activity
20242026
most citedFrom Persona to Personalization: A Survey on Role-Playing Language Agents

14 citations · 21 across the 9 of their papers we have counts for

collaborators

14 papers

cs.AI2026

Beyond Skill Evolution: Self-Evolving Context Management Policies for Long-Horizon Agent Harnesses

Weiyuan Li, Jinghan Xu, Aili Chen +4

Harness evolution improves LLM agents by learning from execution trajectories, but existing experience- and skill-based methods are less effective on long-horizon tasks. As interac…

cs.AI2026

OSPD: On-Policy Self-Distillation for Persona-Consistent Dialogue

Rui Xu, Yikai Zhang, Aili Chen +3

Maintaining persona consistency across multi-turn dialogues remains a core challenge for role-playing language models. Off-policy distillation from external teachers incurs distrib…

cs.CL2026

SocialRL: Refining LLMs' Social Intelligence through Multi-turn Reinforcement Learning and Reward Design

Jianing Wang, Xintao Wang, Aili Chen +7

Social intelligence enables agents to read social context, infer intent, and adapt over sustained dialogue. As language models become autonomous collaborators, it is central to bui…

cs.CL2026

From AI Assistant to AI Scientist: Autonomous Discovery of LLM-RL Algorithms with LLM Agents

Sirui Xia, Yikai Zhang, Aili Chen +3

Discovering improved policy optimization algorithms for language models remains a costly manual process requiring repeated mechanism-level modification and validation. Unlike simpl…

cs.LG2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

ARM: Adaptive Reasoning Model

Siye Wu, Jian Xie, Yikai Zhang +4

While large reasoning models demonstrate strong performance on complex tasks, they lack the ability to adjust reasoning token usage based on task difficulty. This often leads to th…

cs.CL2025

DEEPER Insight into Your User: Directed Persona Refinement for Dynamic Persona Modeling

Aili Chen, Chengyu Du, Jiangjie Chen +6

To advance personalized applications such as recommendation systems and user behavior prediction, recent research increasingly adopts large language models (LLMs) for human -readab…

cs.CL2024

Think Thrice Before You Act: Progressive Thought Refinement in Large Language Models

Chengyu Du, Jinyi Han, Yizhou Ying +9

Recent advancements in large language models (LLMs) have demonstrated that progressive refinement, rather than providing a single answer, results in more accurate and thoughtful ou…

cs.AI2024★ 5 cited

TravelAgent: An AI Assistant for Personalized Travel Planning

Aili Chen, Xuyang Ge, Ziquan Fu +2

As global tourism expands and artificial intelligence technology advances, intelligent travel planning services have emerged as a significant research focus. Within dynamic real-wo…

cs.CL2024

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…

cs.CL2024★ 2 cited

SelfGoal: Your Language Agents Already Know How to Achieve High-level Goals

Ruihan Yang, Jiangjie Chen, Yikai Zhang +5

Language agents powered by large language models (LLMs) are increasingly valuable as decision-making tools in domains such as gaming and programming. However, these agents often fa…

cs.CL2024★ 14 cited

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…