4 citations · 6 across the 5 of their papers we have counts for
5 papers
Entropy-Based Decoding for Retrieval-Augmented Large Language Models
Zexuan Qiu, Zijing Ou, Bin Wu +3
Augmenting Large Language Models (LLMs) with retrieved external knowledge has proven effective for improving the factual accuracy of generated responses. Despite their success, ret…
SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation
Minda Hu, Licheng Zong, Hongru Wang +6
Large Language Models (LLMs) have shown great potential in the biomedical domain with the advancement of retrieval-augmented generation (RAG). However, existing retrieval-augmented…
An Entropy-based Text Watermarking Detection Method
Yijian Lu, Aiwei Liu, Dianzhi Yu +2
Text watermarking algorithms for large language models (LLMs) can effectively identify machine-generated texts by embedding and detecting hidden features in the text. Although the…
CLongEval: A Chinese Benchmark for Evaluating Long-Context Large Language Models
Zexuan Qiu, Jingjing Li, Shijue Huang +3
Developing Large Language Models (LLMs) with robust long-context capabilities has been the recent research focus, resulting in the emergence of long-context LLMs proficient in Chin…
A Survey of Text Watermarking in the Era of Large Language Models
Aiwei Liu, Leyi Pan, Yijian Lu +7
Text watermarking algorithms are crucial for protecting the copyright of textual content. Historically, their capabilities and application scenarios were limited. However, recent a…