Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning
Strategies are not Better than Random Selection

Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection

12 September 2023

Sophia Althammer

Guido Zuccon

Sebastian Hofstatter

Papers citing "Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection"

11 / 11 papers shown

Title
GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise Moseli Motsóehli Kyungim Baek 26 1 0 08 Nov 2024
Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations Ji Xin Chenyan Xiong A. Srinivasan Ankita Sharma Damien Jose Paul N. Bennett VLM 78 41 0 14 Oct 2021
SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval Thibault Formal Carlos Lassance Benjamin Piwowarski S. Clinchant 194 186 0 21 Sep 2021
Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review Eugene Yang Sean MacAvaney D. Lewis O. Frieder 82 28 0 03 May 2021
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 231 966 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
Cold-start Active Learning through Self-supervised Language Modeling Michelle Yuan Hsuan-Tien Lin Jordan L. Boyd-Graber 106 180 0 19 Oct 2020
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks Nandan Thakur Nils Reimers Johannes Daxenberger Iryna Gurevych 202 241 0 16 Oct 2020
Pretrained Transformers for Text Ranking: BERT and Beyond Jimmy J. Lin Rodrigo Nogueira Andrew Yates VLM 219 608 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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 279 9,136 0 06 Jun 2015