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Document Summarization
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Automatic Document Summarization is the task of rewriting a document into its shorter form while still retaining its important content. The most popular two paradigms are extractive approaches and abstractive approaches. Extractive approaches generate summaries by extracting parts of the original document (usually sentences), while abstractive methods may generate new words or phrases which are not in the original document.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tencent-ailab/lodoss
공식 코드Toward Unifying Text Segmentation and Long Document Summarization
https://github.com/tensorflow/ranking
공식 코드TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank
https://github.com/tensorflow/tensor2tensor
공식 코드https://github.com/thefonseca/factorsum
공식 코드Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents
https://github.com/ucfnlp/endorser-summ
공식 코드Modeling Endorsement for Multi-Document Abstractive Summarization
https://github.com/ucfnlp/multidoc_summarization
공식 코드Adapting the Neural Encoder-Decoder Framework from Single to Multi-Document Summarization
https://github.com/ucfnlp/summarization-dpp-capsnet
공식 코드https://github.com/ucfnlp/summarization-sing-pair-mix
공식 코드Scoring Sentence Singletons and Pairs for Abstractive Summarization
https://github.com/vidhishanair/structured_summarizer
공식 코드https://github.com/wbbeyourself/scm4llms
공식 코드Enhancing Large Language Model with Self-Controlled Memory Framework
https://github.com/webis-de/scolia25-xsum
공식 코드Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization
https://github.com/webis-de/summary-explorer
공식 코드Summary Explorer: Visualizing the State of the Art in Text Summarization
https://github.com/whl97/LS-Score
공식 코드Unsupervised Reference-Free Summary Quality Evaluation via Contrastive Learning
https://github.com/xinnuoxu/miranews
공식 코드MiRANews: Dataset and Benchmarks for Multi-Resource-Assisted News Summarization
https://github.com/xlhex/nlg_api_watermark
공식 코드Protecting Intellectual Property of Language Generation APIs with Lexical Watermark
https://github.com/xnliang98/c2f-far
공식 코드https://github.com/xssstory/STAS
공식 코드Unsupervised Extractive Summarization by Pre-training Hierarchical Transformers
https://github.com/yale-nlp/odsum
공식 코드ODSum: New Benchmarks for Open Domain Multi-Document Summarization
https://github.com/yaolu/Multi-XScience
공식 코드https://github.com/yeliu918/hetformer
공식 코드HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization
https://github.com/yema2018/attention-aware
공식 코드Global-aware Beam Search for Neural Abstractive Summarization
https://github.com/yema2018/global_aware
공식 코드Global-aware Beam Search for Neural Abstractive Summarization
https://github.com/yg211/acl20-ref-free-eval
공식 코드SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization
https://github.com/yunzhusong/NAACL2022-REFLECT
공식 코드Improving Multi-Document Summarization through Referenced Flexible Extraction with Credit-Awareness
https://github.com/zhaochaocs/mds-dr
공식 코드Read Top News First: A Document Reordering Approach for Multi-Document News Summarization
https://github.com/10-zin/Synthesizer
Synthesizer: Rethinking Self-Attention in Transformer Models
https://github.com/2023-MindSpore-1/ms-code-154
https://github.com/2023-MindSpore-1/ms-code-164
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/t5
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/big_bird
https://github.com/AIKevin/Pointer_Generator_Summarizer
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/AndreyKolomiets/News_Headline_Generation
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/ArvinZhuang/BiTAG
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
https://github.com/ArvindSridhar/AbstractiveTextSummarization
Get To The Point: Summarization with Pointer-Generator Networks
https://github.com/BBuf/GLM
GLM: General Language Model Pretraining with Autoregressive Blank Infilling
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