MTMS: Multi-teacher Multi-stage Knowledge Distillation for Reasoning-Based Machine Reading Comprehension-Reference-Cited by-同舟云学术

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MTMS: Multi-teacher Multi-stage Knowledge Distillation for Reasoning-Based Machine Reading Comprehension

Published:2024-07-10 Issue: Volume: Page:1995-2005
ISSN:
Container-title:Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Author:

Zhao Zhuo¹^ORCID,Xie Zhiwen²^ORCID,Zhou Guangyou²^ORCID,Huang Jimmy Xiangji³^ORCID

Affiliation:

1. Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, China, Hubei, China

2. Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning & School of Computer, Central China Normal University, Wuhan, Hubei, China

3. Information Retrieval and Knowledge Management Research Lab, York University, Toronto, Ontario, Canada

Funder

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626772.3657824

Reference53 articles.

1. Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877--1901.

2. Graph Transformer for Graph-to-Sequence Learning

3. Prior Gradient Mask Guided Pruning-Aware Fine-Tuning

4. Gentle Teaching Assistant Model For Improved Accuracy In Question-Answering

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