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11/15/2022
A Universal Discriminator for Zero-Shot Generalization
Generative modeling has been the dominant approach for large-scale pretr...
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11/09/2022
Zero-Label Prompt Selection
Natural language prompts have been shown to facilitate cross-task genera...
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11/08/2022
Prompt-Based Metric Learning for Few-Shot NER
Few-shot named entity recognition (NER) targets generalizing to unseen l...
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07/01/2022
On the Performance of Data Compression in Clustered Fog Radio Access Networks
The fog-radio-access-network (F-RAN) has been proposed to address the st...
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11/07/2021
NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Framework
Pretrained language models have become the standard approach for many NL...
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09/27/2021
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding
The few-shot natural language understanding (NLU) task has attracted muc...
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08/13/2021
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning
Most previous methods for text data augmentation are limited to simple t...
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03/18/2021
GPT Understands, Too
While GPTs with traditional fine-tuning fail to achieve strong results o...
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12/01/2020