Multimodal Transformer
[ACL'19] [PyTorch] Multimodal Transformer
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Multimodal Transformer | 418 | 2 years ago | 8 | mit | Python | |||||
| [ACL'19] [PyTorch] Multimodal Transformer | ||||||||||
| Nlp Papers | 248 | 3 years ago | ||||||||
| Papers I have read, mainly about NLP. Welcome everyone to supplement in issue. | ||||||||||
| Zero | 131 | a year ago | bsd-3-clause | Python | ||||||
| Zero -- A neural machine translation system | ||||||||||
| Atpapers | 105 | 3 years ago | ||||||||
| Worth-reading papers and related resources on attention mechanism, Transformer and pretrained language model (PLM) such as BERT. 值得一读的注意力机制、Transformer和预训练语言模型论文与相关资源集合 | ||||||||||
| Interpretablenlp | 70 | 3 years ago | mit | |||||||
| A list of publications on NLP interpretability (Welcome PR) | ||||||||||
| Text Summarization | 34 | 6 years ago | ||||||||
| Abstractive and Extractive Deep Learning Methods for Text Summarisation | ||||||||||
| Affective Attention | 26 | 4 years ago | 2 | Python | ||||||
| Source code for the ACL 2019 paper "Attention-based Conditioning Methods for External Knowledge Integration" | ||||||||||
| Layer_augmentation | 23 | 3 years ago | 4 | apache-2.0 | Python | |||||
| Implementation of the NLI model in our ACL 2019 paper: Augmenting Neural Networks with First-order Logic. | ||||||||||
| Acl2019 Commonsense | 13 | 2 years ago | 5 | apache-2.0 | Python | |||||
| Source code for the paper "Attention Is (not) All You Need for Commonsense Reasoning" published at ACL 2019. | ||||||||||
| Pytorch_relationextraction_attentionbilstm | 12 | 5 years ago | 2 | Python | ||||||
| Pytorch Implementation of Attention-Based BiLSTM for Relation Extraction ("Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification" ACL 2016 http://www.aclweb.org/anthology/P16-2034) | ||||||||||
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