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We trained multiple models on ", "url": "https://github.com/adity7a/FakeNewsDetection.git", "size_kb": 54101, "q": "indian fake news detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-08-01" }, "SaiSanjana2002/Fake_news_detection": { "stars": 0, "desc": "fake news detection on Indian dataset", "url": "https://github.com/SaiSanjana2002/Fake_news_detection.git", "size_kb": 4674, "q": "indian fake news detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-03-19" }, "PriyanshuPrasad1718/Chrome-extension-for-Indian-fake-news-detection": { "stars": 0, "desc": "Develop a Chrome extension designed to identify fake news, trained using a dataset comprising Indian news articles. The extension will utilize two mod", "url": "https://github.com/PriyanshuPrasad1718/Chrome-extension-for-Indian-fake-news-detection.git", "size_kb": 9131, "q": "indian fake news detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-10-22" }, "wenhuchen/Table-Fact-Checking": { "stars": 416, "desc": "Data and Code for ICLR2020 Paper \"TabFact: A Large-scale Dataset for Table-based Fact Verification\"", "url": "https://github.com/wenhuchen/Table-Fact-Checking.git", "size_kb": 774188, "q": "fact verification dataset", "lang": "Python", "pushed": "2023-09-19" }, "Raldir/FEVEROUS": { "stars": 76, "desc": "Repository for Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS), accepted to NeurIPS 2021 Dataset and Benchmar", "url": "https://github.com/Raldir/FEVEROUS.git", "size_kb": 4880, "q": "fact verification dataset", "lang": "PHP", "pushed": "2024-07-01" }, "TalSchuster/FeverSymmetric": { "stars": 53, "desc": "Symmetric evaluation set based on the FEVER (fact verification) dataset", "url": "https://github.com/TalSchuster/FeverSymmetric.git", "size_kb": 154, "q": "fact verification dataset", "lang": "Python", "pushed": "2021-04-05" }, "FuxiaoLiu/Twitter-Video-dataset": { "stars": 12, "desc": "[EACL'23] COVID-VTS: Fact Extraction and Verification on Short Video Platforms", "url": "https://github.com/FuxiaoLiu/Twitter-Video-dataset.git", "size_kb": 1041, "q": "fact verification dataset", "lang": null, "pushed": "2023-09-26" }, "dependentsign/EX-FEVER": { "stars": 12, "desc": "A Dataset for Multi-hop Explainable Fact Verification (ACL 2024 findings)", "url": "https://github.com/dependentsign/EX-FEVER.git", "size_kb": 37950, "q": "fact verification dataset", "lang": "Python", "pushed": "2025-03-22" }, "IKMLab/CFEVER-data": { "stars": 9, "desc": "AAAI-24 CFEVER: A Chinese Fact Extraction and VERification Dataset", "url": "https://github.com/IKMLab/CFEVER-data.git", "size_kb": 1629, "q": "fact verification dataset", "lang": null, "pushed": "2026-02-26" }, "Shreyashm16/Factify": { "stars": 8, "desc": "Factify is a Multi-Modal Fact Verification dataset released for a shared task as part of the De-Factify workshop in AAAI-21.", "url": "https://github.com/Shreyashm16/Factify.git", "size_kb": 12, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2022-10-14" }, "posuer/Check-COVID": { "stars": 7, "desc": "A COVID-19 News Fact-checking Dataset. 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Algorithms, results, and documentation inclu", "url": "https://github.com/KHayzelden/AutomatedFactChecking.git", "size_kb": 23718, "q": "fact verification dataset", "lang": "Python", "pushed": "2019-08-18" }, "derrickny/Credibility_verification_system_Model_building_API": { "stars": 1, "desc": "This project focuses on text-based classification, specifically in the domain of fact-checking statements. The dataset comprises statements paired wit", "url": "https://github.com/derrickny/Credibility_verification_system_Model_building_API.git", "size_kb": 14226, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2023-11-25" }, "claudio-bon/fact-checking-fever": { "stars": 1, "desc": "In this assingment we perform a fact checking task over FEVER dataset. 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In this thesis, we deal with Con", "url": "https://github.com/arpita739/Bengali-and-Hindi-Signature-Verification-using-Convolution-Siamese-Network.git", "size_kb": 4460, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2021-07-01" }, "Dnnss9/fact-verification": { "stars": 0, "desc": "comparative project using FEVER dataset", "url": "https://github.com/Dnnss9/fact-verification.git", "size_kb": 13405, "q": "fact verification dataset", "lang": "Python", "pushed": "2025-05-06" }, "poliinfo3/PoliInfo3-FormalRun-FactVerification": { "stars": 0, "desc": "Dataset (Formal Run): Fact Verification", "url": "https://github.com/poliinfo3/PoliInfo3-FormalRun-FactVerification.git", "size_kb": 6844, "q": "fact verification dataset", "lang": "Python", "pushed": "2022-06-14" }, "oughtinc/Factored-verification-dataset": { "stars": 0, "desc": "Paper dataset for \"Factored Verification: Detecting and Reducing Hallucination in Summaries of Academic Papers\"", "url": "https://github.com/oughtinc/Factored-verification-dataset.git", "size_kb": 892, "q": "fact verification dataset", "lang": "Python", "pushed": "2023-10-15" }, "ZonG0D/unsloth-verification-datasets": { "stars": 0, "desc": "Fine-tuning datasets teaching LLMs to verify device/platform facts via terminal instead of guessing", "url": "https://github.com/ZonG0D/unsloth-verification-datasets.git", "size_kb": 31, "q": "fact verification dataset", "lang": null, "pushed": "2026-07-07" }, "doeniz/fact-verification-datasets-with-evidence": { "stars": 0, "desc": "Datasets, including retrieved evidence, used in the bachlor thesis \"Towards Reliable Fact-Verification Systems\" (2025). 