Alternatives and similar repositories for fact-graph:

Users that are interested in fact-graph are comparing it to the libraries listed below

• esdurmus / feqa
  Data and code for "A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization" (ACL 2020)
  ☆48Updated last year
• artidoro / frank
  FRANK: Factuality Evaluation Benchmark
  ☆54Updated 2 years ago
• kleinay / seq2seq_constrained_decoding
  Constrained decoding utilities for text generation using Huggingface seq2seq models
  ☆23Updated 2 years ago
• luyang-huang96 / LongDocSum
  Code for NAACL 2021 full paper "Efficient Attentions for Long Document Summarization"
  ☆67Updated 3 years ago
• salesforce / QGen
  ☆33Updated last year
• mingdachen / WikiTableT
  Code, data, and pretrained models for the paper "Generating Wikipedia Article Sections from Diverse Data Sources"
  ☆20Updated 4 years ago
• teacherpeterpan / Zero-shot-Fact-Verification
  Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"
  ☆64Updated 3 years ago
• meetdavidwan / factpegasus
  PyTorch code for "FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization" (NAACL 2022)
  ☆38Updated 2 years ago
• amazon-science / fact-check-summarization
  ☆77Updated 11 months ago
• bjascob / amrlib-models
  Repository for model used in amrlib
  ☆22Updated last year
• wzhouad / NLL-IE
  Source code for paper "Learning from Noisy Labels for Entity-Centric Information Extraction", EMNLP 2021
  ☆55Updated 3 years ago
• youngbin-ro / Multi2OIE
  Multi^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERT (Findings of ACL: EMNLP 2020)
  ☆56Updated 2 years ago
• ryokamoi / wice
  This repository contains the dataset and code for "WiCE: Real-World Entailment for Claims in Wikipedia" in EMNLP 2023.
  ☆41Updated last year
• AkariAsai / evidentiality_qa
  The official implemetation of "Evidentiality-guided Generation for Knowledge-Intensive NLP Tasks" (NAACL 2022).
  ☆43Updated 2 years ago
• swarnaHub / ExplaGraphs
  [EMNLP 2021] Dataset and PyTorch Code for ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning
  ☆11Updated 2 years ago
• j6mes / acl2021-factual-error-correction
  ACL 2021
  ☆26Updated 2 years ago
• goodbai-nlp / AMRBART
  Code for our paper "Graph Pre-training for AMR Parsing and Generation" in ACL2022
  ☆96Updated 11 months ago
• cultural-csk / candle
  Extracting Cultural Commonsense Knowledge at Scale (WWW 2023)
  ☆11Updated last year
• tomerwolgithub / Break
  ☆45Updated 2 years ago
• stangelid / qt
  ☆44Updated 3 years ago
• McGill-NLP / FaithDial
  ☆48Updated 2 years ago
• yanaiela / pararel
  ☆44Updated last year
• Jacobsolawetz / large-scale-oie
  ☆37Updated 2 years ago
• W4ngatang / qags
  Question Answering and Generation for Summarization
  ☆68Updated 2 years ago
• awebson / prompt_semantics
  This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”
  ☆85Updated 2 years ago
• TevenLeScao / pet
  This repository contains the code for "How many data points is a prompt worth?"
  ☆48Updated 3 years ago
• vidhishanair / FactEdit
  ☆14Updated last year
• DevSinghSachan / syntax-augmented-bert
  Source code of the paper "Do Syntax Trees Help Pre-trained Transformers Extract Information?" (EACL 2021)
  ☆74Updated 3 years ago
• peterwestuw / surface-form-competition
  ☆58Updated 2 years ago
• princeton-nlp / rationale-robustness
  NAACL 2022: Can Rationalization Improve Robustness? https://arxiv.org/abs/2204.11790
  ☆27Updated 2 years ago