{"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/articles/papers/24","list_of":"/task/articles","task":"Articles","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":24,"pages_in_order":41,"rows_per_page":100,"rows":[2301,2400],"of":4012,"counts":{"archive_papers_tagged":4012,"with_a_code_link":1123,"where_syntology_ran_a_sample":126,"not_listed_spam_title":0,"listed":4012,"listed_where_code_ran":126,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":107,"every_run_a_failure_of_syntologys_instrument":19,"listed_with_a_run_with_no_instrument_failure":107,"listed_every_run_a_failure_of_syntologys_instrument":19,"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/articles","prev":"/task/articles/papers/23","next":"/task/articles/papers/25","papers":[{"url":"/paper/biographical-a-semi-supervised-relation","slug":"biographical-a-semi-supervised-relation","title":"Biographical: A Semi-Supervised Relation Extraction Dataset","date":"2022-05-02","arxiv_id":"2205.00806","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-knowledge-storage-and-semantic-space","title":"A Knowledge storage and semantic space alignment Method for Multi-documents dialogue generation","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"automatically-discarding-straplines-to","title":"Automatically Discarding Straplines to Improve Data Quality for Abstractive News Summarization","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"biocite-a-deep-learning-based-citation","title":"BioCite: A Deep Learning-based Citation Linkage Framework for Biomedical Research Articles","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ethics-sheets-for-ai-tasks-1","title":"Ethics Sheets for AI Tasks","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"explainable-assessment-of-healthcare-articles-1","title":"Explainable Assessment of Healthcare Articles with QA","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-biographies-on-wikipedia-the","title":"Generating Biographies on Wikipedia: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"surrey-cts-nlp-at-wassa2022-an-experiment-of","title":"SURREY-CTS-NLP at WASSA2022: An Experiment of Discourse and Sentiment Analysis for the Prediction of Empathy, Distress and Emotion","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-detecting-political-bias-in-hindi","title":"Towards Detecting Political Bias in Hindi News Articles","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"wassa-2022-shared-task-predicting-empathy","title":"WASSA 2022 Shared Task: Predicting Empathy, Emotion and Personality in Reaction to News Stories","date":"2022-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-emotion-specific-features-to","title":"Leveraging Emotion-specific Features to Improve Transformer Performance for Emotion Classification","date":"2022-04-30","arxiv_id":"2205.00283","repositories_listed":0,"syntology":null},{"url":null,"slug":"sciev-finding-scientific-evidence-papers-for","title":"SciEv: Finding Scientific Evidence Papers for Scientific News","date":"2022-04-30","arxiv_id":"2205.00126","repositories_listed":0,"syntology":null},{"url":null,"slug":"reliability-in-time-evaluating-the-web","title":"Reliability in Time: Evaluating the Web Sources of Information on COVID-19 in Wikipedia across Various Language Editions from the Beginning of the Pandemic","date":"2022-04-29","arxiv_id":"2204.14130","repositories_listed":0,"syntology":null},{"url":"/paper/meshup-a-corpus-for-full-text-biomedical","slug":"meshup-a-corpus-for-full-text-biomedical","title":"MeSHup: A Corpus for Full Text Biomedical Document Indexing","date":"2022-04-28","arxiv_id":"2204.13604","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplifying-multilingual-news-clustering","title":"Simplifying Multilingual News Clustering Through Projection From a Shared Space","date":"2022-04-28","arxiv_id":"2204.13418","repositories_listed":0,"syntology":null},{"url":null,"slug":"timebert-enhancing-pre-trained-language","title":"BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information","date":"2022-04-27","arxiv_id":"2204.13032","repositories_listed":0,"syntology":null},{"url":null,"slug":"c3-continued-pretraining-with-contrastive","title":"C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrieval","date":"2022-04-25","arxiv_id":"2204.11989","repositories_listed":0,"syntology":null},{"url":null,"slug":"islander-a-real-time-news-monitoring-and","title":"Islander: A Real-Time News Monitoring and Analysis