{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/fact-checking/papers/5","list_of":"/task/fact-checking","task":"Fact Checking","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":5,"pages_in_order":7,"rows_per_page":100,"rows":[401,500],"of":669,"counts":{"archive_papers_tagged":669,"with_a_code_link":297,"where_syntology_ran_a_sample":67,"not_listed_spam_title":0,"listed":669,"listed_where_code_ran":67,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":51,"every_run_a_failure_of_syntologys_instrument":16,"listed_with_a_run_with_no_instrument_failure":51,"listed_every_run_a_failure_of_syntologys_instrument":16,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/fact-checking","prev":"/task/fact-checking/papers/4","next":"/task/fact-checking/papers/6","papers":[{"url":null,"slug":"are-large-vision-language-models-up-to-the","title":"Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning? An Extensive Investigation into the Capabilities and Limitations of LVLMs","date":"2024-06-01","arxiv_id":"2406.00257","repositories_listed":0,"syntology":null},{"url":null,"slug":"exu-ai-models-for-examining-multilingual","title":"ExU: AI Models for Examining Multilingual Disinformation Narratives and Understanding their Spread","date":"2024-05-30","arxiv_id":"2406.15443","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-impact-and-opportunities-of-generative-ai","title":"The Impact and Opportunities of Generative AI in Fact-Checking","date":"2024-05-24","arxiv_id":"2405.15985","repositories_listed":0,"syntology":null},{"url":null,"slug":"mining-the-explainability-and-generalization","title":"Mining the Explainability and Generalization: Fact Verification Based on Self-Instruction","date":"2024-05-21","arxiv_id":"2405.12579","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-news-generation-and-fact-checking","title":"Automatic News Generation and Fact-Checking System Based on Language Processing","date":"2024-05-17","arxiv_id":"2405.10492","repositories_listed":0,"syntology":null},{"url":null,"slug":"syndy-synthetic-dynamic-dataset-generation","title":"SynDy: Synthetic Dynamic Dataset Generation Framework for Misinformation Tasks","date":"2024-05-17","arxiv_id":"2405.10700","repositories_listed":0,"syntology":null},{"url":null,"slug":"viwikifc-fact-checking-for-vietnamese","title":"ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source","date":"2024-05-13","arxiv_id":"2405.07615","repositories_listed":0,"syntology":null},{"url":null,"slug":"new-contexts-old-heuristics-how-young-people","title":"New contexts, old heuristics: How young people in India and the US trust online content in the age of generative AI","date":"2024-05-03","arxiv_id":"2405.02522","repositories_listed":0,"syntology":null},{"url":null,"slug":"factcheck-editor-multilingual-text-editor","title":"FactCheck Editor: Multilingual Text Editor with End-to-End fact-checking","date":"2024-04-30","arxiv_id":"2404.19482","repositories_listed":0,"syntology":null},{"url":null,"slug":"reprohum-0087-01-human-evaluation","title":"ReproHum #0087-01: Human Evaluation Reproduction Report for Generating Fact Checking Explanations","date":"2024-04-26","arxiv_id":"2404.17481","repositories_listed":0,"syntology":null},{"url":null,"slug":"kgvalidator-a-framework-for-automatic","title":"KGValidator: A Framework for Automatic Validation of Knowledge Graph Construction","date":"2024-04-24","arxiv_id":"2404.15923","repositories_listed":0,"syntology":null},{"url":null,"slug":"claim-check-worthiness-detection-how-well-do","title":"Claim Check-Worthiness Detection: How Well do LLMs Grasp Annotation Guidelines?","date":"2024-04-18","arxiv_id":"2404.12174","repositories_listed":0,"syntology":null},{"url":null,"slug":"ragar-your-falsehood-radar-rag-augmented","title":"RAGAR, Your Falsehood Radar: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models","date":"2024-04-18","arxiv_id":"2404.12065","repositories_listed":0,"syntology":null},{"url":null,"slug":"collaboratively-adding-context-to-social","title":"Collaboratively