QED: A Framework and Dataset for Explanations in Question Answering

8 September 2020

Livio Baldini Soares

Papers citing "QED: A Framework and Dataset for Explanations in Question Answering"

30 / 30 papers shown

Title
A kinetic-based regularization method for data science applications Abhisek Ganguly Alessandro Gabbana Vybhav Rao Sauro Succi Santosh Ansumali 120 1 0 06 Mar 2025
Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs Nicolas Boizard Kevin El Haddad C´eline Hudelot Pierre Colombo 134 17 0 28 Jan 2025
Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models Xiao Cui Mo Zhu Yulei Qin Liang Xie Wengang Zhou Haoyang Li 149 7 0 19 Dec 2024
PORT: Preference Optimization on Reasoning Traces Salem Lahlou Abdalgader Abubaker Hakim Hacid LRM 94 5 0 23 Jun 2024
WT5?! Training Text-to-Text Models to Explain their Predictions Sharan Narang Colin Raffel Katherine Lee Adam Roberts Noah Fiedel Karishma Malkan 64 201 0 30 Apr 2020
Towards Transparent and Explainable Attention Models Akash Kumar Mohankumar Preksha Nema Sharan Narasimhan Mitesh M. Khapra Balaji Vasan Srinivasan Balaraman Ravindran 72 102 0 29 Apr 2020
AmbigQA: Answering Ambiguous Open-domain Questions Sewon Min Julian Michael Hannaneh Hajishirzi Luke Zettlemoyer 105 316 0 22 Apr 2020
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness? Alon Jacovi Yoav Goldberg XAI 124 597 0 07 Apr 2020
Break It Down: A Question Understanding Benchmark Tomer Wolfson Mor Geva Ankit Gupta Matt Gardner Yoav Goldberg Daniel Deutch Jonathan Berant 75 188 0 31 Jan 2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 445 20,298 0 23 Oct 2019
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations Oana-Maria Camburu Brendan Shillingford Pasquale Minervini Thomas Lukasiewicz Phil Blunsom AAML GAN 71 97 0 07 Oct 2019
WIQA: A dataset for "What if..." reasoning over procedural text Niket Tandon Bhavana Dalvi Keisuke Sakaguchi Antoine Bosselut Peter Clark 63 101 0 10 Sep 2019
Attention is not not Explanation Sarah Wiegreffe Yuval Pinter XAI AAML FAtt 120 913 0 13 Aug 2019
SpanBERT: Improving Pre-training by Representing and Predicting Spans Mandar Joshi Danqi Chen Yinhan Liu Daniel S. Weld Luke Zettlemoyer Omer Levy 147 1,965 0 24 Jul 2019
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions Christopher Clark Kenton Lee Ming-Wei Chang Tom Kwiatkowski Michael Collins Kristina Toutanova 227 1,549 0 24 May 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 145 1,327 0 26 Feb 2019
A BERT Baseline for the Natural Questions Chris Alberti Kenton Lee Michael Collins ELM AI4MH 56 127 0 24 Jan 2019
Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions Upol Ehsan Pradyumna Tambwekar Larry Chan Brent Harrison Mark O. Riedl 97 243 0 11 Jan 2019
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 417 638 0 04 Dec 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,114 0 11 Oct 2018
HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering Zhilin Yang Peng Qi Saizheng Zhang Yoshua Bengio William W. Cohen Ruslan Salakhutdinov Christopher D. Manning RALM 182 2,655 0 25 Sep 2018
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts Matthew Lamm Arun Tejasvi Chaganty Christopher D. Manning Dan Jurafsky Percy Liang 39 24 0 07 Sep 2018
CoQA: A Conversational Question Answering Challenge Siva Reddy Danqi Chen Christopher D. Manning RALM HAI 105 1,205 0 21 Aug 2018
End-to-end Neural Coreference Resolution Kenton Lee Luheng He M. Lewis Luke Zettlemoyer LRM BDL 83 894 0 21 Jul 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 126 591 0 10 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 405 3,798 0 28 Feb 2017
Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations Upol Ehsan Brent Harrison Larry Chan Mark O. Riedl 118 219 0 25 Feb 2017
The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations Lasha Abzianidze Johannes Bjerva Kilian Evang Hessel Haagsma Rik van Noord Pierre Ludmann Duc-Duy Nguyen Johan Bos 3DV 53 159 0 13 Feb 2017
SQuAD: 100,000+ Questions for Machine Comprehension of Text Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang RALM 289 8,160 0 16 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,706 0 10 Jun 2016