Learning to Scaffold: Optimizing Model Explanations for Teaching

22 April 2022

Patrick Fernandes

Marcos Vinícius Treviso

Danish Pruthi

André F. T. Martins

Graham Neubig

FAtt

ArXiv PDF HTML

Papers citing "Learning to Scaffold: Optimizing Model Explanations for Teaching"

21 / 21 papers shown

Title
Breaking Free from MMI: A New Frontier in Rationalization by Probing Input Utilization W. Liu Zhiying Deng Zhongyu Niu Jun Wang Haozhao Wang Zhigang Zeng Ruixuan Li 44 2 0 08 Mar 2025
Explanation Regularisation through the Lens of Attributions Pedro Ferreira Wilker Aziz Ivan Titov 43 1 0 23 Jul 2024
Evaluating Saliency Explanations in NLP by Crowdsourcing Xiaotian Lu Jiyi Li Zhen Wan Xiaofeng Lin Koh Takeuchi Hisashi Kashima XAI FAtt LRM 27 1 0 17 May 2024
Explainable Bayesian Optimization Tanmay Chakraborty Christin Seifert Christian Wirth 58 5 0 24 Jan 2024
Enhancing the Rationale-Input Alignment for Self-explaining Rationalization Wei Liu Haozhao Wang Jun Wang Zhiying Deng Yuankai Zhang Chengwei Wang Ruixuan Li 32 9 0 07 Dec 2023
Proto-lm: A Prototypical Network-Based Framework for Built-in Interpretability in Large Language Models Sean Xie Soroush Vosoughi Saeed Hassanpour 41 3 0 03 Nov 2023
D-Separation for Causal Self-Explanation Wei Liu Jun Wang Haozhao Wang Rui Li Zhiying Deng YuanKai Zhang Yang Qiu 82 14 0 23 Sep 2023
Towards Explainable Evaluation Metrics for Machine Translation Christoph Leiter Piyawat Lertvittayakumjorn M. Fomicheva Wei-Ye Zhao Yang Gao Steffen Eger ELM 28 13 0 22 Jun 2023
Quantifying the Intrinsic Usefulness of Attributional Explanations for Graph Neural Networks with Artificial Simulatability Studies Jonas Teufel Luca Torresi Pascal Friederich FAtt 19 1 0 25 May 2023
Decoupled Rationalization with Asymmetric Learning Rates: A Flexible Lipschitz Restraint Wei Liu Jun Wang Haozhao Wang Rui Li Yang Qiu Yuankai Zhang Jie Han Yixiong Zou 44 12 0 23 May 2023
The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics Ricardo Rei Nuno M. Guerreiro Marcos Vinícius Treviso Luísa Coheur A. Lavie André F.T. Martins 27 15 0 19 May 2023
ExaRanker: Explanation-Augmented Neural Ranker Fernando Ferraretto Thiago Laitz R. Lotufo Rodrigo Nogueira ELM LRM 28 7 0 25 Jan 2023
Explanation Regeneration via Information Bottleneck Qintong Li Zhiyong Wu Lingpeng Kong Wei Bi 22 3 0 19 Dec 2022
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 29 39 0 07 Dec 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 21 8 0 23 Nov 2022
Induced Natural Language Rationales and Interleaved Markup Tokens Enable Extrapolation in Large Language Models M. Bueno Carlos Gemmel Jeffrey Stephen Dalton R. Lotufo Rodrigo Nogueira LRM 22 12 0 24 Aug 2022
"Will You Find These Shortcuts?" A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification Jasmijn Bastings Sebastian Ebert Polina Zablotskaia Anders Sandholm Katja Filippova 115 75 0 14 Nov 2021
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 179 687 0 22 Apr 2021
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism M. Shoeybi M. Patwary Raul Puri P. LeGresley Jared Casper Bryan Catanzaro MoE 245 1,821 0 17 Sep 2019
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,684 0 09 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017