Large Language Models | Jiangjie Chen

SEGMENT+: Long Text Processing with Short-Context Language Models

We introduce SEGMENT+, a framework that enables LMs to efficiently handle extended inputs within limited context windows, improving performance in long-document tasks through structured notes and a filtering module.

Wei Shi, Shuang Li, Kerun Yu, Jinglei Chen, Zujie Liang, Xinhui Wu, Yuxi Qian, Feng Wei, Bo Zheng, Jiaqing Liang, Jiangjie Chen, Yanghua Xiao

SEGMENT+: Long Text Processing with Short-Context Language Models

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?

EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms

We introduce EvoAgent, a method using evolutionary algorithms to automatically expand expert agents into multi-agent systems, enhancing the task-solving capabilities of large language model-based agents without additional human design.

Siyu Yuan, Kaitao Song, Jiangjie Chen, Xu Tan, Dongsheng Li, Deqing Yang

EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms

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

We introduce SelfGoal, an automatic approach that enhances language agents’ capabilities to achieve high-level goals with limited instructions and delayed feedback by adaptively breaking down goals into practical subgoals.

Ruihan Yang, Jiangjie Chen, Yikai Zhang, Siyu Yuan, Aili Chen, Kyle Richardson, Yanghua Xiao, Deqing Yang

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

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?