{"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/extractive-summarization/papers/3","list_of":"/task/extractive-summarization","task":"Extractive Summarization","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":3,"pages_in_order":4,"rows_per_page":100,"rows":[201,300],"of":315,"counts":{"archive_papers_tagged":315,"with_a_code_link":114,"where_syntology_ran_a_sample":10,"not_listed_spam_title":0,"listed":315,"listed_where_code_ran":10,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":10,"every_run_a_failure_of_syntologys_instrument":0,"listed_with_a_run_with_no_instrument_failure":10,"listed_every_run_a_failure_of_syntologys_instrument":0,"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/extractive-summarization","prev":"/task/extractive-summarization/papers/2","next":"/task/extractive-summarization/papers/4","papers":[{"url":null,"slug":"uetrice-at-mediqa-2021-a-prosper-thy","title":"UETrice at MEDIQA 2021: A Prosper-thy-neighbour Extractive Multi-document Summarization Model","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-document-summarization-using-pre","title":"Unsupervised document summarization using pre-trained sentence embeddings and graph centrality","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"genetic-algorithms-for-extractive","title":"Genetic Algorithms For Extractive Summarization","date":"2021-05-05","arxiv_id":"2105.02365","repositories_listed":0,"syntology":null},{"url":"/paper/automated-news-summarization-using","slug":"automated-news-summarization-using","title":"Automated News Summarization Using Transformers","date":"2021-04-23","arxiv_id":"2108.01064","repositories_listed":0,"syntology":null},{"url":"/paper/text-summarization-of-czech-news-articles","slug":"text-summarization-of-czech-news-articles","title":"Text Summarization of Czech News Articles Using Named Entities","date":"2021-04-21","arxiv_id":"2104.10454","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-extractive-summarization-by","title":"Unsupervised Extractive Summarization by Human Memory Simulation","date":"2021-04-16","arxiv_id":"2104.08392","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-considering","title":"Extractive Summarization Considering Discourse and Coreference Relations based on Heterogeneous Graph","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"globalizing-bert-based-transformer","title":"Globalizing BERT-based Transformer Architectures for Long Document Summarization","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multihumes-multilingual-humanitarian-dataset","title":"MultiHumES: Multilingual Humanitarian Dataset for Extractive Summarization","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extending-multi-sense-word-embedding-to","title":"Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications","date":"2021-03-29","arxiv_id":"2103.15330","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-of-call-transcripts","title":"Extractive Summarization of Call Transcripts","date":"2021-03-19","arxiv_id":"2103.10599","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-informative-cve-description-from","title":"Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization","date":"2021-01-05","arxiv_id":"2101.01431","repositories_listed":0,"syntology":null},{"url":null,"slug":"news-image-steganography-a-novel-architecture","title":"News Image Steganography: A Novel Architecture Facilitates the Fake News Identification","date":"2021-01-03","arxiv_id":"2101.00606","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-extractive-multi-document-text","title":"A novel extractive multi-document text summarization system using quantum-inspired genetic algorithm: MTSQIGA","date":"2020-12-30","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-multiple-asr-hypotheses-to-boost-i18n","title":"Using multiple ASR hypotheses to boost i18n NLU performance","date":"2020-12-07","arxiv_id":"2012.04099","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-we-really-need-that-many-parameters-in","title":"Do We Really Need That Many Parameters In Transformer For Extractive Summarization? Discourse Can Help !","date":"2020-12-03","arxiv_id":"2012.02144","repositories_listed":0,"syntology":null},{"url":null,"slug":"amex-ai-labs-an-investigative-study-on","title":"AMEX AI-Labs: An Investigative Study on Extractive Summarization of Financial Documents","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-system-for-annual","title":"Extractive Summarization System for Annual Reports","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hindi-history-note-generation-with","title":"Hindi History Note Generation with Unsupervised Extractive Summarization","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"holms-alternative-summary-evaluation-with","title":"HOLMS: Alternative Summary Evaluation with Large Language Models","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"identifying-implicit-quotes-for-unsupervised","title":"Identifying Implicit Quotes for Unsupervised Extractive Summarization of Conversations","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"news-editorials-towards-summarizing-long","title":"News Editorials: Towards Summarizing Long Argumentative Texts","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sumsum-fns-2020-shared-task","title":"SUMSUM@FNS-2020 Shared