Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers

2 November 2023

Papers citing "Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers"

8 / 8 papers shown

Title
RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models Can Jin Hongwu Peng Anxiang Zhang Nuo Chen Jiahui Zhao ... K. Li Shuya Feng Kai Zhong Caiwen Ding Dimitris N. Metaxas 99 2 0 02 Feb 2025
TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy Yiqun Chen Qi Liu Yi Zhang Weiwei Sun Daiting Shi Jiaxin Mao Dawei Yin Jiaxin Mao Dawei Yin 33 6 0 17 Jun 2024
Towards Completeness-Oriented Tool Retrieval for Large Language Models Changle Qu Sunhao Dai Xiaochi Wei Hengyi Cai Shuaiqiang Wang Dawei Yin Jun Xu Jirong Wen KELM 22 7 0 25 May 2024
Zero-Shot Listwise Document Reranking with a Large Language Model Xueguang Ma Xinyu Crystina Zhang Ronak Pradeep Jimmy J. Lin 65 50 0 03 May 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 221 321 0 21 Sep 2022
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 229 961 0 17 Apr 2021
Overview of the TREC 2020 deep learning track Nick Craswell Bhaskar Mitra Emine Yilmaz Daniel Fernando Campos 54 368 0 15 Feb 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 243 1,815 0 17 Sep 2019