https://github.com/tanyuqian/progressive-generation
Jointly Measuring Diversity and Quality in Text Generation Models
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Jointly Measuring Diversity and Quality in Text Generation Models
Enhancing Relation Extraction Using Syntactic Indicators and Sentential Contexts
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Show and Tell: Lessons learned from the 2015 MSCOCO Image Captioning Challenge
A Neural Attention Model for Abstractive Sentence Summarization
Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
Neural Machine Translation by Jointly Learning to Align and Translate
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
PubMed 200k RCT: a Dataset for Sequential Sentence Classification in Medical Abstracts
Neural Machine Translation by Jointly Learning to Align and Translate
Simulated Multiple Reference Training Improves Low-Resource Machine Translation
Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
On the Effect of Dropping Layers of Pre-trained Transformer Models
Neural Machine Translation by Jointly Learning to Align and Translate
Neural Machine Translation by Jointly Learning to Align and Translate
Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.