System","date":"2022-04-25","arxiv_id":"2204.11457","repositories_listed":0,"syntology":null},{"url":null,"slug":"taygete-at-semeval-2022-task-4-roberta-based","title":"Taygete at SemEval-2022 Task 4: RoBERTa based models for detecting Patronising and Condescending Language","date":"2022-04-22","arxiv_id":"2204.10519","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-review-of-guidelines-for-the-use","title":"A systematic review of guidelines for the use of race, ethnicity, and ancestry reveals widespread consensus but also points of ongoing disagreement","date":"2022-04-21","arxiv_id":"2204.10672","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-learning-for-medical-text-a","title":"Few-shot learning for medical text: A systematic review","date":"2022-04-21","arxiv_id":"2204.14081","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-label-classification-for-biomedical","title":"Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations","date":"2022-04-20","arxiv_id":"2204.09781","repositories_listed":0,"syntology":null},{"url":null,"slug":"mono-vs-multilingual-bert-for-hate-speech","title":"Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi","date":"2022-04-19","arxiv_id":"2204.08669","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-label-topic-classification-for-covid-19","title":"Multi-label topic classification for COVID-19 literature with Bioformer","date":"2022-04-14","arxiv_id":"2204.06758","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-full-length-wikipedia-biographies","title":"Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies","date":"2022-04-12","arxiv_id":"2204.05879","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-graph-matching-for-modification","title":"Neural Graph Matching for Modification Similarity Applied to Electronic Document Comparison","date":"2022-04-12","arxiv_id":"2204.05486","repositories_listed":0,"syntology":null},{"url":null,"slug":"deflectometry-for-specular-surfaces-an","title":"Deflectometry for specular surfaces: an overview","date":"2022-04-10","arxiv_id":"2204.11592","repositories_listed":0,"syntology":null},{"url":null,"slug":"fake-news-detection-using-parallel-bert-deep","title":"Fake news detection using parallel BERT deep neural networks","date":"2022-04-10","arxiv_id":"2204.04793","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-machine-learning-in-precision","title":"Multimodal Machine Learning in Precision Health","date":"2022-04-10","arxiv_id":"2204.04777","repositories_listed":0,"syntology":null},{"url":null,"slug":"matching-writers-to-content-writing-tasks","title":"Matching Writers to Content Writing Tasks","date":"2022-04-07","arxiv_id":"2204.09718","repositories_listed":0,"syntology":null},{"url":null,"slug":"mhms-multimodal-hierarchical-multimedia","title":"MHMS: Multimodal Hierarchical Multimedia Summarization","date":"2022-04-07","arxiv_id":"2204.03734","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequence-based-extractive-summarisation-for","title":"Sequence-Based Extractive Summarisation for Scientific Articles","date":"2022-04-07","arxiv_id":"2204.03301","repositories_listed":0,"syntology":null},{"url":null,"slug":"cryptocurrency-return-prediction-using","title":"Forecasting Cryptocurrency Returns from Sentiment Signals: An Analysis of BERT Classifiers and Weak Supervision","date":"2022-04-06","arxiv_id":"2204.05781","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-deep-neural-networks-contribute-to","title":"Do Deep Neural Networks Contribute to Multivariate Time Series Anomaly Detection?","date":"2022-04-04","arxiv_id":"2204.01637","repositories_listed":0,"syntology":null},{"url":null,"slug":"extended-reality-for-anxiety-and-depression","title":"Extended Reality for Mental Health Evaluation -A Scoping Review","date":"2022-04-04","arxiv_id":"2204.01348","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-factual-accuracy-of-abstractive","title":"Improving the Factual Accuracy of Abstractive Clinical Text Summarization using Multi-Objective Optimization","date":"2022-04-02","arxiv_id":"2204.00797","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-intervention-approval-in-clinical","title":"Predicting Intervention Approval in Clinical Trials through Multi-Document Summarization","date":"2022-04-01","arxiv_id":"2204.00290","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-scientific-articles-with-machine","title":"Generating Scientific Articles with Machine Learning","date":"2022-03-30","arxiv_id":"2203.16569","repositories_listed":0,"syntology":null},{"url":null,"slug":"forecasting-with-economic-news","title":"Forecasting