activity
20202023
most citedAdaptive Self-training for Few-shot Neural Sequence Labeling

34 citations · 51 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2023

Towards Poisoning Fair Representations

Tianci Liu, Haoyu Wang, Feijie Wu +4

Fair machine learning seeks to mitigate model prediction bias against certain demographic subgroups such as elder and female. Recently, fair representation learning (FRL) trained b…

cs.LG2023

SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification

Tianci Liu, Haoyu Wang, Yaqing Wang +3

Recent years have witnessed increasing concerns towards unfair decisions made by machine learning algorithms. To improve fairness in model decisions, various fairness notions have…

cs.CL2022★ 1 cited

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…

cs.CL2022★ 12 cited

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…

cs.CL2021★ 1 cited

LiST: Lite Prompted Self-training Makes Parameter-Efficient Few-shot Learners

Yaqing Wang, Subhabrata Mukherjee, Xiaodong Liu +3

We present a new method LiST is short for Lite Prompted Self-Training for parameter-efficient fine-tuning of large pre-trained language models (PLMs) for few-shot learning. LiST im…

cs.CL2021

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…

cs.CL2020★ 34 cited

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…

cs.LG2020★ 3 cited

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…