Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop
Reading Comprehension

Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension

12 June 2019

Joey Tianyi Zhou

Papers citing "Explore, Propose, and Assemble: An Interpretable Model for Multi-Hop Reading Comprehension"

10 / 10 papers shown

Title
Towards a Praxis for Intercultural Ethics in Explainable AI Chinasa T. Okolo 39 3 0 24 Apr 2023
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension Peng Gao Feng Gao Jiancheng Ni Yu Wang Fei-Yue Wang 22 2 0 19 Dec 2022
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches A. Mohammadi Reza Ramezani Ahmad Baraani 32 3 0 08 Dec 2022
METGEN: A Module-Based Entailment Tree Generation Framework for Answer Explanation Ruixin Hong Hongming Zhang Xintong Yu Changshui Zhang ReLM LRM 32 32 0 05 May 2022
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 17 44 0 20 Oct 2021
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference Jianguo Zhang Kazuma Hashimoto Wenhao Liu Chien-Sheng Wu Yao Wan Philip S. Yu R. Socher Caiming Xiong 14 92 0 25 Oct 2020
A Survey on Explainability in Machine Reading Comprehension Mokanarangan Thayaparan Marco Valentino André Freitas FaML 12 50 0 01 Oct 2020
Differentiable Reasoning over a Virtual Knowledge Base Bhuwan Dhingra Manzil Zaheer Vidhisha Balachandran Graham Neubig Ruslan Salakhutdinov William W. Cohen 18 88 0 25 Feb 2020
Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering Antoine Bosselut Ronan Le Bras Yejin Choi NAI 27 41 0 10 Nov 2019
R4C: A Benchmark for Evaluating RC Systems to Get the Right Answer for the Right Reason Naoya Inoue Pontus Stenetorp Kentaro Inui 28 59 0 10 Oct 2019