with Economic News","date":"2022-03-29","arxiv_id":"2203.15686","repositories_listed":0,"syntology":null},{"url":null,"slug":"iranian-modal-music-dastgah-detection-using","title":"Iranian Modal Music (Dastgah) detection using deep neural networks","date":"2022-03-29","arxiv_id":"2203.15335","repositories_listed":0,"syntology":null},{"url":null,"slug":"ldkp-a-dataset-for-identifying-keyphrases","title":"LDKP: A Dataset for Identifying Keyphrases from Long Scientific Documents","date":"2022-03-29","arxiv_id":"2203.15349","repositories_listed":0,"syntology":null},{"url":null,"slug":"extracting-image-characteristics-to-predict","title":"Extraction of Visual Information to Predict Crowdfunding Success","date":"2022-03-28","arxiv_id":"2203.14806","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-study-and-comparison-of-recent","title":"Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison","date":"2022-03-27","arxiv_id":"2203.14205","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-the-longevity-of-resources-shared","title":"Predicting the longevity of resources shared in scientific publications","date":"2022-03-24","arxiv_id":"2203.12800","repositories_listed":0,"syntology":null},{"url":null,"slug":"explainability-in-reinforcement-learning","title":"Explainability in reinforcement learning: perspective and position","date":"2022-03-22","arxiv_id":"2203.11547","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-and-unsupervised-categorization-of","title":"Supervised and Unsupervised Categorization of an Imbalanced Italian Crime News Dataset","date":"2022-03-22","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"visuo-haptic-object-perception-for-robots-an","title":"Visuo-Haptic Object Perception for Robots: An Overview","date":"2022-03-22","arxiv_id":"2203.11544","repositories_listed":0,"syntology":null},{"url":null,"slug":"dianes-a-dei-audit-toolkit-for-news-sources","title":"DIANES: A DEI Audit Toolkit for News Sources","date":"2022-03-21","arxiv_id":"2203.11383","repositories_listed":0,"syntology":null},{"url":null,"slug":"hibrids-attention-with-hierarchical-biases","title":"HIBRIDS: Attention with Hierarchical Biases for Structure-aware Long Document Summarization","date":"2022-03-21","arxiv_id":"2203.10741","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-covid-19-news-coverage-using","title":"Understanding COVID-19 News Coverage using Medical NLP","date":"2022-03-19","arxiv_id":"2203.10338","repositories_listed":0,"syntology":null},{"url":null,"slug":"fake-news-detection-using-majority-voting","title":"Fake News Detection Using Majority Voting Technique","date":"2022-03-18","arxiv_id":"2203.09936","repositories_listed":0,"syntology":null},{"url":null,"slug":"informative-causality-extraction-from-medical","title":"Informative Causality Extraction from Medical Literature via Dependency-tree based Patterns","date":"2022-03-13","arxiv_id":"2203.06592","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-analyzing-the-bias-of-news","title":"Towards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection","date":"2022-03-11","arxiv_id":"2203.05824","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-word-embeddings-to-analyze-protests","title":"Using Word Embeddings to Analyze Protests News","date":"2022-03-11","arxiv_id":"2203.05875","repositories_listed":0,"syntology":null},{"url":null,"slug":"hisa-smfm-historical-and-sentiment-analysis","title":"HiSA-SMFM: Historical and Sentiment Analysis based Stock Market Forecasting Model","date":"2022-03-10","arxiv_id":"2203.08143","repositories_listed":0,"syntology":null},{"url":null,"slug":"indicnlg-suite-multilingual-datasets-for","title":"IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages","date":"2022-03-10","arxiv_id":"2203.05437","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-multi-task-learning-with-task","title":"Sequential Multi-task Learning with Task Dependency for Appeal Judgment Prediction","date":"2022-03-09","arxiv_id":"2204.07046","repositories_listed":0,"syntology":null},{"url":null,"slug":"trust-in-ai-and-implications-for-the-aec","title":"Trust in AI and Implications for the AEC Research: A Literature Analysis","date":"2022-03-08","arxiv_id":"2203.03847","repositories_listed":0,"syntology":null},{"url":null,"slug":"ocr-quality-affects-perceived-usefulness-of","title":"OCR quality affects perceived usefulness of historical newspaper clippings -- a user