2 citations · 3 across the 9 of their papers we have counts for
5 papers · 2 filters
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…
Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan Commentary
Meiling Tao, Xuechen Liang, Xinyuan Song +4
Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary f…
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…