rycolab / bayesian-miLinks
This code accompanies the paper "Bayesian Framework for Information-Theoretic Probing" published in EMNLP 2021.
☆10Updated 4 years ago
Alternatives and similar repositories for bayesian-mi
Users that are interested in bayesian-mi are comparing it to the libraries listed below
Sorting:
- Codebase describing experiments in Truncation Sampling as Language Model Desmoothing☆13Updated 3 years ago
- Code for the paper "Implicit Representations of Meaning in Neural Language Models"☆55Updated 2 years ago
- Automatic metrics for GEM tasks☆67Updated 3 years ago
- ☆114Updated 3 years ago
- This is a repository with the code for the EMNLP 2020 paper "Information-Theoretic Probing with Minimum Description Length"☆71Updated last year
- ☆39Updated 4 years ago
- Code accompanying our papers on the "Generative Distributional Control" framework☆118Updated 3 years ago
- PyTorch code for the RetoMaton paper: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022)☆76Updated 3 years ago
- ☆90Updated 3 years ago
- ☆38Updated last year
- ☆24Updated 4 years ago
- ☆48Updated 2 years ago
- This code accompanies the paper "Information-Theoretic Probing for Linguistic Structure" published in ACL 2020.☆21Updated 5 years ago
- Source code for CoNLL 2021 paper by Huebner et al. 2021☆20Updated 2 years ago
- [EMNLP 2020] Collective HumAn OpinionS on Natural Language Inference Data☆40Updated 3 years ago
- Code and data for "A Systematic Assessment of Syntactic Generalization in Neural Language Models"☆29Updated 4 years ago
- ☆87Updated last year
- ☆62Updated 3 years ago
- EMNLP 2021 - Frustratingly Simple Pretraining Alternatives to Masked Language Modeling☆34Updated 4 years ago
- Codebase for running (conditional) probing experiments☆22Updated 3 years ago
- Rationales for Sequential Predictions☆40Updated 3 years ago
- ☆58Updated 3 years ago
- This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”☆85Updated 3 years ago
- Code for paper "CrossFit : A Few-shot Learning Challenge for Cross-task Generalization in NLP" (https://arxiv.org/abs/2104.08835)☆113Updated 3 years ago
- ☆50Updated 2 years ago
- ☆83Updated 2 years ago
- ☆14Updated 9 months ago
- ☆20Updated 2 years ago
- ☆63Updated 2 years ago
- How Contextual are Contextualized Word Representations?☆43Updated 5 years ago