Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated
Neural Text Retrievers

Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers

14 July 2022

Xiao Liu

Yuxiao Dong

Papers citing "Parameter-Efficient Prompt Tuning Makes Generalized and Calibrated Neural Text Retrievers"

8 / 8 papers shown

Title
Domain Adaptation of Multilingual Semantic Search -- Literature Review Anna Bringmann Anastasia Zhukova VLM 41 0 0 05 Feb 2024
BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrieval Shicheng Xu Liang Pang Huawei Shen Xueqi Cheng 16 11 0 18 May 2023
Parameter-Efficient Sparse Retrievers and Rerankers using Adapters Vaishali Pal Carlos Lassance Hervé Déjean S. Clinchant 135 3 0 23 Mar 2023
Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrieval Robert Litschko Ivan Vulić Goran Glavavs LRM 37 14 0 05 Apr 2022
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,858 0 18 Apr 2021
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 261 975 0 17 Apr 2021
OAG-BERT: Towards A Unified Backbone Language Model For Academic Knowledge Services Xiao Liu Da Yin Jingnan Zheng Xingjian Zhang Peng Zhang Hongxia Yang Yuxiao Dong Jie Tang VLM 40 30 0 03 Mar 2021
On the Calibration and Uncertainty of Neural Learning to Rank Models Gustavo Penha C. Hauff 184 30 0 12 Jan 2021