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 51–75 of 216 papers

TitleStatusHype
Truth or Mirage? Towards End-to-End Factuality Evaluation with LLM-OasisCode1
Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact VerificationCode1
Decorrelate Irrelevant, Purify Relevant: Overcome Textual Spurious Correlations from a Feature PerspectiveCode1
Where Are the Facts? Searching for Fact-checked Information to Alleviate the Spread of Fake NewsCode1
KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language ModelsCode1
FactKG: Fact Verification via Reasoning on Knowledge GraphsCode1
Get Your Vitamin C! Robust Fact Verification with Contrastive EvidenceCode1
Evidence-based Factual Error CorrectionCode1
ChartCheck: Explainable Fact-Checking over Real-World Chart ImagesCode1
FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured informationCode1
KILT: a Benchmark for Knowledge Intensive Language TasksCode1
Evaluating adversarial attacks against multiple fact verification systems—0
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy—0
Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering—0
Dual-Channel Evidence Fusion for Fact Verification over Texts and Tables—0
AttentiveChecker: A Bi-Directional Attention Flow Mechanism for Fact Verification—0
Adapting Open Domain Fact Extraction and Verification to COVID-FACT through In-Domain Language Modeling—0
DP-KB: Data Programming with Knowledge Bases Improves Transformer Fine Tuning for Answer Sentence Selection—0
Distilling the Evidence to Augment Fact Verification Models—0
GLAF: Global-to-Local Aggregation and Fission Network for Semantic Level Fact Verification—0
Global Responses to the COVID-19 Pandemic: A Case Study of Spatiotemporal Evidence Finding and Verification—0
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability—0
Are Large Language Models Good Fact Checkers: A Preliminary Study—0
Dataset of Fake News Detection and Fact Verification: A Survey—0
BreakingBERT@IITK at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables—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
10ElefPavKILT-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