adding context to social media posts reduces the sharing of false news","date":"2024-04-03","arxiv_id":"2404.02803","repositories_listed":0,"syntology":null},{"url":null,"slug":"mcfend-a-multi-source-benchmark-dataset-for","title":"MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection","date":"2024-03-14","arxiv_id":"2403.09092","repositories_listed":0,"syntology":null},{"url":null,"slug":"claimver-explainable-claim-level-verification","title":"ClaimVer: Explainable Claim-Level Verification and Evidence Attribution of Text Through Knowledge Graphs","date":"2024-03-12","arxiv_id":"2403.09724","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-large-language-models-to-support","title":"Multimodal Large Language Models to Support Real-World Fact-Checking","date":"2024-03-06","arxiv_id":"2403.03627","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-multilingual-fact-checking-at","title":"Surprising Efficacy of Fine-Tuned Transformers for Fact-Checking over Larger Language Models","date":"2024-02-19","arxiv_id":"2402.12147","repositories_listed":0,"syntology":null},{"url":null,"slug":"genaudit-fixing-factual-errors-in-language","title":"GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence","date":"2024-02-19","arxiv_id":"2402.12566","repositories_listed":0,"syntology":null},{"url":null,"slug":"repetitive-dilemma-games-in-distribution","title":"Repetitive Dilemma Games in Distribution Information Using Interplay of Droop Quota: Meek's Method in Impact of Maximum Compensation and Minimum Cost Routes in Information Role of Marginal Contribution in Two-Sided Matching Markets","date":"2024-02-19","arxiv_id":"2403.18837","repositories_listed":0,"syntology":null},{"url":null,"slug":"tables-as-images-exploring-the-strengths-and","title":"Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMs","date":"2024-02-19","arxiv_id":"2402.12424","repositories_listed":0,"syntology":null},{"url":null,"slug":"entanglement-balancing-punishment-and","title":"Entanglement: Balancing Punishment and Compensation, Repeated Dilemma Game-Theoretic Analysis of Maximum Compensation Problem for Bypass and Least Cost Paths in Fact-Checking, Case of Fake News with Weak Wallace's Law","date":"2024-02-18","arxiv_id":"2403.02342","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-llms-produce-faithful-explanations-for","title":"Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate","date":"2024-02-12","arxiv_id":"2402.07401","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-knowledge-sources-for-open-domain","title":"Comparing Knowledge Sources for Open-Domain Scientific Claim Verification","date":"2024-02-05","arxiv_id":"2402.02844","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-bayesian-multi-perspective","title":"eXplainable Bayesian Multi-Perspective Generative Retrieval","date":"2024-02-04","arxiv_id":"2402.02418","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-makes-medical-claims-un-verifiable","title":"What Makes Medical Claims (Un)Verifiable? Analyzing Entity and Relation Properties for Fact Verification","date":"2024-02-02","arxiv_id":"2402.01360","repositories_listed":0,"syntology":null},{"url":null,"slug":"diverse-but-divisive-llms-can-exaggerate","title":"Diverse, but Divisive: LLMs Can Exaggerate Gender Differences in Opinion Related to Harms of Misinformation","date":"2024-01-29","arxiv_id":"2401.16558","repositories_listed":0,"syntology":null},{"url":null,"slug":"maple-micro-analysis-of-pairwise-language","title":"MAPLE: Micro Analysis of Pairwise Language Evolution for Few-Shot Claim Verification","date":"2024-01-29","arxiv_id":"2401.16282","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-gender-bias-in-large-language","title":"Evaluating Gender Bias in Large Language Models via Chain-of-Thought Prompting","date":"2024-01-28","arxiv_id":"2401.15585","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-we-need-language-specific-fact-checking","title":"Do We Need Language-Specific Fact-Checking Models? The Case of