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CC BY 4.0.", "url": "https://github.com/SinoFacts/dataset.git", "size_kb": 738, "q": "fact verification dataset", "lang": null, "pushed": "2026-08-16" }, "Aalapx/stance-based-fact-verification": { "stars": 0, "desc": "Hybrid retrieval-based stance verification system using FEVER dataset", "url": "https://github.com/Aalapx/stance-based-fact-verification.git", "size_kb": 21, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-03-23" }, "Samarthsinghal28/5W-Fact-Verification": { "stars": 0, "desc": "5W Fact Verification Using Machine Learning Models on the FEVER Dataset", "url": "https://github.com/Samarthsinghal28/5W-Fact-Verification.git", "size_kb": 422, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2025-09-24" }, "gilbertmunuotz/algorithmic-fact-verification": { "stars": 0, "desc": "ML project for detecting fake news and verifying claims using TF-IDF + Logistic Regression on news, LIAR, and Twitter bot datasets.", "url": "https://github.com/gilbertmunuotz/algorithmic-fact-verification.git", "size_kb": 44621, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2026-08-01" }, "oladri-renuka/factuality-verification-analysis": { "stars": 0, "desc": "Error analysis and failure mode comparison of atomic factuality verification methods on FActScore dataset", "url": "https://github.com/oladri-renuka/factuality-verification-analysis.git", "size_kb": 3194, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-04-22" }, "Riddhiman-M/Fact-Extraction-and-Verification": { "stars": 0, "desc": "Given a user query, a relevant fact supporting or refuting it is extracted from the FEVER dataset", "url": "https://github.com/Riddhiman-M/Fact-Extraction-and-Verification.git", "size_kb": 22, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2022-12-13" }, "dc435/Fact_Verification_using_Transformers": { "stars": 0, "desc": "The codebase and report for a fact verification and extraction dataset challenge using an NLP pipeline in python.", "url": "https://github.com/dc435/Fact_Verification_using_Transformers.git", "size_kb": 730, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2023-12-01" }, "18sana/Fact-Verification-Engine": { "stars": 0, "desc": "An autonomous multi-agent fact-verification system that debates claims using Advocate, Skeptic, and Judge agents, performs evidence-backed verificatio", "url": "https://github.com/18sana/Fact-Verification-Engine.git", "size_kb": 133, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-06-29" }, "sudhanshu2049/Scientific-Fact-Check-Classification-Dataset": { "stars": 0, "desc": "The Scientific Claim Verification Dataset (SCVD-11K) is a structured text classification dataset designed for developing and evaluating NLP models tha", "url": "https://github.com/sudhanshu2049/Scientific-Fact-Check-Classification-Dataset.git", "size_kb": 94, "q": "fact verification dataset", "lang": null, "pushed": "2026-02-20" }, "chriskhalil/ARAFA": { "stars": 0, "desc": "ARabic Automatic Fact-checking Annotations \u2014 a large-scale benchmark dataset for automated fact verification in Modern Standard Arabic.", "url": "https://github.com/chriskhalil/ARAFA.git", "size_kb": 1604, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-07-06" }, "doyald19/MedFact": { "stars": 0, "desc": "A web-based assistant that answers questions about diseases, symptoms, treatments \u2014 using verified datasets only.", "url": "https://github.com/doyald19/MedFact.git", "size_kb": 978, "q": "fact verification dataset", "lang": "TypeScript", "pushed": "2025-12-27" }, "mithunpaul08/decomp_attn_fever": { "stars": 0, "desc": "Using allennlp's decomposable attention model over the fever dataset for fact verification", "url": "https://github.com/mithunpaul08/decomp_attn_fever.git", "size_kb": 281, "q": "fact verification dataset", "lang": "Python", "pushed": "2019-03-20" }, "unshDee/FactCheckLIAR": { "stars": 0, "desc": "Fact-verification pipeline with hybrid BM25 + dense retrieval on the LIAR misinformation dataset. 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With a 20,000+ article d", "url": "https://github.com/avijit004/FactBuddy-ML-Powered-Fake-News-Detection.git", "size_kb": 7230, "q": "fact verification dataset", "lang": "Python", "pushed": "2025-03-08" }, "CooperDavis00/kepler-expoplanet-ml-project": { "stars": 0, "desc": "Machine Learning portfolio project, using a Kepler exoplanet search results dataset to verify if objects are in fact exoplanets. ", "url": "https://github.com/CooperDavis00/kepler-expoplanet-ml-project.git", "size_kb": 1631, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2025-05-17" }, "yuxuan-o-o/women-on-the-wall": { "stars": 0, "desc": "Open dataset of historical women for AI persona conversations. Wikipedia-verified facts, voice descriptions, example dialogues, and character boundari", "url": "https://github.com/yuxuan-o-o/women-on-the-wall.git", "size_kb": 69, "q": "fact verification dataset", "lang": null, "pushed": "2026-06-15" }, "biohackdaily/telegram-trading-bots-dataset": { "stars": 0, "desc": "Expert knowledge base on 23 crypto trading bots & AI agents : Telegram, web terminals, CEX & prediction markets, across 9+ chains. 