RRAML: Reinforced Retrieval Augmented Machine Learning

24 July 2023

Papers citing "RRAML: Reinforced Retrieval Augmented Machine Learning"

9 / 9 papers shown

Title
Leveraging LLMs for Utility-Focused Annotation: Reducing Manual Effort for Retrieval and RAG Hengran Zhang Minghao Tang Keping Bi J. Guo Shihao Liu Daiting Shi Dawei Yin Xueqi Cheng 19 0 0 07 Apr 2025
Exploring the Effectiveness of Multi-stage Fine-tuning for Cross-encoder Re-rankers Francesca Pezzuti Sean MacAvaney Nicola Tonellotto 31 0 0 28 Mar 2025
Oreo: A Plug-in Context Reconstructor to Enhance Retrieval-Augmented Generation Sha Li Naren Ramakrishnan RALM KELM 154 1 0 18 Feb 2025
The Power of Noise: Redefining Retrieval for RAG Systems Florin Cuconasu Giovanni Trappolini F. Siciliano Simone Filice Cesare Campagnano Y. Maarek Nicola Tonellotto Fabrizio Silvestri RALM 47 144 0 26 Jan 2024
Bridging the Preference Gap between Retrievers and LLMs Zixuan Ke Weize Kong Cheng-rong Li Mingyang Zhang Qiaozhu Mei Michael Bendersky RALM 28 29 0 13 Jan 2024
Multimodal Neural Databases Giovanni Trappolini Andrea Santilli Emanuele Rodolà A. Halevy Fabrizio Silvestri 47 10 0 02 May 2023
Factual and Informative Review Generation for Explainable Recommendation Zhouhang Xie Sameer Singh Julian McAuley Bodhisattwa Prasad Majumder 44 26 0 12 Sep 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 279 1,124 0 18 Apr 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,848 0 18 Apr 2021