code-terminator / classwise_rationale
Tensorflow implementation for the Class-wise Selective Rationalization
☆14Updated last year
Related projects: ⓘ
- Tensorflow implementation of Invariant Rationalization☆47Updated last year
- This is the official implementation for the paper "Learning to Scaffold: Optimizing Model Explanations for Teaching"☆19Updated 2 years ago
- Code for paper "Search Methods for Sufficient, Socially-Aligned Feature Importance Explanations with In-Distribution Counterfactuals"☆17Updated last year
- Diagnostic benchmark suite to explicitly test logical relational reasoning on natural language☆90Updated 4 months ago
- Demo for method introduced in "Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs"☆56Updated 4 years ago
- Conditional Theorem Proving☆51Updated 3 years ago
- Code for "Rissanen Data Analysis: Examining Dataset Characteristics via Description Length" by Ethan Perez, Douwe Kiela, and Kyungyhun Ch…☆35Updated 3 years ago
- Interpretable Neural Predictions with Differentiable Binary Variables☆85Updated 3 years ago
- ☆65Updated last month
- LP-SparseMAP: Differentiable sparse structured prediction in coarse factor graphs☆41Updated 10 months ago
- A simple Tensorflow implementation of https://arxiv.org/abs/1906.04985☆13Updated 5 years ago
- PyTorch code for meta seq2seq learning☆43Updated 4 years ago
- [WNGT(2019)] On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation☆11Updated 2 years ago
- Group-conditional DRO to alleviate spurious correlations☆15Updated 3 years ago
- Code accompanying our paper at AISTATS 2020☆21Updated 3 years ago
- Implementation of the first neural natural logic paper on natural language inference☆11Updated last year
- Semantic Loss code☆58Updated 5 years ago
- ☆10Updated 4 years ago
- "Predict, then Interpolate: A Simple Algorithm to Learn Stable Classifiers" ICML 2021☆17Updated 3 years ago
- Code for Paper: Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data☆35Updated 3 years ago
- Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019☆14Updated 3 months ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 2 years ago
- Gromov-Wasserstein Alignment of Embeddings☆64Updated 2 years ago
- Pragmatic models for generating and following instructions☆13Updated 4 years ago
- Experiments of ACL 2018 paper box embeddings☆32Updated 5 years ago
- ☆20Updated 2 years ago
- Implementation of the NLI model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic.☆42Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated last year
- Rep the Set: Neural Networks for Learning Set Representations☆27Updated 4 years ago
- ☆57Updated 4 years ago