VerifAI initiative to build open-source easy-to-deploy generative question-answering engine that can reference and verify answers for correctness (using posteriori model)
-
Updated
Nov 22, 2024 - Jupyter Notebook
VerifAI initiative to build open-source easy-to-deploy generative question-answering engine that can reference and verify answers for correctness (using posteriori model)
✨ Build AI interfaces that spark joy
This repository contains the code and models for the LegalLens-2024 shared task, which detects legal violations in unstructured text and associates them with affected individuals using transformer models like BERT, RoBERTa, and DeBERTa for Named Entity Recognition (L-NER) and Natural Language Inference (L-NLI).
OpenSpaceGuide: steering OpenSpace with natural language
We provide the code used to produce the models and analyses of our article: Finding Conflicts of Opinion in Citizen Participation Platforms
Open-source benchmark datasets and pretrained transformer models in the Filipino language.
PhoBERT: Pre-trained language models for Vietnamese (EMNLP-2020 Findings)
Natural Language Inference task on adversarial FEVER dataset.
Tableau-based Theorem Prover for Natural Logic and Language
XNLIeu: a dataset for cross-lingual NLI in Basque
A conversational agent
Antibodies for LLMs hallucinations (grouping LLM as a judge, NLI, reward models)
Mitigating a language model's over-confidence with NLI predictions on Multi-NLI hypotheses with random word order using PAWS (paraphrase) and Winogrande (anaphora).
Probing handling of verbal probabilities in NLP models
A PyTorch Based Deep Learning Quick Develop Framework. One-Stop for train/predict/server/demo
An AI assistant for a Learning Management System (LMS)
BERT and RoBERTa models fine-tuned on the MNLI dataset, optimized for binary entailment/non-entailment classification. Additionally, their performance is explored in handling figurative language.
A Natural Language Inference (NLI) model based on Transformers (BERT and ALBERT)
Natural Language Understanding and Response engine. Semantic parser and execution engine. With DBPedia and SHRDLU demo's.
Add a description, image, and links to the nli topic page so that developers can more easily learn about it.
To associate your repository with the nli topic, visit your repo's landing page and select "manage topics."