207 reliability-tag", "url": "https://github.com/biohackdaily/telegram-trading-bots-dataset.git", "size_kb": 153, "q": "fact verification dataset", "lang": null, "pushed": "2026-04-10" }, "kimyoohan/factquire": { "stars": 0, "desc": "Source-verified facts feed for commercial LLM APIs \u2014 every price, limit, and lifecycle fact carries a verbatim primary-source quote. 135 models, 16 pr", "url": "https://github.com/kimyoohan/factquire.git", "size_kb": 1712, "q": "fact verification dataset", "lang": "HTML", "pushed": "2026-08-15" }, "AwaiaTahir/Claim-Verifier": { "stars": 0, "desc": "A fact-checking pipeline that verifies statements against local datasets and live web searches using hybrid retrieval and local LLMs.", "url": "https://github.com/AwaiaTahir/Claim-Verifier.git", "size_kb": 33763, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-06-23" }, "Maroof04/TruthLens": { "stars": 0, "desc": "AI-powered misinformation detection system using Retrieval-Augmented Generation (RAG), vector search, and Google Gemini to verify claims against fact-", "url": "https://github.com/Maroof04/TruthLens.git", "size_kb": 819, "q": "fact verification dataset", "lang": "Python", "pushed": "2026-03-11" }, "pablodevicente/IR-Claim_Generation": { "stars": 0, "desc": " implementation of a pipeline for automatic claim generation using the FEVER dataset. The goal is to generate verifiable claims from source documents ", "url": "https://github.com/pablodevicente/IR-Claim_Generation.git", "size_kb": 1977, "q": "fact verification dataset", "lang": "Jupyter Notebook", "pushed": "2025-07-02" }, "MingjunChen1996/Healthcare_Insurance_Fraud_Detection": { "stars": 9, "desc": "Provider Fraud is one of the biggest problems facing Medicare. According to the government, the total Medicare spending increased exponentially due to", "url": "https://github.com/MingjunChen1996/Healthcare_Insurance_Fraud_Detection.git", "size_kb": 961, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2020-06-15" }, "TIBHannover/MM_Claims": { "stars": 8, "desc": "Official code repository for the paper: Gullal Singh Cheema, Sherzod Hakimov, Abdul Sittar, Eric M\u00fcller-Budack, Christian Otto, and Ralph Ewerth. 2022", "url": "https://github.com/TIBHannover/MM_Claims.git", "size_kb": 44322, "q": "claim detection dataset", "lang": "Python", "pushed": "2025-10-27" }, "cleopatra-itn/image_text_claim_detection": { "stars": 5, "desc": "Code and Dataset for paper \"On the Role of Images for Analyzing Claims in Social Media\" @2nd International Workshop on Cross-lingual Event-centric Ope", "url": "https://github.com/cleopatra-itn/image_text_claim_detection.git", "size_kb": 106, "q": "claim detection dataset", "lang": "Python", "pushed": "2021-09-13" }, "vraj141/IMAGE-PROCESSING-FOR-INDIAN-ROADS": { "stars": 5, "desc": "In developing nations such as India, the vehicular growth rate is increasing exponentially which is worsening the traffic operations. Most of the urba", "url": "https://github.com/vraj141/IMAGE-PROCESSING-FOR-INDIAN-ROADS.git", "size_kb": 16035, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2021-12-23" }, "jason50706/CDDTC": { "stars": 4, "desc": "Claim Detection Dataset in Traditional Chinese", "url": "https://github.com/jason50706/CDDTC.git", "size_kb": 6144, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-04-17" }, "Harishr44/Project-on-Insurance-Clain-Detection": { "stars": 3, "desc": "Depending upon Dataset of Hospital's Insurance claim, It will predict whether the candidate's claim is Genuine or Fraud", "url": "https://github.com/Harishr44/Project-on-Insurance-Clain-Detection.git", "size_kb": 438, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2021-02-15" }, "Kartik-Krishna/InsuranceClaims-FraudDetection": { "stars": 3, "desc": "Insurance fraud is a huge problem in the industry. It's difficult to identify fraud claims. Machine Learning is in a unique position to help the Auto ", "url": "https://github.com/Kartik-Krishna/InsuranceClaims-FraudDetection.git", "size_kb": 7602, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2021-04-10" }, "abhinav-123457/Claims-AI-Processor": { "stars": 2, "desc": " Accurate Car Damage Detection using YOLOv8 fine-tuned on the CARDD Dataset", "url": "https://github.com/abhinav-123457/Claims-AI-Processor.git", "size_kb": 20893, "q": "claim detection dataset", "lang": "HTML", "pushed": "2026-06-09" }, "Srijha09/Detection-Of-Fraudulent-Claims-In-Medical-Insurance": { "stars": 2, "desc": "Checking whether the claims are fraud or non-fraud based on various attributes using Medicare Dataset", "url": "https://github.com/Srijha09/Detection-Of-Fraudulent-Claims-In-Medical-Insurance.git", "size_kb": 938, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2019-11-04" }, "mohittomar2008/Insurance-Claims--Fraud-Detection": { "stars": 2, "desc": "Problem Statement: Business case: Insurance fraud is a huge problem in the industry. It's difficult