5 papers
ReMindRAG: Low-Cost LLM-Guided Knowledge Graph Traversal for Efficient RAG
Yikuan Hu, Jifeng Zhu, Lanrui Tang +1
Knowledge graphs (KGs), with their structured representation capabilities, offer promising avenue for enhancing Retrieval Augmented Generation (RAG) systems, leading to the develop…
CANDY: Benchmarking LLMs' Limitations and Assistive Potential in Chinese Misinformation Fact-Checking
Ruiling Guo, Xinwei Yang, Chen Huang +2
The effectiveness of large language models (LLMs) to fact-check misinformation remains uncertain, despite their growing use. To this end, we present CANDY, a benchmark designed to…
Quantifying LLM Biases Across Instruction Boundary in Mixed Question Forms
Zipeng Ling, Shuliang Liu, Yuehao Tang +8
Large Language Models (LLMs) annotated datasets are widely used nowadays, however, large-scale annotations often show biases in low-quality datasets. For example, Multiple-Choice Q…
LLM Abstention Can Be a Prompt Artifact, in Addition to Genuine Uncertainty
Zipeng Ling, Shuliang Liu, Yuehao Tang +8
Large Language Models (LLMs) are increasingly trained to abstain from answering questions they are unsure about. However, this ability is often misapplied: in real-world applicatio…
Generating GitHub Repository Descriptions: A Comparison of Manual and Automated Approaches
Jazlyn Hellman, Eunbee Jang, Christoph Treude +2
Given the vast number of repositories hosted on GitHub, project discovery and retrieval have become increasingly important for GitHub users. Repository descriptions serve as one of…