Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models

31 May 2024

Papers citing "Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models"

6 / 6 papers shown

Title
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey Aoran Gan Hao Yu Kai Zhang Qi Liu Wenyu Yan Zhenya Huang Shiwei Tong Guoping Hu RALM 3DV 36 0 0 21 Apr 2025
E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning Zihan Liao Jun Wang Hang Yu Lingxiao Wei Jianguo Li Jun Wang Wei Zhang 16 2 0 10 Sep 2024
Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection Akari Asai Zeqiu Wu Yizhong Wang Avirup Sil Hannaneh Hajishirzi RALM 138 600 0 17 Oct 2023
Generate rather than Retrieve: Large Language Models are Strong Context Generators W. Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng Meng-Long Jiang RALM AIMat 205 318 0 21 Sep 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Teaching language models to support answers with verified quotes Jacob Menick Maja Trebacz Vladimir Mikulik John Aslanides Francis Song ... Mia Glaese Susannah Young Lucy Campbell-Gillingham G. Irving Nat McAleese ELM RALM 213 204 0 21 Mar 2022