to identify fraud claims. Machine Learning is in a", "url": "https://github.com/mohittomar2008/Insurance-Claims--Fraud-Detection.git", "size_kb": 8667, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-04-27" }, "ankitghosal/healthcare_fraud_detection": { "stars": 2, "desc": "This project aims to identify potential fraud among healthcare providers using medical claims data. Leveraging structured datasets, we integrate, clea", "url": "https://github.com/ankitghosal/healthcare_fraud_detection.git", "size_kb": 2645, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-08-16" }, "EllenLiu2019/bert-finetune": { "stars": 2, "desc": "This project fine-tunes BERT-base-uncased on a public claim detection dataset using the Hugging Face Transformers library. The goal is to classify whe", "url": "https://github.com/EllenLiu2019/bert-finetune.git", "size_kb": 619, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-10-25" }, "omnayak27199/Heart-Disease-Prediction-Using-Ensemble-learning-framwork-": { "stars": 2, "desc": "Nowadays cardiovascular disease is amidst of the leading ten sources for the growing rate of morbidity and mortality worldwide, affecting roughly 50% ", "url": "https://github.com/omnayak27199/Heart-Disease-Prediction-Using-Ensemble-learning-framwork-.git", "size_kb": 614, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2023-03-21" }, "pramodmgond/Insurance-Fraud-Claims-Detection--kaggle": { "stars": 1, "desc": "Kaggle dataset", "url": "https://github.com/pramodmgond/Insurance-Fraud-Claims-Detection--kaggle.git", "size_kb": 5921, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-11-19" }, "SudarshanGouda/Claim_Fraud_Detection-Imbalenced_Dataset-": { "stars": 1, "desc": "", "url": "https://github.com/SudarshanGouda/Claim_Fraud_Detection-Imbalenced_Dataset-.git", "size_kb": 527, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-08-12" }, "Wondet46/Auto-insurance-fraud-claim-dataset-with-dataset-types": { "stars": 1, "desc": "Ensemble models improves when the appropriate feature selection method implemented for detection of auto insurance frauds (imbalanced dataset). The a", "url": "https://github.com/Wondet46/Auto-insurance-fraud-claim-dataset-with-dataset-types.git", "size_kb": 994, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-09-14" }, "adithya-m-s-989/Insurance-Claim-Fraud-Detection": { "stars": 1, "desc": "A supervised ML project to detect fraudulent insurance claims using the insurance_claims.csv dataset. Models predict claim legitimacy based on claiman", "url": "https://github.com/adithya-m-s-989/Insurance-Claim-Fraud-Detection.git", "size_kb": 5399, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-05-11" }, "thayab136/Insurance-Claim-Fraud-Detection": { "stars": 1, "desc": "Problem Statement: Business case: Insurance fraud is a huge problem in the industry. It's difficult to identify fraud claims. Machine Learning is in ", "url": "https://github.com/thayab136/Insurance-Claim-Fraud-Detection.git", "size_kb": 863, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2021-12-26" }, "iNoBo/news_claim_analysis": { "stars": 1, "desc": "This is the repository containing the dataset introduced in the paper: \"Leveraging fine-tuned Large Language Models with LoRA for Effective Claim, Cla", "url": "https://github.com/iNoBo/news_claim_analysis.git", "size_kb": 2019, "q": "claim detection dataset", "lang": null, "pushed": "2024-04-09" }, "zulankm/Insurance-Fraud-Detection": { "stars": 1, "desc": "About this project :- The objective of the analysis is to identify if the claim is fraudulent or not? Dataset consists of several Variables(Independen", "url": "https://github.com/zulankm/Insurance-Fraud-Detection.git", "size_kb": 1386, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-07-30" }, "Medhaswini118/Greenwashing_Detection": { "stars": 1, "desc": "This project uses Artificial Intelligence and Machine Learning to detect greenwashing in corporate environmental claims.Machine learning models are th", "url": "https://github.com/Medhaswini118/Greenwashing_Detection.git", "size_kb": 67, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-09-07" }, "igorambrozini/Insurance_fraud_detection_many_classification_models": { "stars": 1, "desc": "This project focuses on detecting fraudulent auto insurance claims using different machine learning algorithms. The goal is to compare their performan", "url": "https://github.com/igorambrozini/Insurance_fraud_detection_many_classification_models.git", "size_kb": 3842, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-10-10" }, "AyushS1304/MetaJudge-AI": { "stars": 1, "desc": "A research-focused RAG pipeline for claim verification and hallucination detection an correction in AIML papers, evaluated against the SkepticBench da", "url": "https://github.com/AyushS1304/MetaJudge-AI.git", "size_kb": 1726, "q": "claim detection dataset", "lang": "Python", "pushed": "2026-05-03" }, "SayaliChabhare/Vehicle-Insurance-Fraud-Detection-ML-Model-": { "stars": 1, "desc": "Vehical Insurance Fraud Detection Project : The dataset consists of vehicle insurance records, identifying whether claims are fraudulent or legitimate", "url": "https://github.com/SayaliChabhare/Vehicle-Insurance-Fraud-Detection-ML-Model-.git", "size_kb": 