{"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/abstractive-text-summarization/papers/5","list_of":"/task/abstractive-text-summarization","task":"Abstractive Text 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":5,"pages_in_order":9,"rows_per_page":100,"rows":[401,500],"of":846,"counts":{"archive_papers_tagged":846,"with_a_code_link":362,"where_syntology_ran_a_sample":77,"not_listed_spam_title":0,"listed":846,"listed_where_code_ran":77,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":65,"every_run_a_failure_of_syntologys_instrument":12,"listed_with_a_run_with_no_instrument_failure":65,"listed_every_run_a_failure_of_syntologys_instrument":12,"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/abstractive-text-summarization","prev":"/task/abstractive-text-summarization/papers/4","next":"/task/abstractive-text-summarization/papers/6","papers":[{"url":null,"slug":"mixsumm-topic-based-data-augmentation-using","title":"A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches","date":"2024-07-10","arxiv_id":"2407.07341","repositories_listed":0,"syntology":null},{"url":null,"slug":"applicability-of-large-language-models-and","title":"Applicability of Large Language Models and Generative Models for Legal Case Judgement Summarization","date":"2024-07-06","arxiv_id":"2407.12848","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-guided-self-supervised-summarization-of","title":"Query-Guided Self-Supervised Summarization of Nursing Notes","date":"2024-07-04","arxiv_id":"2407.04125","repositories_listed":0,"syntology":null},{"url":null,"slug":"discrete-diffusion-language-model-for-long","title":"Discrete Diffusion Language Model for Long Text Summarization","date":"2024-06-25","arxiv_id":"2407.10998","repositories_listed":0,"syntology":null},{"url":"/paper/opendebateevidence-a-massive-scale-argument","slug":"opendebateevidence-a-massive-scale-argument","title":"OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset","date":"2024-06-20","arxiv_id":"2406.14657","repositories_listed":0,"syntology":null},{"url":null,"slug":"cads-a-systematic-literature-review-on-the","title":"CADS: A Systematic Literature Review on the Challenges of Abstractive Dialogue Summarization","date":"2024-06-11","arxiv_id":"2406.07494","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigating-and-addressing-hallucinations","title":"Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation","date":"2024-06-08","arxiv_id":"2406.05494","repositories_listed":0,"syntology":null},{"url":null,"slug":"write-summary-step-by-step-a-pilot-study-of","title":"Write Summary Step-by-Step: A Pilot Study of Stepwise Summarization","date":"2024-06-08","arxiv_id":"2406.05361","repositories_listed":0,"syntology":null},{"url":null,"slug":"aspect-oriented-consumer-health-answer","title":"Aspect-oriented Consumer Health Answer Summarization","date":"2024-05-10","arxiv_id":"2405.06295","repositories_listed":0,"syntology":null},{"url":null,"slug":"atsumm-auxiliary-information-enhanced","title":"ATSumm: Auxiliary information enhanced approach for abstractive disaster Tweet Summarization with sparse training data","date":"2024-05-10","arxiv_id":"2405.06541","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-long-text-understanding-with","title":"Improving Long Text Understanding with Knowledge Distilled from Summarization Model","date":"2024-05-08","arxiv_id":"2405.04955","repositories_listed":0,"syntology":null},{"url":"/paper/rst-lora-a-discourse-aware-low-rank","slug":"rst-lora-a-discourse-aware-low-rank","title":"RST-LoRA: A Discourse-Aware Low-Rank Adaptation for Long Document Abstractive Summarization","date":"2024-05-01","arxiv_id":"2405.00657","repositories_listed":0,"syntology":{"n":7,"n_ran":6,"n_constructed":5,"n_ran_checked":5,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"6 ran (of which 5 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rst-lora-a-discourse-aware-low-rank#ran","syntology_url":"https://syntology.ai/paper/2405.00657","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.00657"}},"official":null}},{"url":null,"slug":"neural-sequence-to-sequence-modeling-with","title":"Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization","date":"2024-04-08","arxiv_id":"2404.08685","repositories_listed":0,"syntology":null},{"url":null,"slug":"assisting-humans-in-complex-comparisons","title":"Assisting humans in complex comparisons: automated information comparison at scale","date":"2024-04-05","arxiv_id":"2404.04351","repositories_listed":0,"syntology":null},{"url":null,"slug":"lexabsumm-aspect-based-summarization-of-legal","title":"LexAbSumm: Aspect-based Summarization of Legal Decisions","date":"2024-03-31","arxiv_id":"2404.00594","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-sequence-to-sequence-models-for","title":"Improving Sequence-to-Sequence