Advanced Topics in Computational Semantics (ATCS) - Practical 1

From Hero to Zéroe: A Benchmark of Low-Level Adversarial Attacks

PyTorch Implementation of "Learning Natural Language Inference with LSTM", 2016, S. Wang et al. (https://arxiv.org/pdf/1512.08849.pdf)

JSNLI (Japanese SNLI) dataset for huggingface datasets

In this repository, we deal with the task of implementing Natural Language Inferencing (NLI) using the SNLI dataset. Different methods such as SumEmbeddings, BiLSTM, BiGRU, Transformers, and Logistic Regression are experimented.

pytorch implementation of various models for snli and mnli task

Model Evaluation using WANLI Test Set

Model Evaluation using SNLI Development Set

Adversarial evaluation of model performances [Updated]

Model Evaluation using SuperGLUE Diagnostic Dataset

A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".

Implementation of the ESIM model for natural language inference with PyTorch

Implementation of models in our EMNLP 2019 paper: A Logic-Driven Framework for Consistency of Neural Models

Implementation of the InferSent paper by Conneau et al., EMNLP2017

Implementation of the NLI model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic.

Pytorch implementations of several text semantic matching models. The repository currently contains ESIM, CAFE, RE2

Implementation of the semi-structured inference model in our ACL 2020 paper. INFOTABS: Inference on Tables as Semi-structured Data

Implementation of models in our EMNLP 2019 paper: A Logic-Driven Framework for Consistency of Neural Models

End-to-end Siamese CNNs as feature selection for a CNN-based Entailment Modelling