Chinese","date":"2024-01-27","arxiv_id":"2401.15498","repositories_listed":0,"syntology":null},{"url":null,"slug":"ta-keed-the-first-generative-fact-checking","title":"Ta'keed: The First Generative Fact-Checking System for Arabic Claims","date":"2024-01-25","arxiv_id":"2401.14067","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-fact-checking-of-climate-change","title":"Automated Fact-Checking of Climate Change Claims with Large Language Models","date":"2024-01-23","arxiv_id":"2401.12566","repositories_listed":0,"syntology":null},{"url":null,"slug":"claim-detection-for-automated-fact-checking-a","title":"Claim Detection for Automated Fact-checking: A Survey on Monolingual, Multilingual and Cross-Lingual Research","date":"2024-01-22","arxiv_id":"2401.11969","repositories_listed":0,"syntology":null},{"url":null,"slug":"fact-checking-based-fake-news-detection-a","title":"Fact-checking based fake news detection: a review","date":"2024-01-03","arxiv_id":"2401.01717","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-revisit-of-fake-news-dataset-with-augmented","title":"A Revisit of Fake News Dataset with Augmented Fact-checking by ChatGPT","date":"2023-12-19","arxiv_id":"2312.11870","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-fact-checking-with-semantic-triples","title":"Zero-Shot Fact-Checking with Semantic Triples and Knowledge Graphs","date":"2023-12-19","arxiv_id":"2312.11785","repositories_listed":0,"syntology":null},{"url":null,"slug":"evidence-based-interpretable-open-domain-fact","title":"Evidence-based Interpretable Open-domain Fact-checking with Large Language Models","date":"2023-12-10","arxiv_id":"2312.05834","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-large-language-models-good-fact-checkers","title":"Are Large Language Models Good Fact Checkers: A Preliminary Study","date":"2023-11-29","arxiv_id":"2311.17355","repositories_listed":0,"syntology":null},{"url":null,"slug":"exfake-towards-an-explainable-fake-news","title":"ExFake: Towards an Explainable Fake News Detection Based on Content and Social Context Information","date":"2023-11-16","arxiv_id":"2311.10784","repositories_listed":0,"syntology":null},{"url":null,"slug":"online-continual-knowledge-learning-for","title":"Online Continual Knowledge Learning for Language Models","date":"2023-11-16","arxiv_id":"2311.09632","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-fact-checking-in-dialogue-are","title":"Automated Fact-Checking in Dialogue: Are Specialized Models Needed?","date":"2023-11-14","arxiv_id":"2311.08195","repositories_listed":0,"syntology":null},{"url":null,"slug":"fine-tuning-language-models-for-factuality","title":"Fine-tuning Language Models for Factuality","date":"2023-11-14","arxiv_id":"2311.08401","repositories_listed":0,"syntology":null},{"url":null,"slug":"trusted-source-alignment-in-large-language","title":"Trusted Source Alignment in Large Language Models","date":"2023-11-12","arxiv_id":"2311.06697","repositories_listed":0,"syntology":null},{"url":null,"slug":"lost-in-translation-multilingual","title":"Lost in Translation -- Multilingual Misinformation and its Evolution","date":"2023-10-27","arxiv_id":"2310.18089","repositories_listed":0,"syntology":null},{"url":null,"slug":"right-no-matter-why-ai-fact-checking-and-ai","title":"Right, No Matter Why: AI Fact-checking and AI Authority in Health-related Inquiry Settings","date":"2023-10-22","arxiv_id":"2310.14358","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-perils-promises-of-fact-checking-with","title":"The Perils & Promises of Fact-checking with Large Language Models","date":"2023-10-20","arxiv_id":"2310.13549","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-language-models-help-humans-verify","title":"Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong","date":"2023-10-19","arxiv_id":"2310.12558","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-claim-matching-with-large-language","title":"Automated Claim Matching with Large Language Models: Empowering Fact-Checkers in the Fight Against