Models for Abstractive Text Summarization Using Meta Heuristic Approaches","date":"2024-03-24","arxiv_id":"2403.16247","repositories_listed":0,"syntology":null},{"url":null,"slug":"paramanu-ayn-an-efficient-novel-generative","title":"PARAMANU-AYN: Pretrain from scratch or Continual Pretraining of LLMs for Legal Domain Adaptation?","date":"2024-03-20","arxiv_id":"2403.13681","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-instructions-to-constraints-language","title":"From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification","date":"2024-03-10","arxiv_id":"2403.06326","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-cross-lingual-transfer-for-prompting","title":"Few-Shot Cross-Lingual Transfer for Prompting Large Language Models in Low-Resource Languages","date":"2024-03-09","arxiv_id":"2403.06018","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-second-look-on-bass-boosting-abstractive","title":"A Second Look on BASS -- Boosting Abstractive Summarization with Unified Semantic Graphs -- A Replication Study","date":"2024-03-05","arxiv_id":"2403.02930","repositories_listed":0,"syntology":null},{"url":null,"slug":"vbart-the-turkish-llm","title":"VBART: The Turkish LLM","date":"2024-03-02","arxiv_id":"2403.01308","repositories_listed":0,"syntology":null},{"url":null,"slug":"eros-entity-driven-controlled-policy-document","title":"EROS: Entity-Driven Controlled Policy Document Summarization","date":"2024-02-29","arxiv_id":"2403.00141","repositories_listed":0,"syntology":null},{"url":null,"slug":"layer-wise-regularized-dropout-for-neural","title":"Layer-wise Regularized Dropout for Neural Language Models","date":"2024-02-26","arxiv_id":"2402.16361","repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-level-factual-adaptiveness-of-fine","title":"Entity-level Factual Adaptiveness of Fine-tuning based Abstractive Summarization Models","date":"2024-02-23","arxiv_id":"2402.15162","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-of-multidomain-abstractive","title":"Analysis of Multidomain Abstractive Summarization Using Salience Allocation","date":"2024-02-19","arxiv_id":"2402.11955","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-hybrid-strategy-for-chat-transcript","title":"A Hybrid Strategy for Chat Transcript Summarization","date":"2024-02-02","arxiv_id":"2402.01510","repositories_listed":0,"syntology":null},{"url":null,"slug":"gumsley-evaluating-entity-salience-in","title":"GUMsley: Evaluating Entity Salience in Summarization for 12 English Genres","date":"2024-01-31","arxiv_id":"2401.17974","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-gpt-3-5-s-awareness-and","title":"Evaluating GPT-3.5's Awareness and Summarization Abilities for European Constitutional Texts with Shared Topics","date":"2024-01-25","arxiv_id":"2401.14524","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-robustness-of-transformer-based","title":"Cross-Domain Robustness of Transformer-based Keyphrase Generation","date":"2023-12-17","arxiv_id":"2312.10700","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-representation-bias-for-data","title":"Exploiting Representation Bias for Data Distillation in Abstractive Text Summarization","date":"2023-12-10","arxiv_id":"2312.06022","repositories_listed":0,"syntology":null},{"url":null,"slug":"questioning-biases-in-case-judgment-summaries","title":"Questioning Biases in Case Judgment Summaries: Legal Datasets or Large Language Models?","date":"2023-12-01","arxiv_id":"2312.00554","repositories_listed":0,"syntology":null},{"url":null,"slug":"controllable-topic-focused-abstractive","title":"Controllable Topic-Focused Abstractive Summarization","date":"2023-11-12","arxiv_id":"2311.06724","repositories_listed":0,"syntology":null},{"url":null,"slug":"legal-hnet-mixing-legal-long-context-tokens","title":"Legal-HNet: Mixing Legal Long-Context Tokens with Hartley Transform","date":"2023-11-09","arxiv_id":"2311.05089","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-abstractiveness-of-summarization","title":"Enhancing Abstractiveness of Summarization Models through Calibrated Distillation","date":"2023-10-20","arxiv_id":"2310.13760","repositories_listed":0,"syntology":null},{"url":null,"slug":"metric-ensembles-for-hallucination-detection","title":"Metric Ensembles For Hallucination Detection","date":"2023-10-16","arxiv_id":"2310.10495","repositories_listed":0,"syntology":null},{"url":null,"slug":"calibrating-likelihoods-towards-consistency","title":"Calibrating Likelihoods towards Consistency in Summarization Models","date":"2023-10-12","arxiv_id":"2310.08764","repositories_listed":0,"syntology":null},{"url":null,"slug":"teaching-language-models-to-hallucinate-less","title":"Teaching Language Models to Hallucinate Less with Synthetic