{"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/text-summarization/papers/7","list_of":"/task/text-summarization","task":"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":7,"pages_in_order":14,"rows_per_page":100,"rows":[601,700],"of":1340,"counts":{"archive_papers_tagged":1340,"with_a_code_link":440,"where_syntology_ran_a_sample":84,"not_listed_spam_title":0,"listed":1340,"listed_where_code_ran":84,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":70,"every_run_a_failure_of_syntologys_instrument":14,"listed_with_a_run_with_no_instrument_failure":70,"listed_every_run_a_failure_of_syntologys_instrument":14,"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/text-summarization","prev":"/task/text-summarization/papers/6","next":"/task/text-summarization/papers/8","papers":[{"url":null,"slug":"leveraging-deep-learning-for-abstractive-code","title":"Leveraging Deep Learning for Abstractive Code Summarization of Unofficial Documentation","date":"2023-10-23","arxiv_id":"2310.15015","repositories_listed":0,"syntology":null},{"url":null,"slug":"controlled-randomness-improves-the","title":"Controlled Randomness Improves the Performance of Transformer Models","date":"2023-10-20","arxiv_id":"2310.13526","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-information-extraction-a-review-of","title":"Open Information Extraction: A Review of Baseline Techniques, Approaches, and Applications","date":"2023-10-18","arxiv_id":"2310.11644","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-news-summerization","title":"Automatic News Summerization","date":"2023-10-17","arxiv_id":"2310.11520","repositories_listed":0,"syntology":null},{"url":null,"slug":"key-phrase-boosted-unsupervised-summary","title":"Key-phrase boosted unsupervised summary generation for FinTech organization","date":"2023-10-16","arxiv_id":"2310.10294","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":"surveying-the-landscape-of-text-summarization","title":"Surveying the Landscape of Text Summarization with Deep Learning: A Comprehensive Review","date":"2023-10-13","arxiv_id":"2310.09411","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":"constructive-large-language-models-alignment","title":"Constructive Large Language Models Alignment with Diverse Feedback","date":"2023-10-10","arxiv_id":"2310.06450","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-and-human-ai-interactive-text","title":"Automatic and Human-AI Interactive Text Generation","date":"2023-10-05","arxiv_id":"2310.03878","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-fine-tuning-of-llms-on-the-very","title":"Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly","date":"2023-10-04","arxiv_id":"2310.03150","repositories_listed":0,"syntology":null},{"url":null,"slug":"sweeping-heterogeneity-with-smart-mops","title":"Sweeping Heterogeneity with Smart MoPs: Mixture of Prompts for LLM Task Adaptation","date":"2023-10-04","arxiv_id":"2310.02842","repositories_listed":0,"syntology":null},{"url":null,"slug":"error-norm-truncation-robust-training-in-the","title":"Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models","date":"2023-10-02","arxiv_id":"2310.00840","repositories_listed":0,"syntology":null},{"url":null,"slug":"neuro-symbolic-reasoning-for-planning","title":"Neuro Symbolic Reasoning for Planning: Counterexample Guided Inductive Synthesis using Large Language Models and Satisfiability Solving","date":"2023-09-28","arxiv_id":"2309.16436","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":"summarization-is-almost-dead","title":"Summarization is (Almost) Dead","date":"2023-09-18","arxiv_id":"2309.09558","repositories_listed":0,"syntology":null},{"url":null,"slug":"2309-06009","title":"Content Reduction, Surprisal and Information Density Estimation for Long Documents","date":"2023-09-12","arxiv_id":"2309.06009","repositories_listed":0,"syntology":null},{"url":null,"slug":"serving-moe-models-on-resource-constrained","title":"SwapMoE: Serving Off-the-shelf MoE-based Large Language Models with Tunable Memory Budget","date":"2023-08-29","arxiv_id":"2308.15030","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-depth-between-beam-search-and","title":"On the Depth between Beam Search and Exhaustive Search for Text Generation","date":"2023-08-25","arxiv_id":"2308.13696","repositories_listed":0,"syntology":null},{"url":null,"slug":"summhelper-collaborative-human-computer","title":"SummHelper: Collaborative Human-Computer Summarization","date":"2023-08-16","arxiv_id":"2308.08363","repositories_listed":0,"syntology":null},{"url":null,"slug":"bus-efficient-and-effective-vision-language","title":"BUS:Efficient