Misinformation","date":"2023-10-13","arxiv_id":"2310.09223","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-based-knowledge-graph","title":"Reinforcement Learning-based Knowledge Graph Reasoning for Explainable Fact-checking","date":"2023-10-11","arxiv_id":"2310.07613","repositories_listed":0,"syntology":null},{"url":null,"slug":"autohall-automated-hallucination-dataset","title":"AutoHall: Automated Hallucination Dataset Generation for Large Language Models","date":"2023-09-30","arxiv_id":"2310.00259","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-condition-and-generate-classification","title":"Prompt, Condition, and Generate: Classification of Unsupported Claims with In-Context Learning","date":"2023-09-19","arxiv_id":"2309.10359","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-social-discourse-to-measure-check","title":"Leveraging Social Discourse to Measure Check-worthiness of Claims for Fact-checking","date":"2023-09-17","arxiv_id":"2309.09274","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-news-bias-misspecifications-and","title":"Learning Source Biases: Multisource Misspecifications and Their Impact on Predictions","date":"2023-09-15","arxiv_id":"2309.08740","repositories_listed":0,"syntology":null},{"url":null,"slug":"zero-shot-audio-topic-reranking-using-large","title":"Zero-shot Audio Topic Reranking using Large Language Models","date":"2023-09-14","arxiv_id":"2309.07606","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-of-disinformation-and-fake-news","title":"Analysis of Disinformation and Fake News Detection Using Fine-Tuned Large Language Model","date":"2023-09-09","arxiv_id":"2309.04704","repositories_listed":0,"syntology":null},{"url":null,"slug":"factllama-optimizing-instruction-following","title":"FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking","date":"2023-09-01","arxiv_id":"2309.00240","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-centered-nlp-fact-checking-co-designing","title":"Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI","date":"2023-08-14","arxiv_id":"2308.07213","repositories_listed":0,"syntology":null},{"url":null,"slug":"mind-your-language-model-fact-checking-llms","title":"Position: Key Claims in LLM Research Have a Long Tail of Footnotes","date":"2023-08-14","arxiv_id":"2308.07120","repositories_listed":0,"syntology":null},{"url":null,"slug":"finding-already-debunked-narratives-via","title":"Breaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checking","date":"2023-08-10","arxiv_id":"2308.05680","repositories_listed":0,"syntology":null},{"url":null,"slug":"establishing-trust-in-chatgpt-biomedical","title":"Fact-Checking Generative AI: Ontology-Driven Biological Graphs for Disease-Gene Link Verification","date":"2023-08-07","arxiv_id":"2308.03929","repositories_listed":0,"syntology":null},{"url":null,"slug":"fact-checking-of-ai-generated-reports","title":"Fact-Checking of AI-Generated Reports","date":"2023-07-27","arxiv_id":"2307.14634","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-vs-google-a-comparative-study-of","title":"ChatGPT vs. Google: A Comparative Study of Search Performance and User Experience","date":"2023-07-03","arxiv_id":"2307.01135","repositories_listed":0,"syntology":null},{"url":null,"slug":"fraunhofer-sit-at-checkthat-2023-tackling","title":"Fraunhofer SIT at CheckThat! 2023: Tackling Classification Uncertainty Using Model Souping on the Example of Check-Worthiness Classification","date":"2023-07-03","arxiv_id":"2307.02377","repositories_listed":0,"syntology":null},{"url":null,"slug":"fraunhofer-sit-at-checkthat-2023-mixing","title":"Fraunhofer SIT at CheckThat! 