utility Trade-Offs in Role-Playing Dialogue Agents
Yihong Tang, Kehai Chen, Xuefeng Bai +4
Large Language Models (LLMs) have made remarkable advances in role-playing dialogue agents, demonstrating their utility in character simulations. However, it remains challenging fo…
The Power of Personality: A Human Simulation Perspective to Investigate Large Language Model Agents
Yifan Duan, Yihong Tang, Xuefeng Bai +3
Large language models (LLMs) excel in both closed tasks (including problem-solving, and code generation) and open tasks (including creative writing), yet existing explanations for…
ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning
Yihong Tang, Jiao Ou, Che Liu +3
Role-playing is an emerging application in the field of Human-Computer Interaction (HCI), primarily implemented through the alignment training of a large language model (LLM) with…
RoleBreak: Character Hallucination as a Jailbreak Attack in Role-Playing Systems
Yihong Tang, Bo Wang, Xu Wang +5
Role-playing systems powered by large language models (LLMs) have become increasingly influential in emotional communication applications. However, these systems are susceptible to…
MORPHEUS: Modeling Role from Personalized Dialogue History by Exploring and Utilizing Latent Space
Yihong Tang, Bo Wang, Dongming Zhao +4
Personalized Dialogue Generation (PDG) aims to create coherent responses according to roles or personas. Traditional PDG relies on external role data, which can be scarce and raise…
Enhancing Role-playing Systems through Aggressive Queries: Evaluation and Improvement
Yihong Tang, Jiao Ou, Che Liu +3
The advent of Large Language Models (LLMs) has propelled dialogue generation into new realms, particularly in the field of role-playing systems (RPSs). While enhanced with ordinary…
DialogBench: Evaluating LLMs as Human-like Dialogue Systems
Jiao Ou, Junda Lu, Che Liu +4
Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue capabilities by leveraging instruction tuning, which refreshes human impressions of dialogue sys…
Enhancing Personalized Dialogue Generation with Contrastive Latent Variables: Combining Sparse and Dense Persona
Yihong Tang, Bo Wang, Miao Fang +4
The personalized dialogue explores the consistent relationship between dialogue generation and personality. Existing personalized dialogue agents model persona profiles from three…