and Effective Vision-language Pre-training with Bottom-Up Patch Summarization","date":"2023-07-17","arxiv_id":"2307.08504","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-neural-symbolic-approach-towards","title":"A Neural-Symbolic Approach Towards Identifying Grammatically Correct Sentences","date":"2023-07-16","arxiv_id":"2307.08036","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-biomedical-text-summarization-and","title":"Enhancing Biomedical Text Summarization and Question-Answering: On the Utility of Domain-Specific Pre-Training","date":"2023-07-10","arxiv_id":"2307.04412","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":"leveraging-gpt-4-for-food-effect","title":"Leveraging GPT-4 for Food Effect Summarization to Enhance Product-Specific Guidance Development via Iterative Prompting","date":"2023-06-28","arxiv_id":"2306.16275","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":"one-model-to-rule-them-all-ranking-slovene","title":"One model to rule them all: ranking Slovene summarizers","date":"2023-06-20","arxiv_id":"2306.11518","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-natural-language-processing-and-2","title":"Using Natural Language Processing and Networks to Automate Structured Literature Reviews: An Application to Farmers Climate Change Adaptation","date":"2023-06-16","arxiv_id":"2306.09737","repositories_listed":0,"syntology":null},{"url":null,"slug":"opportunities-and-challenges-for-chatgpt-and","title":"Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health","date":"2023-06-15","arxiv_id":"2306.10070","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-vs-human-authored-text-insights-into","title":"ChatGPT vs Human-authored Text: Insights into Controllable Text Summarization and Sentence Style Transfer","date":"2023-06-13","arxiv_id":"2306.07799","repositories_listed":0,"syntology":null},{"url":null,"slug":"correction-of-errors-in-preference-ratings","title":"Correction of Errors in Preference Ratings from Automated Metrics for Text Generation","date":"2023-06-06","arxiv_id":"2306.03866","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-gpt-model-pre-training-using-tensor","title":"Efficient GPT Model Pre-training using Tensor Train Matrix Representation","date":"2023-06-05","arxiv_id":"2306.02697","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":"hybrid-long-document-summarization-using-c2f","title":"Hybrid Long Document Summarization using C2F-FAR and ChatGPT: A Practical Study","date":"2023-06-01","arxiv_id":"2306.01169","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":"aakos-aspect-adaptive-knowledge-based-opinion","title":"AaKOS: Aspect-adaptive Knowledge-based Opinion Summarization","date":"2023-05-26","arxiv_id":"2306.05537","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":"dolphin-a-challenging-and-diverse-benchmark","title":"Dolphin: A Challenging and Diverse Benchmark for Arabic NLG","date":"2023-05-24","arxiv_id":"2305.14989","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-summary-useful-or-not-an-extrinsic-human","title":"Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks","date":"2023-05-24","arxiv_id":"2305.15044","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":"optimizing-non-autoregressive-transformers","title":"Optimizing Non-Autoregressive Transformers with Contrastive Learning","date":"2023-05-23","arxiv_id":"2305.13667","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":"semantic-similarity-measure-of-natural","title":"Semantic Similarity Measure of Natural Language Text through Machine Learning and a Keyword-Aware Cross-Encoder-Ranking Summarizer -- A Case Study Using UCGIS GIS&T Body of Knowledge","date":"2023-05-17","arxiv_id":"2305.09877","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-unifying-multi-lingual-and-cross","title":"Towards Unifying Multi-Lingual and Cross-Lingual Summarization","date":"2023-05-16","arxiv_id":"2305.09220","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-in-one-a-model-hijacking-attack-against","title":"Two-in-One: A Model Hijacking Attack Against Text Generation Models","date":"2023-05-12","arxiv_id":"2305.07406","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":"gpt-4-a-review-on-advancements-and","title":"Gpt-4: A Review on Advancements and Opportunities in Natural Language Processing","date":"2023-05-04","arxiv_id":"2305.03195","repositories_listed":0,"syntology":null},{"url":null,"slug":"backdoor-learning-on-sequence-to-sequence","title":"Backdoor Learning on Sequence to Sequence