Co-occurring keywords · papers mentioning both
Papers
Unregulated Chinese-to-English Data Expansion Does NOT Work for Neural Event Detection
COLING 2022
Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals
Interspeech 2022
Unsupervised Natural Language Inference Using PHL Triplet Generation
ACL 2022
Unsupervised Question Answering via Answer Diversifying
COLING 2022
Unsupervised Syntactically Controlled Paraphrase Generation with Abstract Meaning Representations
EMNLP 2022
Using Data Augmentation and Consistency Regularization to Improve Semi-supervised Speech Recognition
Interspeech 2022
Using Deep Mixture-of-Experts to Detect Word Meaning Shift for TempoWiC
EMNLP 2022
Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness
NeurIPS 2022
Using Neural Machine Translation Methods for Sign Language Translation
ACL 2022
UTNLP at SemEval-2022 Task 6: A Comparative Analysis of Sarcasm Detection Using Generative-based and Mutation-based Data Augmentation
SemEval 2022
UU-Tax at SemEval-2022 Task 3: Improving the generalizability of language models for taxonomy classification through data augmentation
SemEval 2022
Vega-MT: The JD Explore Academy Machine Translation System for WMT22
EMNLP 2022
ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
NeurIPS 2022
Virtual Augmentation Supported Contrastive Learning of Sentence Representations
ACL 2022
VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization
AAAI 2022
Voice Conversion Can Improve ASR in Very Low-Resource Settings
Interspeech 2022
VORTEX: Physics-Driven Data Augmentations Using Consistency Training for Robust Accelerated MRI Reconstruction
MIDL 2022
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation
EMNLP 2022
Wav2Vec-Aug: Improved self-supervised training with limited data
Interspeech 2022
WeSinger: Data-augmented Singing Voice Synthesis with Auxiliary Losses
Interspeech 2022
What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective
NeurIPS 2022
What Makes Better Augmentation Strategies? Augment Difficult but Not too Different
ICLR 2022
When and How Mixup Improves Calibration
ICML 2022
When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation
ACL 2022
When Is TTS Augmentation Through a Pivot Language Useful?
Interspeech 2022