1775, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-10-07" }, "kinit-sk/MultiCW": { "stars": 1, "desc": "This repository contains the code and datasets for the paper \"MultiCW - A Large-Scale Balanced Benchmark Dataset for Training Robust Check-Worthiness ", "url": "https://github.com/kinit-sk/MultiCW.git", "size_kb": 9944, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-01-22" }, "ntunlplab/Finance-ICRD": { "stars": 1, "desc": "There are two tasks in the ICRD. We separate the datasets into three parts, including Train/Dev/Test. (1) Premise Detection In the premise detection", "url": "https://github.com/ntunlplab/Finance-ICRD.git", "size_kb": 2, "q": "claim detection dataset", "lang": null, "pushed": "2022-05-31" }, "MinhajulKabirNishat/Healthcare-Fraud-Detection-Dataset": { "stars": 0, "desc": "Realistic medical insurance claims dataset with ICD-10, CPT codes. Main dataset containing all claim-level records and features.", "url": "https://github.com/MinhajulKabirNishat/Healthcare-Fraud-Detection-Dataset.git", "size_kb": 277, "q": "claim detection dataset", "lang": "Python", "pushed": "2026-05-11" }, "d3v1ll3n/persian-text-claim-detection": { "stars": 0, "desc": "Claim detection on a Persian dataset", "url": "https://github.com/d3v1ll3n/persian-text-claim-detection.git", "size_kb": 1861, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2023-08-14" }, "MobeenFatimaa/Insurance-Claim-Fraud-Detection-Dataset-Generator": { "stars": 0, "desc": "Synthetic dataset generator and 100k-row insurance claim dataset for machine learning, fraud detection, anomaly detection, and explainable AI (SHAP/LI", "url": "https://github.com/MobeenFatimaa/Insurance-Claim-Fraud-Detection-Dataset-Generator.git", "size_kb": 27, "q": "claim detection dataset", "lang": "Python", "pushed": "2026-08-17" }, "sruthisharma88/Insurance_claims_fraud_detection": { "stars": 0, "desc": "SOMTE analysis on an Imbalanced Insurance claim dataset", "url": "https://github.com/sruthisharma88/Insurance_claims_fraud_detection.git", "size_kb": 677, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-08-31" }, "Mehrab-Kalantari/Vehicle-Claim-Fraud-Detection": { "stars": 0, "desc": "Vehicle insurance claim fraud detection dataset analysis and modeling", "url": "https://github.com/Mehrab-Kalantari/Vehicle-Claim-Fraud-Detection.git", "size_kb": 1259, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2023-07-26" }, "MehrdadBN80/vehicle-Insurance_Claim_Fraud_Detection_dataset_classification": { "stars": 0, "desc": "", "url": "https://github.com/MehrdadBN80/vehicle-Insurance_Claim_Fraud_Detection_dataset_classification.git", "size_kb": 3576, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2023-05-21" }, "sapnasinha25/Fraudulent_Claim_Detection": { "stars": 0, "desc": "Fraudulent Claim Detection from a given dataset with application of Machine Learning technique", "url": "https://github.com/sapnasinha25/Fraudulent_Claim_Detection.git", "size_kb": 3073, "q": "claim detection dataset", "lang": null, "pushed": "2025-06-15" }, "ppal3297/Fraud-Detection-Challenge": { "stars": 0, "desc": "This dataset included policy holders personal, policy, claim, vehicle data and the task was to detect fraudulent claims from the given dataset.", "url": "https://github.com/ppal3297/Fraud-Detection-Challenge.git", "size_kb": 1855, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2019-05-08" }, "thrishikareddyp/claim-risk-profiler": { "stars": 0, "desc": "Fraud detection project using a synthetic insurance claims dataset", "url": "https://github.com/thrishikareddyp/claim-risk-profiler.git", "size_kb": 135, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-07-16" }, "OdinSword/Fraud-Detection-Challenge": { "stars": 0, "desc": "This dataset included policy holders personal, policy, claim, vehicle data and the task was to detect fraudulent claims from the given dataset", "url": "https://github.com/OdinSword/Fraud-Detection-Challenge.git", "size_kb": 1855, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2019-04-17" }, "vats1703/Insurance_Claim_Fraud_Detection": { "stars": 0, "desc": "Unsupervised Machine Learning Project to detect possible anomalies in unlabeled data from an insurance dataset", "url": "https://github.com/vats1703/Insurance_Claim_Fraud_Detection.git", "size_kb": 1189, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-04-18" }, "amit1998negi/insurance-fraud-detection-project": { "stars": 0, "desc": "It contains dataset to train and test claim frauds", "url": "https://github.com/amit1998negi/insurance-fraud-detection-project.git", "size_kb": 1779, "q": "claim detection dataset", "lang": null, "pushed": "2025-04-13" }, "nguyenha1311/insurance-claims-fraud-detection": { "stars": 0, "desc": "Detecting vehicle insurance claim fraud using EDA, SMOTE, and Logistic Regression classification on a Kaggle dataset.", "url": "https://github.com/nguyenha1311/insurance-claims-fraud-detection.git", "size_kb": 2811, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-05-29" }, "E-Chemweno/Fraud-Detection-Auto-Claims": { "stars": 0, "desc": "Analyzed auto claims dataset to detect fraud using logistic regression and tested the hypothesis that claims above $10k are