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Abstractive Text Summarization
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Abstractive Text Summarization is the task of generating a short and concise summary that captures the salient ideas of the source text. The generated summaries potentially contain new phrases and sentences that may not appear in the source text.
Source: Generative Adversarial Network for Abstractive Text Summarization
Image credit: Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Alibaba-NLP/CHRONOS
공식 코드Unfolding the Headline: Iterative Self-Questioning for News Retrieval and Timeline Summarization
https://github.com/Andrew03/transformer-abstractive-summarization
공식 코드Efficient Adaptation of Pretrained Transformers for Abstractive Summarization
https://github.com/ArrowHuang/NumHG
공식 코드https://github.com/CZWin32768/xnlg
공식 코드https://github.com/ChenRocks/fast_abs_rl
공식 코드Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting
https://github.com/HLTCHKUST/QFS
공식 코드Improve Query Focused Abstractive Summarization by Incorporating Answer Relevance
https://github.com/HadiAskari/Relevance-Paraphrasing
공식 코드Assessing LLMs for Zero-shot Abstractive Summarization Through the Lens of Relevance Paraphrasing
https://github.com/Hellisotherpeople/DebateSum
공식 코드DebateSum: A large-scale argument mining and summarization dataset
https://github.com/Hellisotherpeople/debate2vec
공식 코드DebateSum: A large-scale argument mining and summarization dataset
https://github.com/InitialBug/BiSET
공식 코드BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization
https://github.com/JC230903/NLP-low-resource-pipeline-for-indian-languages/tree/main/pythonversion
공식 코드Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline
https://github.com/JbRemy/Cahan
공식 코드Bidirectional Context-Aware Hierarchical Attention Network for Document Understanding
https://github.com/KaiQiangSong/struct_infused_summ
공식 코드Structure-Infused Copy Mechanisms for Abstractive Summarization
https://github.com/MiuLab/DialSum
공식 코드Abstractive Dialogue Summarization with Sentence-Gated Modeling Optimized by Dialogue Acts
https://github.com/OnlpLab/HeSum
공식 코드HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew
https://github.com/PrekshaNema25/DiverstiyBasedAttentionMechanism
공식 코드Diversity driven Attention Model for Query-based Abstractive Summarization
https://github.com/Prithwiraj12/Bengali-Deep-News-Summarization
공식 코드Bengali Abstractive News Summarization(BANS): A Neural Attention Approach
https://github.com/RUCAIBox/TextBox
공식 코드TextBox 2.0: A Text Generation Library with Pre-trained Language Models
https://github.com/SofeeyaJ/GASCADE_ECIR2025
공식 코드GASCADE: Grouped Summarization of Adverse Drug Event for Enhanced Cancer Pharmacovigilance
https://github.com/THUDM/GLM
공식 코드GLM: General Language Model Pretraining with Autoregressive Blank Infilling
https://github.com/TysonYu/AdaptSum
공식 코드AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization
https://github.com/UKPLab/tacl2025-ood-eval-self-rationalization
공식 코드Self-Rationalization in the Wild: A Large Scale Out-of-Distribution Evaluation on NLI-related tasks
https://github.com/W4ngatang/qags
공식 코드Asking and Answering Questions to Evaluate the Factual Consistency of Summaries
https://github.com/WoodenWhite/Centrality_Pre_Summ
공식 코드Exploring Explainable Selection to Control Abstractive Summarization
https://github.com/WoodenWhite/MCLAS
공식 코드Cross-Lingual Abstractive Summarization with Limited Parallel Resources
https://github.com/Yale-LILY/ConvoSumm
공식 코드https://github.com/Yale-LILY/dart
공식 코드https://github.com/YiSyuanChen/MTL-ABS
공식 코드Meta-Transfer Learning for Low-Resource Abstractive Summarization
https://github.com/ZNLP/sb-nmt
공식 코드Synchronous Bidirectional Inference for Neural Sequence Generation
https://github.com/ZhangShiyue/EmailSum
공식 코드https://github.com/abisee/pointer-generator
공식 코드Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/achaudhury/shmoop-corpus
공식 코드The Shmoop Corpus: A Dataset of Stories with Loosely Aligned Summaries
https://github.com/acohan/long-summarization
공식 코드A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
https://github.com/airi-institute/al_ats
공식 코드https://github.com/alebryvas/berk266
공식 코드Abstractive Summarization of Spoken andWritten Instructions with BERT
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