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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/thefonseca/factorsum
공식 코드Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents
https://github.com/thinkwee/DPP_CNN_Summarization
공식 코드https://github.com/tikhonovpavel/wikimulti
공식 코드https://github.com/tongbao96/code-for-sfr-as
공식 코드Enhancing Abstractive Summarization of Scientific Papers Using Structure Information
https://github.com/travel-go/Abstractive-Text-Summarization
공식 코드Contrastive Attention Mechanism for Abstractive Sentence Summarization
https://github.com/tshi04/LeafNATS
공식 코드LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization
https://github.com/tshi04/NATS
공식 코드Neural Abstractive Text Summarization with Sequence-to-Sequence Models
https://github.com/tsosea2/covidet-ext
공식 코드https://github.com/ucfnlp/cascaded-summ
공식 코드A Cascade Approach to Neural Abstractive Summarization with Content Selection and Fusion
https://github.com/ucfnlp/control-over-copying
공식 코드Controlling the Amount of Verbatim Copying in Abstractive Summarization
https://github.com/ucfnlp/endorser-summ
공식 코드Modeling Endorsement for Multi-Document Abstractive Summarization
https://github.com/ucfnlp/joint-parse-n-summarize
공식 코드https://github.com/ucfnlp/points-of-correspondence
공식 코드Understanding Points of Correspondence between Sentences for Abstractive Summarization
https://github.com/ucfnlp/summarization-sing-pair-mix
공식 코드Scoring Sentence Singletons and Pairs for Abstractive Summarization
https://github.com/utsjiyaoli/qa-attack
공식 코드Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial Approach
https://github.com/vanderpoelliam/cpmi
공식 코드Mutual Information Alleviates Hallucinations in Abstractive Summarization
https://github.com/varadhbhatnagar/fc-claim-det
공식 코드Harnessing Abstractive Summarization for Fact-Checked Claim Detection
https://github.com/vidhishanair/factedit
공식 코드https://github.com/vidhishanair/structured_summarizer
공식 코드https://github.com/vietai/vit5
공식 코드ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation
https://github.com/vinairesearch/bartpho
공식 코드BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese
https://github.com/violet-zct/fairseq-detect-hallucination
공식 코드Detecting Hallucinated Content in Conditional Neural Sequence Generation
https://github.com/wangclnlp/DeepSpeed-Chat-Extension/tree/main/examples/esrl
공식 코드ESRL: Efficient Sampling-based Reinforcement Learning for Sequence Generation
https://github.com/wendy-xiao/chatgpt_editing_summ
공식 코드Personalized Abstractive Summarization by Tri-agent Generation Pipeline
https://github.com/wendy-xiao/entity-based-spancopy
공식 코드Entity-based SpanCopy for Abstractive Summarization to Improve the Factual Consistency
https://github.com/wprojectsn/codes
공식 코드https://github.com/xbmxb/prom
공식 코드PROM: A Phrase-level Copying Mechanism with Pre-training for Abstractive Summarization
https://github.com/xieyxclack/factual_coco
공식 코드Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation
https://github.com/xl2248/sov-mas
공식 코드Summary-Oriented Vision Modeling for Multimodal Abstractive Summarization
https://github.com/xssstory/SeqCo
공식 코드https://github.com/yale-lily/dyle
공식 코드DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization
https://github.com/yaserkl/RLSeq2Seq
공식 코드https://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/yfqiu-nlp/hiergnn
공식 코드Abstractive Summarization Guided by Latent Hierarchical Document Structure
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