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 101–150 of 216 papers

TitleStatusHype
Learning to Generate Programs for Table Fact Verification via Structure-Aware Semantic ParsingCode0
Learning to Verify Summary Facts with Fine-Grained LLM FeedbackCode0
Logic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact VerificationCode0
M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence RetrievalCode0
MCQG-SRefine: Multiple Choice Question Generation and Evaluation with Iterative Self-Critique, Correction, and Comparison FeedbackCode0
Molecular Facts: Desiderata for Decontextualization in LLM Fact VerificationCode0
Multi-Evidence based Fact Verification via A Confidential Graph Neural NetworkCode0
Multilingual Evidence Retrieval and Fact Verification to Combat Global Disinformation: The Power of PolyglotismCode0
Program Enhanced Fact Verification with Verbalization and Graph Attention NetworkCode0
Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language ModelsCode0
QA-NatVer: Question Answering for Natural Logic-based Fact VerificationCode0
Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting EvidenceCode0
Rethinking Loss Functions for Fact VerificationCode0
End-to-End Bias Mitigation by Modelling Biases in CorporaCode0
Step-by-Step Fact Verification System for Medical Claims with Explainable ReasoningCode0
Structural Self-Supervised Objectives for TransformersCode0
TabFact: A Large-scale Dataset for Table-based Fact VerificationCode0
Table-based Fact Verification with Salience-aware LearningCode0
Table-based Fact Verification with Self-adaptive Mixture of ExpertsCode0
TabVer: Tabular Fact Verification with Natural LogicCode0
Take It Easy: Label-Adaptive Self-Rationalization for Fact Verification and Explanation GenerationCode0
Team Trifecta at Factify5WQA: Setting the Standard in Fact Verification with Fine-TuningCode0
Topic-Aware Evidence Reasoning and Stance-Aware Aggregation for Fact VerificationCode0
Towards a Framework for Evaluating Explanations in Automated Fact VerificationCode0
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language ModelsCode0
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