fraudulent.", "url": "https://github.com/E-Chemweno/Fraud-Detection-Auto-Claims.git", "size_kb": 345, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-08-26" }, "BismaBRJ/car-claim-pred-fraud-cust-seg": { "stars": 0, "desc": "Claim prediction, fraud detection, and customer segmentation using the \"Vehicle Insurance Fraud Detection\" Kaggle dataset", "url": "https://github.com/BismaBRJ/car-claim-pred-fraud-cust-seg.git", "size_kb": 327, "q": "claim detection dataset", "lang": null, "pushed": "2025-10-20" }, "sankeerthsunnapu/medicare-fraud-detection": { "stars": 0, "desc": "Machine Learning project for detecting fraudulent healthcare providers using Medicare claim datasets.", "url": "https://github.com/sankeerthsunnapu/medicare-fraud-detection.git", "size_kb": 27292, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-05-26" }, "Himanshusharma1005/Claims-AI-Processor": { "stars": 0, "desc": "98%+ Accurate Car Damage Detection using YOLOv8 fine-tuned on the CARDD Dataset", "url": "https://github.com/Himanshusharma1005/Claims-AI-Processor.git", "size_kb": 20890, "q": "claim detection dataset", "lang": null, "pushed": "2025-11-02" }, "pegah81/Vehicle-Insurance-Fraud-Detection": { "stars": 0, "desc": "CS-SBU-2023 | Applying Fraud Detection on the Vehicle Insurance Claim dataset.", "url": "https://github.com/pegah81/Vehicle-Insurance-Fraud-Detection.git", "size_kb": 1813, "q": "claim detection dataset", "lang": null, "pushed": "2023-06-03" }, "Ankush1902/Fraudulent_Claim_Detection": { "stars": 0, "desc": "This project uses machine learning to detect fraudulent automobile insurance claims. The Jupyter Notebook analyzes an imbalanced dataset, processes fe", "url": "https://github.com/Ankush1902/Fraudulent_Claim_Detection.git", "size_kb": 534, "q": "claim detection dataset", "lang": null, "pushed": "2025-08-02" }, "BlazedLith/Fraud-Claim-Detection": { "stars": 0, "desc": "A machine learning project that detects potentially fraudulent insurance claims in real time using a cleaned and engineered insurance dataset, class i", "url": "https://github.com/BlazedLith/Fraud-Claim-Detection.git", "size_kb": 4858, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-12-04" }, "charanvarma0703/fraud-insurance-claim-detection": { "stars": 0, "desc": "Developed a predictive model to identify individuals at risk of heart disease using machine learning algorithms. Utilized a dataset containing medica ", "url": "https://github.com/charanvarma0703/fraud-insurance-claim-detection.git", "size_kb": 463, "q": "claim detection dataset", "lang": null, "pushed": "2025-03-21" }, "mofatima/healthcare-claims-fraud-detection": { "stars": 0, "desc": "Fraud & upcoding detection for healthcare claims using Random Forest and XGBoost, with a Streamlit app for real-time claim risk scoring and revenue-in", "url": "https://github.com/mofatima/healthcare-claims-fraud-detection.git", "size_kb": 5221, "q": "claim detection dataset", "lang": "Python", "pushed": "2026-07-15" }, "4i4shan/Vehicle-Insurance-Claim-Fraud-Detection": { "stars": 0, "desc": "End-to-end vehicle insurance claim fraud detection using XGBoost, Random Forest & Logistic Regression with SMOTE \u2014 achieves high recall on a heavily i", "url": "https://github.com/4i4shan/Vehicle-Insurance-Claim-Fraud-Detection.git", "size_kb": 1116, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-03-19" }, "ShaikhBorhanUddin/Vehicle-Insurance-Claim-Fraud-Detection": { "stars": 0, "desc": "A publicly available dataset was utilized, and various machine learning algorithms were applied. The final deliverables include a comparative analysis", "url": "https://github.com/ShaikhBorhanUddin/Vehicle-Insurance-Claim-Fraud-Detection.git", "size_kb": 4515, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-04-28" }, "Nikhilnike1607/Insurance-claims-fraud-detection": { "stars": 0, "desc": "Utilized 8 supervised machine learning models in python to compare the accuracy of all models. This dataset has historical insurance claims and wants ", "url": "https://github.com/Nikhilnike1607/Insurance-claims-fraud-detection.git", "size_kb": 595, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-07-01" }, "Horizon-Truth/horizon-truth-misinformation-dataset": { "stars": 0, "desc": "A curated Ethiopian-context dataset of misinformation claims designed for fact-checking, research, and AI-based misinformation detection.", "url": "https://github.com/Horizon-Truth/horizon-truth-misinformation-dataset.git", "size_kb": 507, "q": "claim detection dataset", "lang": null, "pushed": "2026-08-08" }, "Vaishurajdata/Insurance-_Claims-Fraud-Detections-1843": { "stars": 0, "desc": "In this project, you are provided a dataset which has the details of the insurance policy along with the customer details. It also has the details of ", "url": "https://github.com/Vaishurajdata/Insurance-_Claims-Fraud-Detections-1843.git", "size_kb": 563, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-10-12" }, "singhkpratham/Fraud_Detection_R_D3": { "stars": 0, "desc": "A project to flag the fraudulent claims in insurance sector. Automate the creation of analytical dataset (ADS), cleaning it and then predicting the fr", "url": "https://github.com/singhkpratham/Fraud_Detection_R_D3.git", "size_kb": 1474, "q": "claim detection