Tasks","date":"2023-10-10","arxiv_id":"2310.06827","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-summarization-of-large-document","title":"Abstractive Summarization of Large Document Collections Using GPT","date":"2023-10-09","arxiv_id":"2310.05690","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resource-summarization-using-pre-trained","title":"Low Resource Summarization using Pre-trained Language Models","date":"2023-10-04","arxiv_id":"2310.02790","repositories_listed":0,"syntology":null},{"url":null,"slug":"benllmeval-a-comprehensive-evaluation-into","title":"BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP","date":"2023-09-22","arxiv_id":"2309.13173","repositories_listed":0,"syntology":null},{"url":null,"slug":"promptsum-parameter-efficient-controllable","title":"PromptSum: Parameter-Efficient Controllable Abstractive Summarization","date":"2023-08-06","arxiv_id":"2308.03117","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompting-large-language-models-with-speech","title":"Prompting Large Language Models with Speech Recognition Abilities","date":"2023-07-21","arxiv_id":"2307.11795","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-factuality-of-abstractive-1","title":"Improving Factuality of Abstractive Summarization via Contrastive Reward Learning","date":"2023-07-10","arxiv_id":"2307.04507","repositories_listed":0,"syntology":null},{"url":null,"slug":"named-entity-inclusion-in-abstractive-text-1","title":"Named Entity Inclusion in Abstractive Text Summarization","date":"2023-07-05","arxiv_id":"2307.02570","repositories_listed":0,"syntology":null},{"url":null,"slug":"challenges-in-domain-specific-abstractive","title":"Challenges in Domain-Specific Abstractive Summarization and How to Overcome them","date":"2023-07-03","arxiv_id":"2307.00963","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-text-summarization-for-resumes","title":"Abstractive Text Summarization for Resumes With Cutting Edge NLP Transformers and LSTM","date":"2023-06-23","arxiv_id":"2306.13315","repositories_listed":0,"syntology":null},{"url":null,"slug":"absformer-transformer-based-model-for","title":"Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization","date":"2023-06-07","arxiv_id":"2306.04787","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-ready-are-pre-trained-abstractive-models","title":"How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?","date":"2023-06-02","arxiv_id":"2306.01248","repositories_listed":0,"syntology":null},{"url":null,"slug":"factually-consistent-summarization-via","title":"Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback","date":"2023-05-31","arxiv_id":"2306.00186","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-summarization-as-augmentation-for","title":"Abstractive Summarization as Augmentation for Document-Level Event Detection","date":"2023-05-29","arxiv_id":"2305.18023","repositories_listed":0,"syntology":null},{"url":null,"slug":"incorporating-distributions-of-discourse","title":"Incorporating Distributions of Discourse Structure for Long Document Abstractive Summarization","date":"2023-05-26","arxiv_id":"2305.16784","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-text-summarization-using-the-brio","title":"Abstractive Text Summarization Using the BRIO Training Paradigm","date":"2023-05-23","arxiv_id":"2305.13696","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-agnostic-distillation-of-encoder-decoder","title":"Task-agnostic Distillation of Encoder-Decoder Language Models","date":"2023-05-21","arxiv_id":"2305.12330","repositories_listed":0,"syntology":null},{"url":null,"slug":"counterfactual-debiasing-for-generating","title":"Counterfactual Debiasing for Generating Factually Consistent Text Summaries","date":"2023-05-18","arxiv_id":"2305.10736","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-summary-worthy-visual-representation","title":"Learning Summary-Worthy Visual Representation for Abstractive Summarization in Video","date":"2023-05-08","arxiv_id":"2305.04824","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-current-state-of-summarization","title":"The Current State of Summarization","date":"2023-05-08","arxiv_id":"2305.04853","repositories_listed":0,"syntology":null},{"url":null,"slug":"simcsum-joint-learning-of-simplification-and","title":"SimCSum: Joint Learning of Simplification and Cross-lingual Summarization for Cross-lingual Science Journalism","date":"2023-04-04","arxiv_id":"2304.01621","repositories_listed":0,"syntology":null},{"url":null,"slug":"cqsumdp-a-chatgpt-annotated-resource-for","title":"CQSumDP: A ChatGPT-Annotated Resource for Query-Focused Abstractive Summarization Based on Debatepedia","date":"2023-03-31","arxiv_id":"2305.06147","repositories_listed":0,"syntology":null},{"url":null,"slug":"comparing-abstractive-summaries-generated-by","title":"Comparing Abstractive Summaries