SOTAVerified

Fact Verification

Fact verification, also called "fact checking", is a process of verifying facts in natural text against a database of facts.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 216 papers

TitleStatusHype
Towards Debiasing Fact Verification ModelsCode0
Unsupervised Pretraining for Fact Verification by Language Model DistillationCode0
XFEVER: Exploring Fact Verification across LanguagesCode0
ZeFaV: Boosting Large Language Models for Zero-shot Fact VerificationCode0
Learn to Combine Linguistic and Symbolic Information for Table-based Fact Verification—0
Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture—0
Logically at Factify 2022: Multimodal Fact Verification—0
Verdict Inference with Claim and Retrieved Elements Using RoBERTa—0
Evaluating adversarial attacks against multiple fact verification systems—0
LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification—0
Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering—0
Approximate Conditional Coverage & Calibration via Neural Model Approximations—0
BreakingBERT@IITK at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables—0
Mining the Explainability and Generalization: Fact Verification Based on Self-Instruction—0
Modeling Entity Knowledge for Fact Verification—0
ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source—0
BOUN at SemEval-2021 Task 9: Text Augmentation Techniques for Fact Verification in Tabular Data—0
BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verification—0
Multimodal Misinformation Detection using Large Vision-Language Models—0
Natural Logic-guided Autoregressive Multi-hop Document Retrieval for Fact Verification—0
Overview of Factify5WQA: Fact Verification through 5W Question-Answering—0
Dual-Channel Evidence Fusion for Fact Verification over Texts and Tables—0
Paragraph-based Transformer Pretraining for Multi-Sentence Inference—0
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models—0
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection—0
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All datasetsKILT: FEVERFEVERDanFEVER

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Re2GKILT-AC78.53—Unverified
2intersectKILT-AC71.28—Unverified
3WikipediaKILT-AC65.68—Unverified
4KGIKILT-AC64.41—Unverified
5Multitask DPR + BARTKILT-AC63.94—Unverified
6BERT + DPRKILT-AC58.58—Unverified
7RAGKILT-AC53.45—Unverified
8BART + DPRKILT-AC47.68—Unverified
9NSMNKILT-AC41.88—Unverified
10T5-baseKILT-AC0—Unverified
#ModelMetricClaimedVerifiedStatus
1ProoFVer-SBAccuracy79.47—Unverified
2DREAMAccuracy76.85—Unverified
3RoBERTa-Base Joint MSPP FlexibleAccuracy75.36—Unverified
4RoBERTa-Base Joint MSPPAccuracy74.39—Unverified
5KGATAccuracy74.1—Unverified
6RAGAccuracy72.5—Unverified
7GEARAccuracy71.6—Unverified
#ModelMetricClaimedVerifiedStatus
1DanFEVER XLM-RoBERTa LargeF10.9—Unverified