A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models

4 March 2021

Papers citing "A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models"

8 / 8 papers shown

Title
Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection Sophia Althammer Guido Zuccon Sebastian Hofstatter Suzan Verberne Allan Hanbury 34 4 0 12 Sep 2023
InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers Leonid Boytsov Preksha Patel Vivek Sourabh Riddhi Nisar Sayan Kundu R. Ramanathan Eric Nyberg 26 19 0 08 Jan 2023
From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective Thibault Formal Carlos Lassance Benjamin Piwowarski S. Clinchant VLM 26 138 0 10 May 2022
Sequential Attention Module for Natural Language Processing Mengyuan Zhou Jian Ma Haiqing Yang Lian-Xin Jiang Yang Mo AI4TS 19 2 0 07 Sep 2021
Adversarial Training Helps Transfer Learning via Better Representations Zhun Deng Linjun Zhang Kailas Vodrahalli Kenji Kawaguchi James Zou GAN 36 52 0 18 Jun 2021
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 231 971 0 17 Apr 2021
Pretrained Transformers for Text Ranking: BERT and Beyond Jimmy J. Lin Rodrigo Nogueira Andrew Yates VLM 239 611 0 13 Oct 2020
Overview of the TREC 2019 deep learning track Nick Craswell Bhaskar Mitra Emine Yilmaz Daniel Fernando Campos E. Voorhees 180 465 0 17 Mar 2020