mitharvardwai / mitxharvard-wai-resources

Related projects ⓘ

Alternatives and complementary repositories for mitxharvard-wai-resources

• 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
• kailas-v / human-ai-interactions
  ☆11Updated 2 years ago
• elehman16 / exposing_patient_data_release
  ☆49Updated 3 years ago
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• peterbhase / ExplanationSearch
  Code for paper "Search Methods for Sufficient, Socially-Aligned Feature Importance Explanations with In-Distribution Counterfactuals"
  ☆16Updated 2 years ago
• sebastianGehrmann / CausalMediationAnalysis
  Code for the paper "Causal Mediation Analysis for Interpreting Neural NLP: The Case of Gender Bias"
  ☆74Updated 3 years ago
• clinicalml / teaching-to-understand-ai
  Code and webpages for our study on teaching humans to defer to an AI
  ☆11Updated last year
• copenlu / xai-benchmark
  A Diagnostic Study of Explainability Techniques for Text Classification
  ☆67Updated 4 years ago
• BatsResearch / nplm
  A weak supervision framework for (partial) labeling functions
  ☆14Updated 4 months ago
• allenai / contrastive-explanations
  Explaining neural decisions contrastively to alternative decisions.
  ☆23Updated 3 years ago
• jayelm / compexp
  Compositional Explanations of Neurons, NeurIPS 2020 https://arxiv.org/abs/2006.14032
  ☆25Updated 3 years ago
• salesforce / fast-influence-functions
  ☆86Updated last year
• MLforHealth / MIMIC_Generalisation
  Code to study the generalisability of benchmark models on non-stationary EHRs.
  ☆14Updated 5 years ago
• microsoft / augmented-interpretable-models
  Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
  ☆38Updated 7 months ago
• swabhs / notebooks_for_aflite
  IPython notebook with synthetic experiments for AFLite, based on the ICML 2020 paper, "Adversarial Filters of Dataset Biases".
  ☆16Updated 4 years ago
• pliang279 / LM_bias
  [ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models
  ☆60Updated 2 years ago
• mmoradi-iut / NLP-perturbation
  Text perturbation methods to evaluate the robustness of NLP models
  ☆21Updated 3 years ago
• john-hewitt / control-tasks
  Repository describing example random control tasks for designing and interpreting neural probes
  ☆31Updated 2 years ago
• benbo / interactive-weak-supervision
  Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
  ☆30Updated 3 years ago
• code-terminator / classwise_rationale
  Tensorflow implementation for the Class-wise Selective Rationalization
  ☆14Updated last year
• tongshuangwu / polyjuice
  ☆95Updated 2 years ago
• facebookresearch / CMR
  N/A
  ☆18Updated 2 years ago
• allenai / mice
  ☆26Updated 2 years ago
• awasthiabhijeet / Learning-From-Rules
  Implementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net…
  ☆49Updated last year
• feyzaakyurek / bbnli
  Bias Benchmark for Natural Language Inference. Code repo for the Findings of NAACL 2022 paper "On Measuring Social Biases in Prompt-Based…
  ☆15Updated 2 years ago
• ruiqi-zhong / DescribeDistributionalDifferences
  Code for preprint: Summarizing Differences between Text Distributions with Natural Language
  ☆42Updated last year
• fdalvi / NeuroX
  A Python library that encapsulates various methods for neuron interpretation and analysis in Deep NLP models.
  ☆97Updated last year
• zouharvi / ryanize-bib
  Highlight errors in a bib file: missing URLs, capitalization protection, etc
  ☆24Updated 6 months ago
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆40Updated 2 years ago
• luoyuanlab / Clinical-Longformer
  ☆56Updated last year