activity
20242026
collaborators

5 papers

cs.SE2026

MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms

Yibo Wang, Congying Xia, Wenting Zhao +5

Unit test generation has become a promising and important Large Language Model (LLM) use case. However, existing evaluation benchmarks for LLM unit test generation focus on functio…

cs.CL2025

Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs

Yangning Li, Weizhi Zhang, Yuyao Yang +17

Retrieval-Augmented Generation (RAG) lifts the factuality of Large Language Models (LLMs) by injecting external knowledge, yet it falls short on problems that demand multi-step inf…

cs.CR2025

MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection

Liancheng Fang, Aiwei Liu, Henry Peng Zou +4

We introduce MUSE, a watermarking algorithm for tabular generative models. Previous approaches typically leverage DDIM invertibility to watermark tabular diffusion models, but tabu…

cs.CL2024

Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoning

Tao Zhang, Ning Yan, Masood Mortazavi +3

Large language models (LLMs) pre-trained on massive corpora have demonstrated impressive few-shot learning capability on many NLP tasks. Recasting an NLP task into a text-to-text g…

cs.CL2024

LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing

Jiangshu Du, Yibo Wang, Wenting Zhao +37

This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and ques…