1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
LMEB: Long-horizon Memory Embedding Benchmark
Xinping Zhao, Xinshuo Hu, Jiaxin Xu +9
Embedding models are increasingly used as retrievers in memory-augmented systems, but are typically evaluated on traditional passage retrieval benchmarks. It remains unclear whethe…
Learning to Extract Rational Evidence via Reinforcement Learning for Retrieval-Augmented Generation
Xinping Zhao, Shouzheng Huang, Yan Zhong +4
Retrieval-Augmented Generation (RAG) effectively improves the accuracy of Large Language Models (LLMs). However, retrieval noises significantly undermine the quality of LLMs' gener…
SEER: Self-Aligned Evidence Extraction for Retrieval-Augmented Generation
Xinping Zhao, Dongfang Li, Yan Zhong +4
Recent studies in Retrieval-Augmented Generation (RAG) have investigated extracting evidence from retrieved passages to reduce computational costs and enhance the final RAG perform…
Towards Detecting LLMs Hallucination via Markov Chain-based Multi-agent Debate Framework
Xiaoxi Sun, Jinpeng Li, Yan Zhong +2
The advent of large language models (LLMs) has facilitated the development of natural language text generation. It also poses unprecedented challenges, with content hallucination e…