Task","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tweetsum-event-oriented-social-summarization","title":"TWEETSUM: Event oriented Social Summarization Dataset","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cist-cl-scisumm-2020-longsumm-2020-automatic","title":"CIST@CL-SciSumm 2020, LongSumm 2020: Automatic Scientific Document Summarization","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/neural-extractive-summarization-with","slug":"neural-extractive-summarization-with","title":"Neural Extractive Summarization with Hierarchical Attentive Heterogeneous Graph Network","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-pre-trained-transformer-for-better-lay","title":"Using Pre-Trained Transformer for Better Lay Summarization","date":"2020-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-extractive-text-summarization-with","title":"Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks","date":"2020-10-13","arxiv_id":"2010.06253","repositories_listed":0,"syntology":null},{"url":null,"slug":"experiments-in-extractive-summarization","title":"Experiments in Extractive Summarization: Integer Linear Programming, Term/Sentence Scoring, and Title-driven Models","date":"2020-08-01","arxiv_id":"2008.00140","repositories_listed":0,"syntology":null},{"url":null,"slug":"dialect-diversity-in-text-summarization-on","title":"Dialect Diversity in Text Summarization on Twitter","date":"2020-07-15","arxiv_id":"2007.07860","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-retrieval-and-extraction-on-covid","title":"Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-granularity-interaction-network-for","title":"Multi-Granularity Interaction Network for Extractive and Abstractive Multi-Document Summarization","date":"2020-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-word-embeddings-and-n-grams-for","title":"Combining Word Embeddings and N-grams for Unsupervised Document Summarization","date":"2020-04-25","arxiv_id":"2004.14119","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-focused-ehr-summarization-to-aid","title":"Query-Focused EHR Summarization to Aid Imaging Diagnosis","date":"2020-04-09","arxiv_id":"2004.04645","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-utterance-generation","title":"Automated Utterance Generation","date":"2020-04-07","arxiv_id":"2004.03484","repositories_listed":0,"syntology":null},{"url":null,"slug":"at-which-level-should-we-extract-an-empirical","title":"At Which Level Should We Extract? An Empirical Analysis on Extractive Document Summarization","date":"2020-04-06","arxiv_id":"2004.02664","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-summarization-for-low-resource","title":"Abstractive Summarization for Low Resource Data using Domain Transfer and Data Synthesis","date":"2020-02-09","arxiv_id":"2002.03407","repositories_listed":0,"syntology":null},{"url":null,"slug":"audio-summarization-with-audio-features-and","title":"Audio Summarization with Audio Features and Probability Distribution Divergence","date":"2020-01-20","arxiv_id":"2001.07098","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-memnet-for-extractive-summarization","title":"Hybrid MemNet for Extractive Summarization","date":"2019-12-25","arxiv_id":"1912.11701","repositories_listed":0,"syntology":null},{"url":null,"slug":"unity-in-diversity-learning-distributed","title":"Unity in Diversity: Learning Distributed Heterogeneous Sentence Representation for Extractive Summarization","date":"2019-12-25","arxiv_id":"1912.11688","repositories_listed":0,"syntology":null},{"url":null,"slug":"ebsum-ji-yu-bert-de-qiang-jian-xing-chou-qu","title":"EBSUM: 基於 BERT 的強健性抽取式摘要法 (EBSUM: An Enhanced BERT-based Extractive Summarization Framework)","date":"2019-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-supervised-extractive-text","title":"Towards Supervised Extractive Text Summarization via RNN-based Sequence Classification","date":"2019-11-13","arxiv_id":"1911.06121","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automatic-extractive-text","title":"Towards automatic extractive text summarization of A-133 Single Audit reports with machine learning","date":"2019-11-08","arxiv_id":"1911.06197","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-discourse-level-segmentation-for","title":"Exploiting Discourse-Level Segmentation for Extractive Summarization","date":"2019-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-document-summarization-with","title":"Multi-Document Summarization with Determinantal Point Processes and Contextualized Representations","date":"2019-10-24","arxiv_id":"1910.11411","repositories_listed":0,"syntology":null},{"url":null,"slug":"group-extract-and-aggregate-summarizing-a","title":"Group, Extract and Aggregate: Summarizing a Large Amount of Finance News for Forex Movement Prediction","date":"2019-10-11","arxiv_id":"1910.05032","repositories_listed":0,"syntology":null},{"url":null,"slug":"topic-aware-pointer-generator-networks-for","title":"Topic-aware Pointer-Generator Networks for Summarizing Spoken Conversations","date":"2019-10-03","arxiv_id":"1910.01335","repositories_listed":0,"syntology":null},{"url":null,"slug":"ebsum-ji-yu-bert-de-qiang-jian-xing-chou-qu-1","title":"EBSUM: 基於BERT 的強健性抽取式摘要法(EBSUM: An Enhanced BERT-based Extractive Summarization Framework)","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"vae-pgn-based-abstractive-model-in-multi","title":"VAE-PGN