2 citations · 4 across the 9 of their papers we have counts for
6 papers · 1 filter
MARS: Memory-Enhanced Agents with Reflective Self-improvement
Xuechen Liang, Meiling Tao, Yinghui Xia +8
Large language models (LLMs) have made significant advances in the field of natural language processing, but they still face challenges such as continuous decision-making, lack of…
Self-evolving Agents with reflective and memory-augmented abilities
Xuechen Liang, Yangfan He, Yinghui Xia +11
Large language models (LLMs) have made significant advances in the field of natural language processing, but they still face challenges such as continuous decision-making. In this…
LanguaShrink: Reducing Token Overhead with Psycholinguistics
Xuechen Liang, Meiling Tao, Yinghui Xia +3
As large language models (LLMs) improve their capabilities in handling complex tasks, the issues of computational cost and efficiency due to long prompts are becoming increasingly…
AICoderEval: Improving AI Domain Code Generation of Large Language Models
Yinghui Xia, Yuyan Chen, Tianyu Shi +2
Automated code generation is a pivotal capability of large language models (LLMs). However, assessing this capability in real-world scenarios remains challenging. Previous methods…
CMAT: A Multi-Agent Collaboration Tuning Framework for Enhancing Small Language Models
Xuechen Liang, Yangfan He, Meiling Tao +5
Open large language models (LLMs) have significantly advanced the field of natural language processing, showcasing impressive performance across various tasks.Despite the significa…
RoleCraft-GLM: Advancing Personalized Role-Playing in Large Language Models
Meiling Tao, Xuechen Liang, Tianyu Shi +2
This study presents RoleCraft-GLM, an innovative framework aimed at enhancing personalized role-playing with Large Language Models (LLMs). RoleCraft-GLM addresses the key issue of…