Models","date":"2023-05-03","arxiv_id":"2305.02424","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-chatgpt-pass-an-introductory-level","title":"Can ChatGPT Pass An Introductory Level Functional Language Programming Course?","date":"2023-04-29","arxiv_id":"2305.02230","repositories_listed":0,"syntology":null},{"url":null,"slug":"chatgpt-a-blessing-or-a-curse-for","title":"ChatGPT in the Classroom: An Analysis of Its Strengths and Weaknesses for Solving Undergraduate Computer Science Questions","date":"2023-04-28","arxiv_id":"2304.14993","repositories_listed":0,"syntology":null},{"url":null,"slug":"prompt-engineering-for-healthcare","title":"Prompt Engineering for Healthcare: Methodologies and Applications","date":"2023-04-28","arxiv_id":"2304.14670","repositories_listed":0,"syntology":null},{"url":null,"slug":"covsumm-an-unsupervised-transformer-cum-graph","title":"CovSumm: an unsupervised transformer-cum-graph-based hybrid document summarization model for CORD-19","date":"2023-04-26","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-federated-learning-via-gradient","title":"Personalized Federated Learning via Gradient Modulation for Heterogeneous Text Summarization","date":"2023-04-23","arxiv_id":"2304.11524","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-biomedical-text-summarization","title":"A Survey for Biomedical Text Summarization: From Pre-trained to Large Language Models","date":"2023-04-18","arxiv_id":"2304.08763","repositories_listed":0,"syntology":null},{"url":null,"slug":"just-tell-me-prompt-engineering-in-business","title":"Just Tell Me: Prompt Engineering in Business Process Management","date":"2023-04-14","arxiv_id":"2304.07183","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-few-shot-prompts-with-relevant","title":"Automatic Semantic Augmentation of Language Model Prompts (for Code Summarization)","date":"2023-04-13","arxiv_id":"2304.06815","repositories_listed":0,"syntology":null},{"url":null,"slug":"explicit-and-implicit-semantic-ranking","title":"Explicit and Implicit Semantic Ranking Framework","date":"2023-04-11","arxiv_id":"2304.04918","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-summarization-via-chatgpt-for","title":"Extractive Summarization via ChatGPT for Faithful Summary Generation","date":"2023-04-09","arxiv_id":"2304.04193","repositories_listed":0,"syntology":null},{"url":null,"slug":"san-bert-extractive-summarization-for","title":"San-BERT: Extractive Summarization for Sanskrit Documents using BERT and it's variants","date":"2023-04-04","arxiv_id":"2304.01894","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparison-of-document-similarity","title":"A Comparison of Document Similarity Algorithms","date":"2023-04-03","arxiv_id":"2304.01330","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":"large-language-models-are-diverse-role","title":"Large Language Models are Diverse Role-Players for Summarization Evaluation","date":"2023-03-27","arxiv_id":"2303.15078","repositories_listed":0,"syntology":null},{"url":null,"slug":"spdf-sparse-pre-training-and-dense-fine","title":"SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models","date":"2023-03-18","arxiv_id":"2303.10464","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-feasibility-of-chatgpt-for","title":"Exploring the Feasibility of ChatGPT for Event Extraction","date":"2023-03-07","arxiv_id":"2303.03836","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-large-text-corpora-for-end-to-end","title":"Leveraging Large Text Corpora for End-to-End Speech Summarization","date":"2023-03-02","arxiv_id":"2303.00978","repositories_listed":0,"syntology":null},{"url":null,"slug":"uzbek-text-summarization-based-on-tf-idf","title":"Uzbek text summarization based on TF-IDF","date":"2023-03-01","arxiv_id":"2303.00461","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-informed-proposals-for-discrete","title":"Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation","date":"2023-02-27","arxiv_id":"2302.13929","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":"/paper/citationsum-citation-aware-graph-contrastive","slug":"citationsum-citation-aware-graph-contrastive","title":"CitationSum: Citation-aware Graph Contrastive Learning for Scientific Paper Summarization","date":"2023-01-26","arxiv_id":"2301.11223","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-the-trends-and-challenges-in","title":"A Review of the Trends and Challenges in Adopting Natural Language Processing Methods for Education Feedback Analysis","date":"2023-01-20","arxiv_id":"2301.08826","repositories_listed":0,"syntology":null},{"url":"/paper/document-summarization-with-text-segmentation","slug":"document-summarization-with-text-segmentation","title":"Document