3 citations · 4 across the 3 of their papers we have counts for
4 papers
AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning
Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee +4
Standard fine-tuning of large pre-trained language models (PLMs) for downstream tasks requires updating hundreds of millions to billions of parameters, and storing a large copy of…
Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework
Yaqing Wang, Haoda Chu, Chao Zhang +1
In this work, we study the problem of named entity recognition (NER) in a low resource scenario, focusing on few-shot and zero-shot settings. Built upon large-scale pre-trained lan…
Adaptive Self-training for Few-shot Neural Sequence Labeling
Yaqing Wang, Subhabrata Mukherjee, Haoda Chu +4
Sequence labeling is an important technique employed for many Natural Language Processing (NLP) tasks, such as Named Entity Recognition (NER), slot tagging for dialog systems and s…
Decomposed Adversarial Learned Inference
Alexander Hanbo Li, Yaqing Wang, Changyou Chen +1
Effective inference for a generative adversarial model remains an important and challenging problem. We propose a novel approach, Decomposed Adversarial Learned Inference (DALI), w…