Papers with Code 아카이브

Document Embedding

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

0

보존된 평가 기록

0

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/IAAR-Shanghai/QAEncoder

공식 코드

QAEncoder: Towards Aligned Representation Learning in Question Answering System

https://github.com/IBM/WordMoversEmbeddings

공식 코드

Word Mover's Embedding: From Word2Vec to Document Embedding

https://github.com/LanaChen0/Predict_News

공식 코드

Approach to Predicting News -- A Precise Multi-LSTM Network With BERT

https://github.com/MaartenGr/BERTopic

공식 코드

BERTopic: Neural topic modeling with a class-based TF-IDF procedure

https://github.com/eoghancunn/facilitating_idr

공식 코드

Facilitating Interdisciplinary Knowledge Transfer with Research Paper Recommender Systems

https://github.com/epfl-dlab/Cr5

공식 코드

Crosslingual Document Embedding as Reduced-Rank Ridge Regression

https://github.com/euranova/CASS-dataset

공식 코드

STRASS: A Light and Effective Method for Extractive Summarization Based on Sentence Embeddings

https://github.com/forrestbao/suenes

공식 코드

SueNes: A Weakly Supervised Approach to Evaluating Single-Document Summarization via Negative Sampling

https://github.com/gzerveas/CODER

공식 코드

CODER: An efficient framework for improving retrieval through COntextual Document Embedding Reranking

https://github.com/jayelm/broader-metaphor

공식 코드

Learning Outside the Box: Discourse-level Features Improve Metaphor Identification

https://github.com/jhlau/doc2vec

공식 코드

An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

https://github.com/linhanz/mderank

공식 코드

MDERank: A Masked Document Embedding Rank Approach for Unsupervised Keyphrase Extraction

https://github.com/maartengr/bertopic_evaluation

공식 코드

BERTopic: Neural topic modeling with a class-based TF-IDF procedure

https://github.com/malteos/scincl

공식 코드

Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings

https://github.com/predlico/aragog

공식 코드

ARAGOG: Advanced RAG Output Grading

https://github.com/rooooyy/hill

공식 코드

HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification

https://github.com/xnliang98/uke_ccrank

공식 코드

Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context

https://github.com/AlexMRuch/Can-x2vec-Save-Lives

Can x2vec Save Lives? Integrating Graph and Language Embeddings for Automatic Mental Health Classification

https://github.com/HelloRusk/hyperdoc2vec

hyperdoc2vec: Distributed Representations of Hypertext Documents

https://github.com/Niousha12/Text_Classification_via_GNN

Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks

https://github.com/bombdiggity/paper-bag

Document Embedding with Paragraph Vectors

https://github.com/cmasch/cnn-text-classification

Neural Document Embeddings for Intensive Care Patient Mortality Prediction

https://github.com/dhyeon/ingredient-vectors

Document Embedding with Paragraph Vectors

https://github.com/hithisisdhara/doc2vec

Document Embedding with Paragraph Vectors

https://github.com/inejc/paragraph-vectors

Document Embedding with Paragraph Vectors

https://github.com/johntailor/bertsenclu

BERTopic: Neural topic modeling with a class-based TF-IDF procedure

https://github.com/knowlab/bi-weekly-paper-presentation

Unsupervised Document Embedding via Contrastive Augmentation

https://github.com/rvstraalen/doc2vec-workshop

Document Embedding with Paragraph Vectors

https://github.com/sreejukomath/NLPProjects

An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

https://github.com/tsandefer/capstone_2

An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

https://github.com/tsandefer/dsi_capstone_2

An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.