Large Language Models | Jiangjie Chen

Past Meets Present: Creating Historical Analogy with Large Language Models

We focus on acquiring historical analogies using LLMs, proposing a self-reflection method to reduce hallucinations and stereotypes, showing that LLMs have strong potential in this task.

Nianqi Li, Siyu Yuan, Jiangjie Chen, Jiaqing Liang, Feng Wei, Zujie Liang, Deqing Yang, Yanghua Xiao

Past Meets Present: Creating Historical Analogy with Large Language Models

TravelAgent: An AI Assistant for Personalized Travel Planning

We introduce TravelAgent, an LLM-powered travel planning system that generates rational, comprehensive, and personalized itineraries through four modules, demonstrating effectiveness in dynamic scenarios.

Aili Chen, Xuyang Ge, Ziquan Fu, Yanghua Xiao, Jiangjie Chen

How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?

We study how LLMs handle irrelevant information and find they struggle with content that is semantically related but ultimately not pertinent, highlighting the limitations of current systems in filtering out such distractions.

Siye Wu, Jian Xie, Jiangjie Chen, Tinghui Zhu, Kai Zhang, Yanghua Xiao

DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?

We introduce DetectBench, a benchmark for testing LLMs’ evidence detection in long contexts, and demonstrates that while existing LLMs lag behind human performance, the proposed Detective Reasoning Prompt and Finetuning methods can significantly improve their evidence detection and reasoning capabilities.

Zhouhong Gu, Lin Zhang, Xiaoxuan Zhu, Jiangjie Chen, Wenhao Huang, Yikai Zhang, Shusen Wang, Zheyu Ye, Yan Gao, Hongwei Feng, Yanghua Xiao

DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?

Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works

We propose evaluating large language models’ character understanding through character profiling, using the CroSS dataset and showing promising results for role-playing agent development.

Xinfeng Yuan, Siyu Yuan, Yuhan Cui, Tianhe Lin, Xintao Wang, Rui Xu, Jiangjie Chen, Deqing Yang

Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works

From Persona to Personalization: A Survey on Role-Playing Language Agents

This paper surveys Role-Playing Language Agents (RPLAs) by categorizing personas, discussing their development, and examining their applications, challenges, and future directions.

Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan, Yikai Zhang, Wei Shi, Jian Xie, Shuang Li, Ruihan Yang, Tinghui Zhu, Aili Chen, Nianqi Li, Lida Chen, Caiyu Hu, Siye Wu, Scott Ren, Ziquan Fu, Yanghua Xiao

From Persona to Personalization: A Survey on Role-Playing Language Agents

Character is Destiny: Can Large Language Models Simulate Persona-Driven Decisions in Role-Playing?

We evaluate the potential of LLMs to make decisions as literary characters, using a new dataset and improved method that enhances decision-making accuracy, with future work and resources to be shared publicly.

Rui Xu, Xintao Wang, Jiangjie Chen, Siyu Yuan, Xinfeng Yuan, Jiaqing Liang, Zulong Chen, Xiaoqing Dong, Yanghua Xiao

Character is Destiny: Can Large Language Models Simulate Persona-Driven Decisions in Role-Playing?

SurveyAgent: A Conversational System for Personalized and Efficient Research Survey

We propose a novel conversational AI system that enhances researchers’ literature review processes by providing personalized knowledge management, literature recommendations, and query answering through a unified platform.

Xintao Wang, Jiangjie Chen, Nianqi Li, Lida Chen, Xinfeng Yuan, Wei Shi, Xuyang Ge, Rui Xu, Yanghua Xiao

SurveyAgent: A Conversational System for Personalized and Efficient Research Survey

Agent Group Chat: An Interactive Group Chat Simulacra For Better Eliciting Collective Emergent Behavior

We propose a simulation to study language’s influence on collective behavior by having agents engage in free chat within various narrative scenarios, with findings suggesting that greater information exchange promotes more orderly and meaningful emergent behaviors.

Zhouhong Gu, Xiaoxuan Zhu, Haoran Guo, Lin Zhang, Yin Cai, Hao Shen, Jiangjie Chen, Zheyu Ye, Yifei Dai, Yan Gao, Yao Hu, Hongwei Feng, Yanghua Xiao

Agent Group Chat: An Interactive Group Chat Simulacra For Better Eliciting Collective Emergent Behavior

TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation

TimeArena enhances LLMs with temporal dynamics for better multitasking, showing advanced models like GPT-4 still trail behind human temporal awareness.

Yikai Zhang, Siyu Yuan, Caiyu Hu, Kyle Richardson, Yanghua Xiao, Jiangjie Chen

TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation