Papers with Code 아카이브
Semantic Similarity
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 28
- 보존된 평가 기록
- 21
The main objective Semantic Similarity is to measure the distance between the semantic meanings of a pair of words, phrases, sentences, or documents. For example, the word “car” is more similar to “bus” than it is to “cat”. The two main approaches to measuring Semantic Similarity are knowledge-based approaches and corpus-based, distributional methods.
Source: Visual and Semantic Knowledge Transfer for Large Scale Semi-supervised Object Detection
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/aranciokov/ranp
https://github.com/arukavina/baking-lyrics
https://github.com/asgaardlab/test-case-similarity-technique
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/asreview/asreview-multilingual-feature-extractor
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/autumn0409/Log-based-Anomaly-Detection-System
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/avi-jit/SWOW-eval
Problems With Evaluation of Word Embeddings Using Word Similarity Tasks
https://github.com/bhoov/ngd-vis
A mathematical theory of semantic development in deep neural networks
https://github.com/bigscience-workshop/biomedical
https://github.com/binwang28/rse
What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study
https://github.com/bio-ontology-research-group/EL2Box_embedding
EL Embeddings: Geometric construction of models for the Description Logic EL ++
https://github.com/bm-k/kosentencebert-skt
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/bojone/labse
https://github.com/brightjade/CS492E-CiteRec
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/bunny98/Text-to-Image-Using-GAN
https://github.com/carrliitos/NLPInformationExtraction
Description and Evaluation of Semantic Similarity Measures Approaches
https://github.com/cea-list/sce
Similarity Contrastive Estimation for Self-Supervised Soft Contrastive Learning
https://github.com/chalothon/Skip-Thought
https://github.com/chunhuililili/mt_dnn
https://github.com/cmdowney88/embeddingstructure
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
https://github.com/complementizer/rl-sentence-compression
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
https://github.com/croitorualin/reverse-stable-diffusion
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/cui0523/Code6/tree/main/ernie
ERNIE: Enhanced Representation through Knowledge Integration
https://github.com/daniel-hain/ML_course_maastricht
https://github.com/dasguptar/treelstm.pytorch
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
https://github.com/dashayushman/TAC-GAN
https://github.com/datcancode/sentence-transformers
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/dichotomies/proxy-nca
https://github.com/dmlc/dgl/tree/master/examples/mxnet/tree_lstm
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
https://github.com/dmlc/dgl/tree/master/examples/pytorch/tree_lstm
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
https://github.com/dmmiller612/bert-extractive-summarizer
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
https://github.com/drmuskangarg/WellnessDimensions
Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental Health
https://github.com/dwright37/phylogenetic-autoencoder
https://github.com/dyashkir/todo-ideas-links
https://github.com/edilsonacjr/semantic_flow
https://github.com/eelenadelolmo/WordVectors
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.