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 76–100 of 216 papers

TitleStatusHype
AMREx: AMR for Explainable Fact Verification—0
TabVer: Tabular Fact Verification with Natural LogicCode0
Augmenting the Veracity and Explanations of Complex Fact Checking via Iterative Self-Revision with LLMs—0
ChronoFact: Timeline-based Temporal Fact Verification—0
A Little Human Data Goes A Long WayCode0
MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison FeedbackCode0
Overview of Factify5WQA: Fact Verification through 5W Question-Answering—0
Take It Easy: Label-Adaptive Self-Rationalization for Fact Verification and Explanation GenerationCode0
Zero-Shot Fact Verification via Natural Logic and Large Language ModelsCode0
Claim Verification in the Age of Large Language Models: A Survey—0
Fact or Fiction? Improving Fact Verification with Knowledge Graphs through Simplified Subgraph RetrievalsCode0
Improving Retrieval Augmented Language Model with Self-Reasoning—0
LookupForensics: A Large-Scale Multi-Task Dataset for Multi-Phase Image-Based Fact Verification—0
Evidence-Based Temporal Fact Verification—0
Multimodal Misinformation Detection using Large Vision-Language Models—0
Scalable and Domain-General Abstractive Proposition Segmentation—0
Molecular Facts: Desiderata for Decontextualization in LLM Fact VerificationCode0
Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments—0
FactGenius: Combining Zero-Shot Prompting and Fuzzy Relation Mining to Improve Fact Verification with Knowledge GraphsCode0
Mining the Explainability and Generalization: Fact Verification Based on Self-Instruction—0
Multi-Evidence based Fact Verification via A Confidential Graph Neural NetworkCode0
ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source—0
Hypothesis Testing Prompting Improves Deductive Reasoning in Large Language Models—0
Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization—0
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language ModelsCode0
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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