https://github.com/EruM16/Attention-Seeker
공식 코드Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A classic task to extract salient phrases that best summarize a document, which essentially has two stages: candidate generation and keyphrase ranking.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction
Wizard of Search Engine: Access to Information Through Conversations with Search Engines
Enhancing Keyphrase Extraction from Long Scientific Documents using Graph Embeddings
MUG: A General Meeting Understanding and Generation Benchmark
How Document Pre-processing affects Keyphrase Extraction Performance
SimCKP: Simple Contrastive Learning of Keyphrase Representations
Enhancing Keyphrase Extraction from Academic Articles with their Reference Information
BibRank: Automatic Keyphrase Extraction Platform Using~Metadata
Persian Keyphrase Generation Using Sequence-to-Sequence Models
MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation
Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical Study
Hyperbolic Relevance Matching for Neural Keyphrase Extraction
Multi-Document Keyphrase Extraction: Dataset, Baselines and Review
Unsupervised Keyphrase Extraction via Interpretable Neural Networks
NORMY: Non-Uniform History Modeling for Open Retrieval Conversational Question Answering
Simple Unsupervised Keyphrase Extraction using Sentence Embeddings
Capturing Global Informativeness in Open Domain Keyphrase Extraction
Pre-trained Language Models for Keyphrase Generation: A Thorough Empirical Study
KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation
Topic Aware Contextualized Embeddings for High Quality Phrase Extraction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.