Generated by ChatGPT to Real Summaries Through Blinded Reviewers and Text Classification Algorithms","date":"2023-03-30","arxiv_id":"2303.17650","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-as-a-factual-inconsistency-evaluator","title":"ChatGPT as a Factual Inconsistency Evaluator for Text Summarization","date":"2023-03-27","arxiv_id":"2303.15621","repositories_listed":0,"syntology":null},{"url":null,"slug":"sass-data-and-methods-for-subject-aware","title":"SASS: Data and Methods for Subject Aware Sentence Simplification","date":"2023-03-26","arxiv_id":"2303.14589","repositories_listed":0,"syntology":null},{"url":null,"slug":"lay-text-summarisation-using-natural-language","title":"Lay Text Summarisation Using Natural Language Processing: A Narrative Literature Review","date":"2023-03-24","arxiv_id":"2303.14222","repositories_listed":0,"syntology":null},{"url":null,"slug":"spec-summary-preference-decomposition-for-low","title":"SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization","date":"2023-03-24","arxiv_id":"2303.14011","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-text-summarization-using","title":"Abstractive Text Summarization using Attentive GRU based Encoder-Decoder","date":"2023-02-25","arxiv_id":"2302.13117","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-analysis-of-abstractive-text-summarization","title":"An Analysis of Abstractive Text Summarization Using Pre-trained Models","date":"2023-02-25","arxiv_id":"2303.12796","repositories_listed":0,"syntology":null},{"url":null,"slug":"summaries-as-captions-generating-figure","title":"Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization","date":"2023-02-23","arxiv_id":"2302.12324","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-limits-of-chatgpt-for-query-or","title":"Exploring the Limits of ChatGPT for Query or Aspect-based Text Summarization","date":"2023-02-16","arxiv_id":"2302.08081","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-summary-guidance-on-medical-report","title":"Leveraging Summary Guidance on Medical Report Summarization","date":"2023-02-08","arxiv_id":"2302.04001","repositories_listed":0,"syntology":null},{"url":null,"slug":"curriculum-guided-abstractive-summarization","title":"Curriculum-guided Abstractive Summarization for Mental Health Online Posts","date":"2023-02-02","arxiv_id":"2302.00954","repositories_listed":0,"syntology":null},{"url":null,"slug":"curriculum-guided-abstractive-summarization-1","title":"Curriculum-Guided Abstractive Summarization","date":"2023-02-02","arxiv_id":"2302.01342","repositories_listed":0,"syntology":null},{"url":null,"slug":"transformer-based-implementation-for","title":"Transformer Based Implementation for Automatic Book Summarization","date":"2023-01-17","arxiv_id":"2301.07057","repositories_listed":0,"syntology":null},{"url":null,"slug":"bus-efficient-and-effective-vision-language-1","title":"BUS: Efficient and Effective Vision-Language Pre-Training with Bottom-Up Patch Summarization.","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"opinesum-entailment-based-self-training-for","title":"OpineSum: Entailment-based self-training for abstractive opinion summarization","date":"2022-12-21","arxiv_id":"2212.10791","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-robustness-of-summarization","title":"Improving the Robustness of Summarization Models by Detecting and Removing Input Noise","date":"2022-12-20","arxiv_id":"2212.09928","repositories_listed":0,"syntology":null},{"url":null,"slug":"mface-multilingual-summarization-with-factual","title":"mFACE: Multilingual Summarization with Factual Consistency Evaluation","date":"2022-12-20","arxiv_id":"2212.10622","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-faithfulness-of-abstractive","title":"Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences","date":"2022-12-19","arxiv_id":"2212.09726","repositories_listed":0,"syntology":null},{"url":null,"slug":"inverse-reinforcement-learning-for-text","title":"Inverse Reinforcement Learning for Text Summarization","date":"2022-12-19","arxiv_id":"2212.09917","repositories_listed":0,"syntology":null},{"url":null,"slug":"trip-triangular-document-level-pre-training","title":"Advancing Multilingual Pre-training: TRIP Triangular Document-level Pre-training for Multilingual Language Models","date":"2022-12-15","arxiv_id":"2212.07752","repositories_listed":0,"syntology":null},{"url":"/paper/momentum-calibration-for-text-generation","slug":"momentum-calibration-for-text-generation","title":"Momentum Calibration for Text Generation","date":"2022-12-08","arxiv_id":"2212.04257","repositories_listed":0,"syntology":null},{"url":null,"slug":"improved-beam-search-for-hallucination","title":"Improved Beam Search for Hallucination Mitigation in Abstractive