Learning multilingual, multi-domain neural language models
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Updated
Jan 8, 2018 - Python
Learning multilingual, multi-domain neural language models
codes for paper "Domain Attention Model for Multi-Domain Sentiment Classification"
Pytorch Implementation of "Sequential Dialogue Context Modeling for Spoken Language Understanding( https://arxiv.org/abs/1705.03455 )"
Multi-domain NMT with token-level mixing model
CrossNER: Evaluating Cross-Domain Named Entity Recognition (AAAI-2021)
[ACCV 2018 Oral] Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
Pytorch implementation of "Multi-domain translation between single-cell imaging and sequencing data using autoencoders" (https://www.nature.com/articles/s41467-020-20249-2) with custom models.
Open source code for ACL 2020 Paper "Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog"
poste-sdk is a Python client library to work with poste.io API
M2D2: A Massively Multi-domain Language Modeling Dataset (EMNLP 2022) by Machel Reid, Victor Zhong, Suchin Gururangan, Luke Zettlemoyer
Source code for transferable dialogue state generator (TRADE, Wu et al., 2019). https://arxiv.org/abs/1905.08743
[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
Code implementation of "HAMUR: Hyper Adapter for Multi-Domain Recommendation" in CIKM‘2023
Framework for learning multi-domain image embeddings suitable for multi-domain image retrieval at instance-level
A framework for conducting Multi-task Multi-domain learning
This middleware enables Django projects to route requests to different URL configurations based on the domain of the incoming request.
Official code of XB-MAML implemented in pytorch
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