Summarization with Text Segmentation","date":"2023-01-20","arxiv_id":"2301.08817","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":"recommending-root-cause-and-mitigation-steps","title":"Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models","date":"2023-01-10","arxiv_id":"2301.03797","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-review-of-automatic-text","title":"A comprehensive review of automatic text summarization techniques: method, data, evaluation and coding","date":"2023-01-04","arxiv_id":"2301.03403","repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-text-summarization-using","title":"Extractive Text Summarization Using Generalized Additive Models with Interactions for Sentence Selection","date":"2022-12-21","arxiv_id":"2212.10707","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":"meeting-summarization-a-survey-of-the-state","title":"Meeting Summarization: A Survey of the State of the Art","date":"2022-12-16","arxiv_id":"2212.08206","repositories_listed":0,"syntology":null},{"url":null,"slug":"despite-super-human-performance-current-llms","title":"Despite \"super-human\" performance, current LLMs are unsuited for decisions about ethics and safety","date":"2022-12-13","arxiv_id":"2212.06295","repositories_listed":0,"syntology":null},{"url":null,"slug":"implementing-deep-learning-based-approaches","title":"Implementing Deep Learning-Based Approaches for Article Summarization in Indian Languages","date":"2022-12-12","arxiv_id":"2212.05702","repositories_listed":0,"syntology":null},{"url":null,"slug":"searching-for-effective-multilingual-fine-1","title":"Searching for Effective Multilingual Fine-Tuning Methods: A Case Study in Summarization","date":"2022-12-12","arxiv_id":"2212.05740","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":"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":"few-shot-query-focused-summarization-with","title":"Few-shot Query-Focused Summarization with Prefix-Merging","date":"2022-11-29","arxiv_id":"2211.16164","repositories_listed":0,"syntology":null},{"url":null,"slug":"best-k-search-algorithm-for-neural-text","title":"Best-$k$ Search Algorithm for Neural Text Generation","date":"2022-11-22","arxiv_id":"2211.11924","repositories_listed":0,"syntology":null},{"url":null,"slug":"creativesumm-shared-task-on-automatic-1","title":"CREATIVESUMM: Shared Task on Automatic Summarization for Creative Writing","date":"2022-11-10","arxiv_id":"2211.05886","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-prompt-tuning-for-text-summarization","title":"Latent Prompt Tuning for Text Summarization","date":"2022-11-03","arxiv_id":"2211.01837","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-text-summarization-of-long","title":"Unsupervised Text Summarization of Long Documents using Dependency-based Noun Phrases and Contextual Order Arrangement","date":"2022-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-pre-trained-models-for-failure","title":"Leveraging Pre-trained Models for Failure Analysis Triplets Generation","date":"2022-10-31","arxiv_id":"2210.17497","repositories_listed":0,"syntology":null},{"url":null,"slug":"lans-large-scale-arabic-news-summarization","title":"LANS: Large-scale Arabic News Summarization Corpus","date":"2022-10-24","arxiv_id":"2210.13600","repositories_listed":0,"syntology":null},{"url":null,"slug":"social-biases-in-automatic-evaluation-metrics","title":"Social Biases in Automatic Evaluation Metrics for NLG","date":"2022-10-17","arxiv_id":"2210.08859","repositories_listed":0,"syntology":null},{"url":null,"slug":"can-language-representation-models-think-in","title":"Can Language Representation Models Think in Bets?","date":"2022-10-14","arxiv_id":"2210.07519","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-graph-based-text-representations","title":"Improving Graph-Based Text Representations with Character and Word Level N-grams","date":"2022-10-12","arxiv_id":"2210.05999","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical3d-adapters-for-long-video-to","title":"Hierarchical3D Adapters for Long Video-to-text Summarization","date":"2022-10-10","arxiv_id":"2210.04829","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":"a-survey-of-automatic-text-summarization","title":"A Survey of Automatic Text Summarization Using Graph Neural Networks","date":"2022-10-01","arxiv_id":null,"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}],"record_sha256":"716d571df24eb926d957ea611199ad890d6bbddfcb920d1fbb82583dd7611db4","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}