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 1–25 of 216 papers

TitleStatusHype
DS@GT at CheckThat! 2025: Evaluating Context and Tokenization Strategies for Numerical Fact VerificationCode0
Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact VerifiersCode1
ClimateViz: A Benchmark for Statistical Reasoning and Fact Verification on Scientific ChartsCode0
Reasoning-Table: Exploring Reinforcement Learning for Table ReasoningCode2
Table-R1: Inference-Time Scaling for Table ReasoningCode1
Improving the fact-checking performance of language models by relying on their entailment ability—0
Hypothetical Documents or Knowledge Leakage? Rethinking LLM-based Query Expansion—0
Reasoning Court: Combining Reasoning, Action, and Judgment for Multi-Hop Reasoning—0
Synthetic News Generation for Fake News Classification—0
Poly-FEVER: A Multilingual Fact Verification Benchmark for Hallucination Detection in Large Language Models—0
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-CheckingCode2
HIPPO: Enhancing the Table Understanding Capability of Large Language Models through Hybrid-Modal Preference OptimizationCode1
Benchmarking Retrieval-Augmented Generation in Multi-Modal ContextsCode2
Step-by-Step Fact Verification System for Medical Claims with Explainable ReasoningCode0
CMQCIC-Bench: A Chinese Benchmark for Evaluating Large Language Models in Medical Quality Control Indicator Calculation—0
FlashCheck: Exploration of Efficient Evidence Retrieval for Fast Fact-Checking—0
Fine-Grained Appropriate Reliance: Human-AI Collaboration with a Multi-Step Transparent Decision Workflow for Complex Task Decomposition—0
SimGRAG: Leveraging Similar Subgraphs for Knowledge Graphs Driven Retrieval-Augmented GenerationCode2
Assessing the Limitations of Large Language Models in Clinical Fact DecompositionCode1
Learning to Verify Summary Facts with Fine-Grained LLM FeedbackCode0
Truth or Mirage? Towards End-to-End Factuality Evaluation with LLM-OasisCode1
ZeFaV: Boosting Large Language Models for Zero-shot Fact VerificationCode0
FactLens: Benchmarking Fine-Grained Fact Verification—0
TabVer: Tabular Fact Verification with Natural LogicCode0
AMREx: AMR for Explainable Fact Verification—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