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
Structural Self-Supervised Objectives for TransformersCode0
Findings of Factify 2: Multimodal Fake News Detection—0
Heuristic Heterogeneous Graph Reasoning Networks for Fact VerificationCode0
Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language ModelsCode0
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy—0
Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering—0
FACTIFY3M: A Benchmark for Multimodal Fact Verification with Explainability through 5W Question-Answering—0
Growing and Serving Large Open-domain Knowledge Graphs—0
Consistent Multi-Granular Rationale Extraction for Explainable Multi-hop Fact Verification—0
FACTIFY-5WQA: 5W Aspect-based Fact Verification through Question Answering—0
Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting EvidenceCode0
BEVERS: A General, Simple, and Performant Framework for Automatic Fact Verification—0
INO at Factify 2: Structure Coherence based Multi-Modal Fact VerificationCode0
Guide the Learner: Controlling Product of Experts Debiasing Method Based on Token Attribution SimilaritiesCode0
Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture—0
Natural Logic-guided Autoregressive Multi-hop Document Retrieval for Fact Verification—0
Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learning—0
Converge to the Truth: Factual Error Correction via Iterative Constrained EditingCode0
Data-Efficient Autoregressive Document Retrieval for Fact Verification—0
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models—0
Learning to Navigate Wikipedia by Taking Random Walks—0
Table-based Fact Verification with Self-labeled Keypoint Alignment—0
SISER: Semantic-Infused Selective Graph Reasoning for Fact Verification—0
GLAF: Global-to-Local Aggregation and Fission Network for Semantic Level Fact Verification—0
Fact-Saboteurs: A Taxonomy of Evidence Manipulation Attacks against Fact-Verification SystemsCode0
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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