study","date":"2022-03-04","arxiv_id":"2203.03557","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-unstructured-text-to-causal-knowledge","title":"From Unstructured Text to Causal Knowledge Graphs: A Transformer-Based Approach","date":"2022-02-23","arxiv_id":"2202.11768","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-watermarking-a-solution-for","title":"Speech watermarking: an approach for the forensic analysis of digital telephonic recordings","date":"2022-02-23","arxiv_id":"2203.02275","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-survey-with-quantitative","title":"A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurements","date":"2022-02-18","arxiv_id":"2202.09020","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-new-lda-formulation-with-covariates","title":"A new LDA formulation with covariates","date":"2022-02-18","arxiv_id":"2202.11527","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-learning-models-and-facial-regions","title":"Machine learning models and facial regions videos for estimating heart rate: a review on Patents, Datasets and Literature","date":"2022-02-17","arxiv_id":"2202.08913","repositories_listed":0,"syntology":null},{"url":null,"slug":"bias-and-unfairness-in-machine-learning","title":"Bias and unfairness in machine learning models: a systematic literature review","date":"2022-02-16","arxiv_id":"2202.08176","repositories_listed":0,"syntology":null},{"url":null,"slug":"ensemble-learning-techniques-for-object","title":"Ensemble Learning techniques for object detection in high-resolution satellite images","date":"2022-02-16","arxiv_id":"2202.10554","repositories_listed":0,"syntology":null},{"url":"/paper/pquad-a-persian-question-answering-dataset","slug":"pquad-a-persian-question-answering-dataset","title":"PQuAD: A Persian Question Answering Dataset","date":"2022-02-13","arxiv_id":"2202.06219","repositories_listed":0,"syntology":null},{"url":null,"slug":"privacy-protection-based-on-mask-template","title":"Privacy protection based on mask template","date":"2022-02-13","arxiv_id":"2202.06250","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-gaze-information-in-highly-dynamic","title":"Latent gaze information in highly dynamic decision-tasks","date":"2022-02-08","arxiv_id":"2202.04072","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-landcover-classification-with","title":"A Review of Landcover Classification with Very-High Resolution Remotely Sensed Optical Images-Analysis Unit,Model Scalability and Transferability","date":"2022-02-07","arxiv_id":"2202.03342","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-probabilistic-models-in-text","title":"Improving Probabilistic Models in Text Classification via Active Learning","date":"2022-02-05","arxiv_id":"2202.02629","repositories_listed":0,"syntology":null},{"url":null,"slug":"sensor-technologies-in-cancer-research-for","title":"Sensor technologies in cancer research for new directions in diagnosis and treatment: and exploratory analysis","date":"2022-02-04","arxiv_id":"2203.00502","repositories_listed":0,"syntology":null},{"url":null,"slug":"stonkbert-can-language-models-predict-medium","title":"StonkBERT: Can Language Models Predict Medium-Run Stock Price Movements?","date":"2022-02-04","arxiv_id":"2202.02268","repositories_listed":0,"syntology":null},{"url":null,"slug":"docbed-a-multi-stage-ocr-solution-for","title":"DocBed: A Multi-Stage OCR Solution for Documents with Complex Layouts","date":"2022-02-03","arxiv_id":"2202.01414","repositories_listed":0,"syntology":null},{"url":null,"slug":"technology-ethics-in-action-critical-and","title":"Technology Ethics in Action: Critical and Interdisciplinary Perspectives","date":"2022-02-03","arxiv_id":"2202.01351","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-literature-review-about-idea","title":"A Systematic Literature Review about Idea Mining: The Use of Machine-driven Analytics to Generate Ideas","date":"2022-01-30","arxiv_id":"2202.12826","repositories_listed":0,"syntology":null},{"url":null,"slug":"meltpoolnet-melt-pool-characteristic","title":"MeltpoolNet: Melt pool Characteristic Prediction in Metal Additive Manufacturing Using Machine Learning","date":"2022-01-26","arxiv_id":"2201.11662","repositories_listed":0,"syntology":null},{"url":null,"slug":"repetition-and-reproduction-of-preclinical","title":"Repetition and reproduction of preclinical medical studies: taking a leaf from the plant sciences with consideration of generalised systematic