https://github.com/zcymonkey/attt2m
공식 코드AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanism
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AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanism
Dynamic Data Selection and Weighting for Iterative Back-Translation
Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-training
Graphine: A Dataset for Graph-aware Terminology Definition Generation
SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
Focus-Driven Contrastive Learniang for Medical Question Summarization
Bidirectional Transformer Reranker for Grammatical Error Correction
Revisiting Generative Commonsense Reasoning: A Pre-Ordering Approach
Can You Learn Semantics Through Next-Word Prediction? The Case of Entailment
Modeling Context With Linear Attention for Scalable Document-Level Translation
SSD: Towards Better Text-Image Consistency Metric in Text-to-Image Generation
Unsupervised Transfer of Semantic Role Models from Verbal to Nominal Domain
Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learner
Rethink about the Word-level Quality Estimation for Machine Translation from Human Judgement
Predicting the Quality of Revisions in Argumentative Writing
Abstract, Rationale, Stance: A Joint Model for Scientific Claim Verification
Anchoring Path for Inductive Relation Prediction in Knowledge Graphs
Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer
Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence Generation
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN
Robust Text Classification: Analyzing Prototype-Based Networks
SDA: Simple Discrete Augmentation for Contrastive Sentence Representation Learning
Understanding and Improving Transformer From a Multi-Particle Dynamic System Point of View
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.