Alternatives and similar repositories for mice:

Users that are interested in mice are comparing it to the libraries listed below

• hsajjad / Interpretability-Tutorial-NAACL2021
  ☆24Updated 3 years ago
• ruiqi-zhong / DescribeDistributionalDifferences
  Code for preprint: Summarizing Differences between Text Distributions with Natural Language
  ☆42Updated last year
• tongshuangwu / polyjuice
  ☆95Updated 2 years ago
• tianlu-wang / Identifying-and-Mitigating-Spurious-Correlations-for-Improving-Robustness-in-NLP-Models
  NAACL 2022 Findings
  ☆16Updated 2 years ago
• CoderPat / learning-scaffold
  This is the official implementation for the paper "Learning to Scaffold: Optimizing Model Explanations for Teaching"
  ☆19Updated 2 years ago
• successar / FRESH
  ☆27Updated last year
• shauli-ravfogel / nullspace_projection
  ☆87Updated 2 years ago
• nicola-decao / diffmask
  Pytorch implementation of DiffMask
  ☆55Updated last year
• awebson / prompt_semantics
  This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”
  ☆85Updated 2 years ago
• yanaiela / amnesic_probing
  ☆37Updated 3 years ago
• peterbhase / LAS-NL-Explanations
  Code for paper "Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?"
  ☆20Updated 4 years ago
• INK-USC / hierarchical-explanation-neural-sequence-models
  Source code for "Towards Hierarchical Importance Attribution: Explaining Compositional Semantics for Neural Sequence Models", ICLR 2020.
  ☆30Updated 4 years ago
• peterbhase / ExplanationSearch
  Code for paper "Search Methods for Sufficient, Socially-Aligned Feature Importance Explanations with In-Distribution Counterfactuals"
  ☆17Updated 2 years ago
• princeton-nlp / rationale-robustness
  NAACL 2022: Can Rationalization Improve Robustness? https://arxiv.org/abs/2204.11790
  ☆27Updated 2 years ago
• peterbhase / ExplanationRoles
  Code for paper "When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data"
  ☆14Updated 3 years ago
• copenlu / xai-benchmark
  A Diagnostic Study of Explainability Techniques for Text Classification
  ☆66Updated 4 years ago
• allenai / contrastive-explanations
  Explaining neural decisions contrastively to alternative decisions.
  ☆23Updated 3 years ago
• allenai / label_rationale_association
  Code for EMNLP 2021 paper "Measuring Association Between Labels and Free-Text Rationales"
  ☆12Updated last year
• bhargaviparanjape / explainable_qa
  Implementation for https://arxiv.org/abs/2005.00652
  ☆28Updated 2 years ago
• peterwestuw / surface-form-competition
  ☆58Updated 2 years ago
• dheerajrajagopal / SelfExplain
  ☆38Updated last year
• pliang279 / sent_debias
  [ACL 2020] Towards Debiasing Sentence Representations
  ☆64Updated 2 years ago
• SawanKumar28 / nile
  NILE : Natural Language Inference with Faithful Natural Language Explanations
  ☆30Updated last year
• john-hewitt / conditional-probing
  Codebase for running (conditional) probing experiments
  ☆23Updated 2 years ago
• keyonvafa / sequential-rationales
  Rationales for Sequential Predictions
  ☆40Updated 2 years ago
• gucci-j / light-transformer-emnlp2021
  EMNLP 2021 - Frustratingly Simple Pretraining Alternatives to Masked Language Modeling
  ☆31Updated 3 years ago
• yanaiela / pararel
  ☆42Updated 11 months ago
• successar / Eraser-Benchmark-Baseline-Models
  Baseline for ERASER benchmark
  ☆17Updated 2 years ago
• shreydesai / calibration
  Code and datasets for the EMNLP 2020 paper "Calibration of Pre-trained Transformers"
  ☆57Updated last year
• SALT-NLP / implicit-hate
  ☆39Updated last year