359 citations · 763 across the 41 of their papers we have counts for
41 papers
RWGBench: Evaluating Scholarly Positioning in Related Work Generation
Anzhe Xie, Weihang Su, Jiaxin Mao +4
Large language models have shown strong fluency in scientific writing, yet the evaluation of related work generation (RWG) remains limited. Existing RWG evaluations largely inherit…
SelfRACG: Enabling LLMs to Self-Express and Retrieve for Code Generation
Qian Dong, Jia Chen, Qingyao Ai +6
Existing retrieval-augmented code generation (RACG) methods typically use an external retrieval module to fetch semantically similar code snippets used for generating subsequent fr…
Augmenting Multi-Agent Communication with State Delta Trajectory
Yichen Tang, Weihang Su, Yujia Zhou +4
Multi-agent techniques such as role playing or multi-turn debates have been shown to be effective in improving the performance of large language models (LLMs) in downstream tasks.…
Evaluating Intelligence via Trial and Error
Jingtao Zhan, Jiahao Zhao, Jiayu Li +7
Intelligence is a crucial trait for species to find solutions within a limited number of trial-and-error attempts. Building on this idea, we introduce Survival Game as a framework…
Auto-PRE: An Automatic and Cost-Efficient Peer-Review Framework for Language Generation Evaluation
Junjie Chen, Weihang Su, Zhumin Chu +9
The rapid development of large language models (LLMs) has highlighted the need for efficient and reliable methods to evaluate their performance. Traditional evaluation methods ofte…
LeKUBE: A Legal Knowledge Update BEnchmark
Changyue Wang, Weihang Su, Hu Yiran +6
Recent advances in Large Language Models (LLMs) have significantly shaped the applications of AI in multiple fields, including the studies of legal intelligence. Trained on extensi…