Multitask Fine-Tuning for Passage Re-Ranking Using BM25 and Pseudo Relevance Feedback-Reference-Cited by-同舟云学术

Multitask Fine-Tuning for Passage Re-Ranking Using BM25 and Pseudo Relevance Feedback

Published:2022 Issue: Volume:10 Page:54254-54262
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Kim Meoungjun¹^ORCID,Ko Youngjoong²^ORCID

Affiliation:

1. Department of Artificial Intelligence, Sungkyunkwan University, Suwon, South Korea

2. Department of Computer Science and Engineering, Sungkyunkwan University, Suwon, South Korea

Funder

Institute of Information & Communications Technology Planning & Evaluation (IITP) Grant funded by the Korea Government (MSIT)

National Research Foundation of Korea (NRF) Grant funded by the Korea Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09779725.pdf?arnumber=9779725

Reference28 articles.

1. BERT: Pre-training of deep bidirectional transformers for language understanding;devlin;Proc Conf North Amer Chapter Assoc Comput Linguistics Hum Lang Technol,2019

2. RoBERTa: A robustly optimized BERT pretraining approach;liu;arXiv 1907 11692,2019

3. Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks

4. Some Simple Effective Approximations to the 2-Poisson Model for Probabilistic Weighted Retrieval

5. The Effect of Adding Relevance Information in a Relevance Feedback Environment

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