dataset", "lang": "R", "pushed": "2017-01-27" }, "abdumajid-nabiev/Insurance-Fraud-Detection": { "stars": 0, "desc": "This project aims to detect fraudulent insurance claims using machine learning techniques. The model is trained on a dataset of insurance claims to id", "url": "https://github.com/abdumajid-nabiev/Insurance-Fraud-Detection.git", "size_kb": 1622, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2024-09-10" }, "adibhattar95/Fraud-Claim-Detection-in-Travel-Insurance": { "stars": 0, "desc": "The objective was to identify claims which were likely to be rejected by the Travel Insurance Company. A Binary Class classification problem. Dataset ", "url": "https://github.com/adibhattar95/Fraud-Claim-Detection-in-Travel-Insurance.git", "size_kb": 174, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2020-03-23" }, "deepakshimathur06/Insurance-Fraud-Detection-using-Machine-Learning": { "stars": 0, "desc": "This project aims to detect fraudulent insurance claims using supervised machine learning models. The dataset contains historical insurance claim reco", "url": "https://github.com/deepakshimathur06/Insurance-Fraud-Detection-using-Machine-Learning.git", "size_kb": 821, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-05-10" }, "innovatiana/innovatiana-chanel-dataset-for-fraud-detection": { "stars": 0, "desc": "This dataset contains a curated collection of images of Chanel products gathered from various online sources, irrespective of their legitimacy. The ri", "url": "https://github.com/innovatiana/innovatiana-chanel-dataset-for-fraud-detection.git", "size_kb": 3174387, "q": "claim detection dataset", "lang": null, "pushed": "2024-07-12" }, "rahulsr2001/Fraud_Detection": { "stars": 0, "desc": "This classification dataset aims to identify fraudulent insurance claims. The XGBoost model achieved a high accuracy of 95%, leveraging features like ", "url": "https://github.com/rahulsr2001/Fraud_Detection.git", "size_kb": 1406, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-01-06" }, "FarahAnanda/fraud-detection-analytics": { "stars": 0, "desc": "Fraud detection analysis using fraudulent claims dataset to develop an effective model for detecting fraud while minimizing costs.", "url": "https://github.com/FarahAnanda/fraud-detection-analytics.git", "size_kb": 1050, "q": "claim detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-03-02" }, "Gautamshahi/FakeCovid": { "stars": 37, "desc": "FakeCovid- A Multilingual Cross-domain Fact Check News Dataset for COVID-19", "url": "https://github.com/Gautamshahi/FakeCovid.git", "size_kb": 39927, "q": "misinformation dataset multilingual", "lang": "Jupyter Notebook", "pushed": "2022-09-08" }, "Pkorirdarius/Nlp_model": { "stars": 1, "desc": "An AI-powered, multilingual NLP application designed to detect and debunk misinformation about genetically modified organisms (GMOs), specifically tar", "url": "https://github.com/Pkorirdarius/Nlp_model.git", "size_kb": 337, "q": "misinformation dataset multilingual", "lang": "Jupyter Notebook", "pushed": "2026-03-12" }, "Neitikjangra/Multilingual-Fake-News-Detection-System": { "stars": 1, "desc": "An end-to-end NLP and Machine Learning project for fake news detection using TF-IDF and Logistic Regression, featuring a complete training pipeline, e", "url": "https://github.com/Neitikjangra/Multilingual-Fake-News-Detection-System.git", "size_kb": 4462, "q": "misinformation dataset multilingual", "lang": "Python", "pushed": "2025-12-29" }, "LanD-FBK/EuroVerdict": { "stars": 0, "desc": "Codes and data for \"EuroVerdict: A Multilingual Dataset for Verdict Generation Against Misinformation\"", "url": "https://github.com/LanD-FBK/EuroVerdict.git", "size_kb": 7844, "q": "misinformation dataset multilingual", "lang": "Python", "pushed": "2025-07-24" }, "generalaimodels/Cross-Lingual-Misinformation-Detection": { "stars": 0, "desc": "Develop a model capable of identifying misinformation in multilingual texts using open-source datasets from social media platforms", "url": "https://github.com/generalaimodels/Cross-Lingual-Misinformation-Detection.git", "size_kb": 9, "q": "misinformation dataset multilingual", "lang": "Python", "pushed": "2024-10-24" }, "wuyoscar/VESKI_Colab_Research_Project.": { "stars": 0, "desc": "A multilingual research initiative detecting, classifying & countering COVID-19 misinformation on social media through AI-driven tools, open datasets ", "url": "https://github.com/wuyoscar/VESKI_Colab_Research_Project..git", "size_kb": 858, "q": "misinformation dataset multilingual", "lang": null, "pushed": "2025-06-03" }, "rajatrajan03/multilingual-indic-factcheck-model": { "stars": 0, "desc": "Multilingual fact-checking model for Indic languages (Hindi, Nepali, Punjabi, Tamil, Telugu, Urdu) with adversarial attack and defense evaluation", "url": "https://github.com/rajatrajan03/multilingual-indic-factcheck-model.git", "size_kb": 28313, "q": "fact checking indic", "lang": "Python", "pushed": "2026-08-11" }, "Shaun2h/BERT-ISBERT-SBERT_RumourDetection": { "stars": 0, "desc": "BERT, ISBERT, SBERT as rumour detection baselines on PHEME dataset. Also on Indonesian Disinfo dataset. README for details.", "url": "https://github.com/Shaun2h/BERT-ISBERT-SBERT_RumourDetection.git", "size_kb": 