14 citations · 44 across the 19 of their papers we have counts for
22 papers
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…
DIVE: Scaling Diversity in Agentic Task Synthesis for Generalizable Tool Use
Aili Chen, Chi Zhang, Junteng Liu +11
Recent work synthesizes agentic tasks for post-training tool-using LLMs, yet robust generalization under shifts in tasks and toolsets remains an open challenge. We trace this britt…
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…
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…
Enhancing Language Agent Strategic Reasoning through Self-Play in Adversarial Games
Yikai Zhang, Ye Rong, Siyu Yuan +3
Existing language agents often encounter difficulties in dynamic adversarial games due to poor strategic reasoning. To mitigate this limitation, a promising approach is to allow ag…
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…
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…
MCiteBench: A Multimodal Benchmark for Generating Text with Citations
Caiyu Hu, Yikai Zhang, Tinghui Zhu +2
Multimodal Large Language Models (MLLMs) have advanced in integrating diverse modalities but frequently suffer from hallucination. A promising solution to mitigate this issue is to…
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…
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…
Revealing the Barriers of Language Agents in Planning
Jian Xie, Kexun Zhang, Jiangjie Chen +5
Autonomous planning has been an ongoing pursuit since the inception of artificial intelligence. Based on curated problem solvers, early planning agents could deliver precise soluti…
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…
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…
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…
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…
How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?
Siye Wu, Jian Xie, Jiangjie Chen +3
By leveraging the retrieval of information from external knowledge databases, Large Language Models (LLMs) exhibit enhanced capabilities for accomplishing many knowledge-intensive…
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation
Yikai Zhang, Siyu Yuan, Caiyu Hu +3
Despite remarkable advancements in emulating human-like behavior through Large Language Models (LLMs), current textual simulations do not adequately address the notion of time. To…
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick
Jiayi Fu, Xuandong Zhao, Ruihan Yang +3
Large language models (LLMs) excellently generate human-like text, but also raise concerns about misuse in fake news and academic dishonesty. Decoding-based watermark, particularly…
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Jian Xie, Kai Zhang, Jiangjie Chen +5
Planning has been part of the core pursuit for artificial intelligence since its conception, but earlier AI agents mostly focused on constrained settings because many of the cognit…
InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews
Xintao Wang, Yunze Xiao, Jen-tse Huang +10
Role-playing agents (RPAs), powered by large language models, have emerged as a flourishing field of applications. However, a key challenge lies in assessing whether RPAs accuratel…