based Abstractive Model in Multi-stage Architecture for Text Summarization","date":"2019-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-closer-look-at-data-bias-in-neural","title":"A Closer Look at Data Bias in Neural Extractive Summarization Models","date":"2019-09-30","arxiv_id":"1909.13705","repositories_listed":0,"syntology":null},{"url":null,"slug":"190910393","title":"Specificity-Based Sentence Ordering for Multi-Document Extractive Risk Summarization","date":"2019-09-23","arxiv_id":"1909.10393","repositories_listed":0,"syntology":null},{"url":null,"slug":"bottlesum-unsupervised-and-self-supervised","title":"BottleSum: Unsupervised and Self-supervised Sentence Summarization using the Information Bottleneck Principle","date":"2019-09-16","arxiv_id":"1909.07405","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-study-of-semantic-augmentation-of-word","title":"A study of semantic augmentation of word embeddings for extractive summarization","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-topic-based-sentence-representation-for","title":"A topic-based sentence representation for extractive text summarization","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-lingual-wikipedia-summarization-and","title":"Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"opinions-summarization-aspect-similarity","title":"Opinions Summarization: Aspect Similarity Recognition Relaxes The Constraint of Predefined Aspects","date":"2019-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ranking-sentences-from-product-description","title":"Ranking sentences from product description & bullets for better search","date":"2019-07-15","arxiv_id":"1907.06330","repositories_listed":0,"syntology":null},{"url":"/paper/answering-while-summarizing-multi-task","slug":"answering-while-summarizing-multi-task","title":"Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction","date":"2019-05-21","arxiv_id":"1905.08511","repositories_listed":0,"syntology":null},{"url":"/paper/hibert-document-level-pre-training-of","slug":"hibert-document-level-pre-training-of","title":"HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization","date":"2019-05-16","arxiv_id":"1905.06566","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-comes-next-extractive-summarization-by","title":"What comes next? Extractive summarization by next-sentence prediction","date":"2019-01-12","arxiv_id":"1901.03859","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-summarization-of-natural-language","title":"Automatic Summarization of Natural Language","date":"2018-12-18","arxiv_id":"1812.10549","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-pseudo-labeling-for-extractive","title":"Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records","date":"2018-11-20","arxiv_id":"1811.08040","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-text-document-summarization-using","title":"Automatic Text Document Summarization using Semantic-based Analysis","date":"2018-11-15","arxiv_id":"1811.06567","repositories_listed":0,"syntology":null},{"url":null,"slug":"extraction-meets-abstraction-ideal-answer","title":"Extraction Meets Abstraction: Ideal Answer Generation for Biomedical Questions","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"uncc-qa-biomedical-question-answering-system","title":"UNCC QA: Biomedical Question Answering system","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-dual-cascade-learning-with","title":"Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization","date":"2018-11-01","arxiv_id":"1811.00436","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-of-ehr-discharge","title":"Extractive Summarization of EHR Discharge Notes","date":"2018-10-26","arxiv_id":"1810.12085","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-extractive-summarization-using","title":"Effective extractive summarization using frequency-filtered entity relationship graphs","date":"2018-10-24","arxiv_id":"1810.10419","repositories_listed":0,"syntology":null},{"url":null,"slug":"harnessing-popularity-in-social-media-for","title":"Harnessing Popularity in Social Media for Extractive Summarization of Online Conversations","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nuts-network-for-unsupervised-telegraphic","title":"NUTS: Network for Unsupervised Telegraphic Summarization","date":"2018-09-27","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-local-and-global-performance-of","title":"Exploiting local and global performance of candidate systems for aggregation of summarization techniques","date":"2018-09-07","arxiv_id":"1809.02343","repositories_listed":0,"syntology":null},{"url":"/paper/neural-latent-extractive-document","slug":"neural-latent-extractive-document","title":"Neural Latent Extractive Document Summarization","date":"2018-08-22","arxiv_id":"1808.07187","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-and-extractive-text-summarization","title":"Abstractive and Extractive Text Summarization using Document Context Vector and Recurrent Neural Networks","date":"2018-07-20","arxiv_id":"1807.08000","repositories_listed":0,"syntology":null},{"url":null,"slug":"provable-fast-greedy-compressive","title":"Provable Fast Greedy Compressive Summarization with Any Monotone Submodular Function","date":"2018-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforced-extractive-summarization-with","title":"Reinforced