2023: Mixing Single-Modal Classifiers to Estimate the Check-Worthiness of Multi-Modal Tweets","date":"2023-07-02","arxiv_id":"2307.00610","repositories_listed":0,"syntology":null},{"url":null,"slug":"hallucination-is-the-last-thing-you-need","title":"Hallucination is the last thing you need","date":"2023-06-20","arxiv_id":"2306.11520","repositories_listed":0,"syntology":null},{"url":null,"slug":"news-verifiers-showdown-a-comparative","title":"News Verifiers Showdown: A Comparative Performance Evaluation of ChatGPT 3.5, ChatGPT 4.0, Bing AI, and Bard in News Fact-Checking","date":"2023-06-18","arxiv_id":"2306.17176","repositories_listed":0,"syntology":null},{"url":null,"slug":"scientific-fact-checking-a-survey-of","title":"Scientific Fact-Checking: A Survey of Resources and Approaches","date":"2023-05-26","arxiv_id":"2305.16859","repositories_listed":0,"syntology":null},{"url":null,"slug":"give-me-more-details-improving-fact-checking","title":"Give Me More Details: Improving Fact-Checking with Latent Retrieval","date":"2023-05-25","arxiv_id":"2305.16128","repositories_listed":0,"syntology":null},{"url":null,"slug":"sail-search-augmented-instruction-learning","title":"SAIL: Search-Augmented Instruction Learning","date":"2023-05-24","arxiv_id":"2305.15225","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-graphs-querying","title":"Knowledge Graphs Querying","date":"2023-05-23","arxiv_id":"2305.14485","repositories_listed":0,"syntology":null},{"url":null,"slug":"manitweet-a-new-benchmark-for-identifying","title":"ManiTweet: A New Benchmark for Identifying Manipulation of News on Social Media","date":"2023-05-23","arxiv_id":"2305.14225","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-history-with-ai-a-comparative","title":"Bridging History with AI A Comparative Evaluation of GPT 3.5, GPT4, and GoogleBARD in Predictive Accuracy and Fact Checking","date":"2023-05-13","arxiv_id":"2305.07868","repositories_listed":0,"syntology":null},{"url":null,"slug":"factify-5wqa-5w-aspect-based-fact","title":"FACTIFY-5WQA: 5W Aspect-based Fact Verification through Question Answering","date":"2023-05-07","arxiv_id":"2305.04329","repositories_listed":0,"syntology":null},{"url":null,"slug":"toxic-comments-reduce-the-activity-of","title":"Toxic comments reduce the activity of volunteer editors on Wikipedia","date":"2023-04-26","arxiv_id":"2304.13568","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-multiple-rdf-knowledge-graphs-for","title":"Using Multiple RDF Knowledge Graphs for Enriching ChatGPT Responses","date":"2023-04-12","arxiv_id":"2304.05774","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-entity-based-claim-extraction-pipeline-for","title":"An Entity-based Claim Extraction Pipeline for Real-world Biomedical Fact-checking","date":"2023-04-11","arxiv_id":"2304.05268","repositories_listed":0,"syntology":null},{"url":null,"slug":"panacea-an-automated-misinformation-detection","title":"PANACEA: An Automated Misinformation Detection System on COVID-19","date":"2023-02-28","arxiv_id":"2303.01241","repositories_listed":0,"syntology":null},{"url":null,"slug":"reading-and-reasoning-over-chart-images-for","title":"Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking","date":"2023-01-27","arxiv_id":"2301.11843","repositories_listed":0,"syntology":null},{"url":null,"slug":"logically-at-factify-2023-a-multi-modal-fact","title":"Logically at Factify 2: A Multi-Modal Fact Checking System Based on Evidence Retrieval techniques and Transformer Encoder Architecture","date":"2023-01-09","arxiv_id":"2301.03127","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-state-of-human-centered-nlp-technology","title":"The State of Human-centered NLP Technology for Fact-checking","date":"2023-01-08","arxiv_id":"2301.03056","repositories_listed":0,"syntology":null},{"url":null,"slug":"check-worthy-claim-detection-across-topics","title":"Check-worthy Claim Detection across Topics for Automated Fact-checking","date":"2022-12-16","arxiv_id":"2212.08514","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-modality-level-explainable-framework-for","title":"A Modality-level Explainable Framework for Misinformation Checking in Social Networks","date":"2022-12-08","arxiv_id":"2212.04272","repositories_listed":0,"syntology":null},{"url":null,"slug":"climedbert-a-pre-trained-language-model-for","title":"CliMedBERT: A Pre-trained Language Model for Climate and Health-related