4 papers
The Score Granularity Gap in Black-Box LLM Classification: A Comparative Study of Confidence Constructions
Ao Sun, Tian Sun, Jiaxing Geng
Large language models (LLMs) are increasingly deployed as black-box classifiers in pipelines that automate confident decisions and route uncertain ones to human review. Such select…
Reasoning in Trees: Improving Retrieval-Augmented Generation for Multi-Hop Question Answering
Yuling Shi, Maolin Sun, Zijun Liu +4
Retrieval-Augmented Generation (RAG) has demonstrated significant effectiveness in enhancing large language models (LLMs) for complex multi-hop question answering (QA). For multi-h…
AttentionRAG: Attention-Guided Context Pruning in Retrieval-Augmented Generation
Yixiong Fang, Tianran Sun, Yuling Shi +1
While RAG demonstrates remarkable capabilities in LLM applications, its effectiveness is hindered by the ever-increasing length of retrieved contexts, which introduces information…
LastingBench: Defend Benchmarks Against Knowledge Leakage
Yixiong Fang, Tianran Sun, Yuling Shi +2
The increasing complexity of large language models (LLMs) raises concerns about their ability to "cheat" on standard Question Answering (QA) benchmarks by memorizing task-specific…