Extractive Summarization with Question-Focused Rewards","date":"2018-05-25","arxiv_id":"1805.10392","repositories_listed":0,"syntology":null},{"url":null,"slug":"toward-extractive-summarization-of-online","title":"Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks","date":"2018-05-25","arxiv_id":"1805.10390","repositories_listed":0,"syntology":null},{"url":"/paper/learning-to-extract-coherent-summary-via-deep","slug":"learning-to-extract-coherent-summary-via-deep","title":"Learning to Extract Coherent Summary via Deep Reinforcement Learning","date":"2018-04-19","arxiv_id":"1804.07036","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlling-decoding-for-more-abstractive","title":"Controlling Decoding for More Abstractive Summaries with Copy-Based Networks","date":"2018-03-19","arxiv_id":"1803.07038","repositories_listed":0,"syntology":null},{"url":"/paper/faithful-to-the-original-fact-aware-neural","slug":"faithful-to-the-original-fact-aware-neural","title":"Faithful to the Original: Fact Aware Neural Abstractive Summarization","date":"2017-11-13","arxiv_id":"1711.04434","repositories_listed":0,"syntology":null},{"url":null,"slug":"taking-into-account-inter-sentence-similarity","title":"Taking into account Inter-sentence Similarity for Update Summarization","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"conceptual-text-summarizer-a-new-model-in","title":"Conceptual Text Summarizer: A new model in continuous vector space","date":"2017-10-30","arxiv_id":"1710.10994","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-using-multi-task","title":"Extractive Summarization Using Multi-Task Learning with Document Classification","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"gold-standard-online-debates-summaries-and","title":"Gold Standard Online Debates Summaries and First Experiments Towards Automatic Summarization of Online Debate Data","date":"2017-08-15","arxiv_id":"1708.04592","repositories_listed":0,"syntology":null},{"url":null,"slug":"tackling-biomedical-text-summarization-oaqa","title":"Tackling Biomedical Text Summarization: OAQA at BioASQ 5B","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-limits-compression","title":"Extractive Summarization: Limits, Compression, Generalized Model and Heuristics","date":"2017-04-18","arxiv_id":"1704.05550","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-unified-multi-faceted-video-summarization","title":"A Unified Multi-Faceted Video Summarization System","date":"2017-04-04","arxiv_id":"1704.01466","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-based-summarization-using-mdl-principle","title":"Query-based summarization using MDL principle","date":"2017-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enumeration-of-extractive-oracle-summaries","title":"Enumeration of Extractive Oracle Summaries","date":"2017-01-06","arxiv_id":"1701.01614","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-redundancy-aware-sentence-regression","title":"A Redundancy-Aware Sentence Regression Framework for Extractive Summarization","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"classify-or-select-neural-architectures-for","title":"Classify or Select: Neural Architectures for Extractive Document Summarization","date":"2016-11-14","arxiv_id":"1611.04244","repositories_listed":0,"syntology":null},{"url":null,"slug":"authorship-attribution-via-network-motifs","title":"Authorship attribution via network motifs identification","date":"2016-07-23","arxiv_id":"1607.06961","repositories_listed":0,"syntology":null},{"url":null,"slug":"focused-meeting-summarization-via","title":"Focused Meeting Summarization via Unsupervised Relation Extraction","date":"2016-06-24","arxiv_id":"1606.07849","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-network-based-abstract-generation-for","title":"Neural Network-Based Abstract Generation for Opinions and Arguments","date":"2016-06-09","arxiv_id":"1606.02785","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-under-strict-length","title":"Extractive Summarization under Strict Length Constraints","date":"2016-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-spoken-document-summarization-with","title":"Improved Spoken Document Summarization with Coverage Modeling Techniques","date":"2016-01-20","arxiv_id":"1601.05194","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-approach-for-single-text-document","title":"Hybrid Approach for Single Text Document Summarization using Statistical and Sentiment Features","date":"2016-01-03","arxiv_id":"1601.00643","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-by-aggregating","title":"Extractive Summarization by Aggregating Multiple Similarities","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-by-maximizing","title":"Extractive Summarization by Maximizing Semantic Volume","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"indicative-tweet-generation-an-extractive","title":"Indicative Tweet Generation: An Extractive Summarization Problem?","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"topical-coherence-for-graph-based-extractive","title":"Topical Coherence for Graph-based Extractive Summarization","date":"2015-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"b7812562830b4ca856d423d5eeb34df180e7c98ca91e6dd12b2db76fe7fec676","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}