Text","date":"2022-12-01","arxiv_id":"2212.00689","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-not-automatic-needs-and-practices","title":"Autonomation, not Automation: Activities and Needs of Fact-checkers as a Basis for Designing Human-Centered AI Systems","date":"2022-11-22","arxiv_id":"2211.12143","repositories_listed":0,"syntology":null},{"url":null,"slug":"did-they-really-tweet-that-querying-fact","title":"Did They Really Tweet That? Querying Fact-Checking Sites and Politwoops to Determine Tweet Misattribution","date":"2022-11-17","arxiv_id":"2211.09681","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-lingual-transfer-learning-for-check","title":"Cross-lingual Transfer Learning for Check-worthy Claim Identification over Twitter","date":"2022-11-09","arxiv_id":"2211.05087","repositories_listed":0,"syntology":null},{"url":"/paper/stanceosaurus-classifying-stance-towards","slug":"stanceosaurus-classifying-stance-towards","title":"Stanceosaurus: Classifying Stance Towards Multilingual Misinformation","date":"2022-10-28","arxiv_id":"2210.15954","repositories_listed":0,"syntology":null},{"url":"/paper/modeling-information-change-in-science","slug":"modeling-information-change-in-science","title":"Modeling Information Change in Science Communication with Semantically Matched Paraphrases","date":"2022-10-24","arxiv_id":"2210.13001","repositories_listed":0,"syntology":null},{"url":null,"slug":"mitigating-the-diminishing-effect-of-elastic","title":"Mitigating the Diminishing Effect of Elastic Weight Consolidation","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-based-claim-representation-improves","title":"Entity-based Claim Representation Improves Fact-Checking of Medical Content in Tweets","date":"2022-09-16","arxiv_id":"2209.07834","repositories_listed":0,"syntology":null},{"url":null,"slug":"graphical-models-of-false-information-and","title":"Graphical Models of False Information and Fact Checking Ecosystems","date":"2022-08-24","arxiv_id":"2208.11582","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-pets-active-data-annotation","title":"Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training","date":"2022-08-18","arxiv_id":"2208.08749","repositories_listed":0,"syntology":null},{"url":null,"slug":"z-index-at-checkthat-lab-2022-check","title":"Z-Index at CheckThat! Lab 2022: Check-Worthiness Identification on Tweet Text","date":"2022-07-15","arxiv_id":"2207.07308","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-contrastive-learning-approach-for","title":"Supervised Contrastive Learning Approach for Contextual Ranking","date":"2022-07-07","arxiv_id":"2207.03153","repositories_listed":0,"syntology":null},{"url":null,"slug":"happenstance-utilizing-semantic-search-to","title":"Happenstance: Utilizing Semantic Search to Track Russian State Media Narratives about the Russo-Ukrainian War On Reddit","date":"2022-05-28","arxiv_id":"2205.14484","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-literal-and-implied-subquestions","title":"Generating Literal and Implied Subquestions to Fact-check Complex Claims","date":"2022-05-14","arxiv_id":"2205.06938","repositories_listed":0,"syntology":null},{"url":null,"slug":"aggregating-pairwise-semantic-differences-for-1","title":"Aggregating Pairwise Semantic Differences for Few-Shot Claim Veracity Classification","date":"2022-05-11","arxiv_id":"2205.05646","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-semantics-aware-approach-to-automated-claim","title":"A Semantics-Aware Approach to Automated Claim Verification","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-fake-news-detection-are-current-1","title":"Automatic Fake News Detection: Are current models “fact-checking” or“gut-checking”?","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-false-claims-in-low-resource","title":"Detecting False Claims in Low-Resource Regions: A Case Study of Caribbean Islands","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"82fea6b1c82dd2057355ca660a068bed25eb697f6408363c49cdc0b33368a859","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}