Summarization","date":"2022-12-06","arxiv_id":"2212.02712","repositories_listed":0,"syntology":null},{"url":null,"slug":"katsum-knowledge-aware-abstractive-text","title":"KATSum: Knowledge-aware Abstractive Text Summarization","date":"2022-12-06","arxiv_id":"2212.03371","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-opinion-summarisation-in-the","title":"Unsupervised Opinion Summarisation in the Wasserstein Space","date":"2022-11-27","arxiv_id":"2211.14923","repositories_listed":0,"syntology":null},{"url":"/paper/summarizing-community-based-question-answer","slug":"summarizing-community-based-question-answer","title":"Summarizing Community-based Question-Answer Pairs","date":"2022-11-17","arxiv_id":"2211.09892","repositories_listed":0,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":2,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/summarizing-community-based-question-answer#ran","syntology_url":"https://syntology.ai/paper/2211.09892","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2211.09892"}},"official":null}},{"url":null,"slug":"ed-faith-evaluating-dialogue-summarization-on","title":"ED-FAITH: Evaluating Dialogue Summarization on Faithfulness","date":"2022-11-15","arxiv_id":"2211.08464","repositories_listed":0,"syntology":null},{"url":null,"slug":"novel-chapter-abstractive-summarization-using-1","title":"Novel Chapter Abstractive Summarization using Spinal Tree Aware Sub-Sentential Content Selection","date":"2022-11-09","arxiv_id":"2211.04903","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-generation-of-abstracts-for","title":"Automatic Generation of Abstracts for Research Papers","date":"2022-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"frsum-towards-faithful-abstractive-1","title":"FRSUM: Towards Faithful Abstractive Summarization via Enhancing Factual Robustness","date":"2022-11-01","arxiv_id":"2211.00294","repositories_listed":0,"syntology":null},{"url":null,"slug":"questioning-the-validity-of-summarization","title":"Questioning the Validity of Summarization Datasets and Improving Their Factual Consistency","date":"2022-10-31","arxiv_id":"2210.17378","repositories_listed":0,"syntology":null},{"url":null,"slug":"probing-of-quantitative-values-in-abstractive","title":"Probing of Quantitative Values in Abstractive Summarization Models","date":"2022-10-03","arxiv_id":"2210.00667","repositories_listed":0,"syntology":null},{"url":null,"slug":"abstractive-approaches-to-multidocument","title":"Abstractive Approaches To Multidocument Summarization Of Medical Literature Reviews","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"lipkey-a-large-scale-news-dataset-for-absent","title":"LipKey: A Large-Scale News Dataset for Absent Keyphrases Generation and Abstractive Summarization","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"source-summary-entity-aggregation-in","title":"Source-summary Entity Aggregation in Abstractive Summarization","date":"2022-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/calibrating-sequence-likelihood-improves","slug":"calibrating-sequence-likelihood-improves","title":"Calibrating Sequence likelihood Improves Conditional Language Generation","date":"2022-09-30","arxiv_id":"2210.00045","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-and-selective","title":"Out-of-Distribution Detection and Selective Generation for Conditional Language Models","date":"2022-09-30","arxiv_id":"2209.15558","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-transformer-based-text-summarization","title":"Applying Transformer-based Text Summarization for Keyphrase Generation","date":"2022-09-08","arxiv_id":"2209.03791","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-semantic-understanding-with-self","title":"Enhancing Semantic Understanding with Self-supervised Methods for Abstractive Dialogue Summarization","date":"2022-09-01","arxiv_id":"2209.00278","repositories_listed":0,"syntology":null},{"url":null,"slug":"entity-based-de-noising-modeling-for","title":"Entity-based De-noising Modeling for Controllable Dialogue Summarization","date":"2022-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"forming-trees-with-treeformers","title":"Forming Trees with Treeformers","date":"2022-07-14","arxiv_id":"2207.06960","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-the-faithfulness-of-abstractive-1","title":"Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control","date":"2022-07-05","arxiv_id":"2207.02263","repositories_listed":0,"syntology":null},{"url":null,"slug":"dacsa-a-large-scale-dataset-for-automatic","title":"DACSA: A large-scale Dataset for Automatic summarization of Catalan and Spanish newspaper Articles","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null}],"record_sha256":"1331b30953878e85c09d939e9070a48bc0772d87d0bd27718bc86fca6677ed11","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}