https://github.com/radoslawkrolikowski/sentiment-analysis-pytorch
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Semantic textual similarity deals with determining how similar two pieces of texts are. This can take the form of assigning a score from 1 to 5. Related tasks are paraphrase or duplicate identification.
Image source: Learning Semantic Textual Similarity from Conversations
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Generalized Product Quantization Network for Semi-supervised Image Retrieval
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
SqueezeBERT: What can computer vision teach NLP about efficient neural networks?
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Supervised Learning of Universal Sentence Representations from Natural Language Inference Data
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
A Joint Sequence Fusion Model for Video Question Answering and Retrieval
Investigating the Effects of Word Substitution Errors on Sentence Embeddings
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Evaluating Multimodal Representations on Visual Semantic Textual Similarity
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.