errors","date":"2022-01-26","arxiv_id":"2201.10960","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-multi-level-context-for","title":"Modeling Multi-level Context for Informational Bias Detection by Contrastive Learning and Sentential Graph Network","date":"2022-01-25","arxiv_id":"2201.10376","repositories_listed":0,"syntology":null},{"url":null,"slug":"whose-language-counts-as-high-quality","title":"Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection","date":"2022-01-25","arxiv_id":"2201.10474","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-link-between-standardization-and-economic","title":"The Link Between Standardization and Economic Growth: A Bibliometric Analysis","date":"2022-01-22","arxiv_id":"2201.09125","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-timing-and-magnitude-of","title":"Evaluating the timing and magnitude of semantic change in diachronic word embedding models","date":"2022-01-20","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cm3-a-causal-masked-multimodal-model-of-the","title":"CM3: A Causal Masked Multimodal Model of the Internet","date":"2022-01-19","arxiv_id":"2201.07520","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-non-expert-s-introduction-to-data-ethics","title":"A Non-Expert's Introduction to Data Ethics for Mathematicians","date":"2022-01-18","arxiv_id":"2201.07794","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-based-carcinoma-detection-and","title":"AI-based Carcinoma Detection and Classification Using Histopathological Images: A Systematic Review","date":"2022-01-18","arxiv_id":"2201.07231","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-document-misinformation-detection-based","title":"Cross-document Misinformation Detection based on Event Graph Reasoning","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-cloze-by-date-understanding-what-lms","title":"Entity Cloze By Date: Understanding what LMs know about unseen entities","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"evons-a-dataset-for-fake-and-real-news","title":"Evons: A Dataset for Fake and Real News Virality Analysis and Prediction","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exposing-the-obscured-influence-of-state","title":"Exposing the Obscured Influence of State-Controlled Media: A Causal Estimation of Influence Between Media Outlets Via Quotation Propagation","date":"2022-01-16","arxiv_id":"2201.05985","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-authorship-attribution-in-english","title":"Few-Shot Authorship Attribution in English Reddit Posts","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fruit-faithfully-reflecting-updated-1","title":"FRUIT: Faithfully Reflecting Updated Information in Text","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"gated-recursive-and-sequential-deep","title":"Gated Recursive and Sequential Deep Hierarchical Encoding for Detecting Incongruent News Articles","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"greener-graph-neural-networks-for-news-media","title":"GREENER: Graph Neural Networks for News Media Profiling","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kcd-knowledge-walks-and-textual-cues-enhanced","title":"KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"my-stance-decides-my-language-modeling-of","title":"\"my stance decides my language\": Modeling of Framing and Political Stance in News Media","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neus-neutral-multi-news-summarization-for","title":"NeuS: Neutral Multi-News Summarization for Framing Bias Mitigation","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"newsclaims-a-new-benchmark-for-claim-1","title":"NewsClaims: A New Benchmark for Claim Detection from News with Background Knowledge","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"newsedits-a-dataset-of-news-article-revision-1","title":"NewsEdits: A Dataset of News Article Revision Histories and a Novel Document-Level Reasoning Challenge","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sequentially-controlled-text-generation","title":"Sequentially Controlled Text Generation","date":"2022-01-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kazakhtts2-extending-the-open-source-kazakh","title":"KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics","date":"2022-01-15","arxiv_id":"2201.05771","repositories_listed":0,"syntology":null}],"record_sha256":"ff46f32cbdea6af09ad066f853f75d826ef3039060e4b0deced8de39784fe5ae","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}