17266, "q": "rumour detection dataset", "lang": "Python", "pushed": "2022-05-15" }, "Raghvendra-14/Multimodal-Rumour-Detection": { "stars": 0, "desc": "Dataset Released", "url": "https://github.com/Raghvendra-14/Multimodal-Rumour-Detection.git", "size_kb": 3, "q": "rumour detection dataset", "lang": null, "pushed": "2023-09-12" }, "Devarsh26/automatic-twitter-rumour-detection": { "stars": 0, "desc": "Rumour Detection using PHEME Dataset", "url": "https://github.com/Devarsh26/automatic-twitter-rumour-detection.git", "size_kb": 1788, "q": "rumour detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-10-24" }, "shaswatpatel123/rumour_detection": { "stars": 0, "desc": "Rumour detection using graph neural network and oversampling in benchmark Twitter dataset", "url": "https://github.com/shaswatpatel123/rumour_detection.git", "size_kb": 369, "q": "rumour detection dataset", "lang": "Jupyter Notebook", "pushed": "2025-03-04" }, "mariandc18/RumoursRumours": { "stars": 0, "desc": "Rumour detection on the PHEME dataset using traditional Machine Learning and Feature Engineering, without explicit textual content.", "url": "https://github.com/mariandc18/RumoursRumours.git", "size_kb": 9581, "q": "rumour detection dataset", "lang": "Jupyter Notebook", "pushed": "2026-01-23" }, "harsha2225/Rumour_Stance_Detection_Pheme9_Dataset": { "stars": 0, "desc": "", "url": "https://github.com/harsha2225/Rumour_Stance_Detection_Pheme9_Dataset.git", "size_kb": 69238, "q": "rumour detection dataset", "lang": "Python", "pushed": "2022-01-06" }, "samriddhisv/Rumour-Detection-and-Analysis-on-Twitter-Dataset": { "stars": 0, "desc": "", "url": "https://github.com/samriddhisv/Rumour-Detection-and-Analysis-on-Twitter-Dataset.git", "size_kb": 967, "q": "rumour detection dataset", "lang": "Jupyter Notebook", "pushed": "2022-12-11" }, "nsksai6/Rumour_RVNN": { "stars": 0, "desc": "This repository contains details of my Term Project Rumour Detection On PHEME-RNR Dataset", "url": "https://github.com/nsksai6/Rumour_RVNN.git", "size_kb": 5687, "q": "rumour detection dataset", "lang": "Python", "pushed": "2022-01-24" }, "hsiuchi77/Rumour_detectmodel_based_on_gat": { "stars": 0, "desc": "rumour detection mode with Bert, ResNet-50 and GAT,use PHEME dataset", "url": "https://github.com/hsiuchi77/Rumour_detectmodel_based_on_gat.git", "size_kb": 25, "q": "rumour detection dataset", "lang": "Python", "pushed": "2026-03-21" }, "HaizeaRL/FEDERATED_RUMOUR_GRAPH_LEARNING": { "stars": 0, "desc": "This repository pretend to be a prototype of how a federated learning framework can be used for rumor detection using graph-based analysis of the PHEM", "url": "https://github.com/HaizeaRL/FEDERATED_RUMOUR_GRAPH_LEARNING.git", "size_kb": 74, "q": "rumour detection dataset", "lang": "Python", "pushed": "2024-12-06" }, "LeadingIndiaAI/Development-and-Analysis-of-a-Neural-Network-Based-Model-for-Detection-of-Rumours": { "stars": 0, "desc": "Since the first RumourEval shared task in 2017, interest in automated claim validation has greatly increased, as the danger of \u201cfake news\u201d has become ", "url": "https://github.com/LeadingIndiaAI/Development-and-Analysis-of-a-Neural-Network-Based-Model-for-Detection-of-Rumours.git", "size_kb": 18073, "q": "rumour detection dataset", "lang": "Jupyter Notebook", "pushed": "2019-07-01" }, "Chriskuei/GERE": { "stars": 20, "desc": "SIGIR 2022: GERE: Generative Evidence Retrieval for Fact Verification", "url": "https://github.com/Chriskuei/GERE.git", "size_kb": 71996, "q": "evidence retrieval fact verification", "lang": "Python", "pushed": "2022-07-19" }, "qshi95/LERGV": { "stars": 8, "desc": "Code for EMNLP2021 paper \u201cLogic-level Evidence Retrieval and Graph-based Verification Network for Table-based Fact Verification\u201d", "url": "https://github.com/qshi95/LERGV.git", "size_kb": 54, "q": "evidence retrieval fact verification", "lang": "Python", "pushed": "2022-01-24" }, "Namronaldo08102004/Vietfactcheck": { "stars": 2, "desc": "An NLP-powered fact-checking system designed to verify Vietnamese news and combat misinformation through claim detection, evidence retrieval, and auto", "url": "https://github.com/Namronaldo08102004/Vietfactcheck.git", "size_kb": 417333, "q": "evidence retrieval fact verification", "lang": "Python", "pushed": "2026-02-10" }, "kabrashrey/hallucination_resistant_multihop_qna": { "stars": 2, "desc": "Large language models tend to provide incorrect answers, known as hallucinations. This project will explore techniques for evidence retrieval, fact ve", "url": "https://github.com/kabrashrey/hallucination_resistant_multihop_qna.git", "size_kb": 71537, "q": "evidence retrieval fact verification", "lang": "Python", "pushed": "2026-04-26" }, "vishwjeet71/VeritasAI": { "stars": 1, "desc": "AI-powered fact verification system that analyzes claims using evidence retrieval, semantic search, and LLM reasoning.", "url": "https://github.com/vishwjeet71/VeritasAI.git", "size_kb": 3384, "q": "evidence retrieval fact verification", "lang": "Python", "pushed": "2026-07-15" }, "zyinghua/bert-for-climate-fever": { "stars": 1, "desc": "A BERT based system for Climate Fact Extration and VERification. 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