https://github.com/xnliang98/uke_ccrank
공식 코드Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context
Papers with Code 아카이브
Keyphrase Extraction
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A classic task to extract salient phrases that best summarize a document, which essentially has two stages: candidate generation and keyphrase ranking.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yan-xinyi/ssb_kpe
공식 코드Enhancing Keyphrase Extraction from Academic Articles Using Section Structure Information
https://github.com/2023-MindSpore-4/Code4/tree/main/FBPrompt-main
Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answering
https://github.com/AnzorGozalishvili/embedrank_serving
Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
https://github.com/AnzorGozalishvili/unsupervised_keyword_extraction
Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
https://github.com/LIAAD/KeywordExtractor-Datasets
https://github.com/UnknownGenie/altered-BERT-KPE
Capturing Global Informativeness in Open Domain Keyphrase Extraction
https://github.com/Varan7/Hashtag-Recommendation
https://github.com/adlnlp/Chulo
ChuLo: Chunk-Level Key Information Representation for Long Document Processing
https://github.com/epapagia/LocalVectors_AKE
Unsupervised Keyphrase Extraction from Scientific Publications
https://github.com/manikandan-ravikiran/complex-assignments
https://github.com/microsoft/MSMARCO-OpenKP
Open Domain Web Keyphrase Extraction Beyond Language Modeling
https://github.com/microsoft/OpenKP
Open Domain Web Keyphrase Extraction Beyond Language Modeling
https://github.com/mon95/deep-keyphrase
https://github.com/morningmoni/LCGen-eval
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation
https://github.com/nju-websoft/FBPrompt
Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answering
https://github.com/nku-hlt/promptrank
https://github.com/sduari/keyword-extraction-datasets
https://github.com/supercoderhawk/deep-keyphrase
https://github.com/talmago/spacy_ke
https://github.com/talmago/spacy_yake
https://github.com/yangyucheng000/Paper-3/tree/main/FBPrompt
Enhancing In-Context Learning with Answer Feedback for Multi-Span Question Answering
https://github.com/ygorg/JCDL_2020_KPE_Eval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.