106 citations · 171 across the 12 of their papers we have counts for
6 papers · 1 filter
Reducing Target Group Bias in Hate Speech Detectors
Darsh J Shah, Sinong Wang, Han Fang +2
The ubiquity of offensive and hateful content on online fora necessitates the need for automatic solutions that detect such content competently across target groups. In this paper…
Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models
Qinyuan Ye, Madian Khabsa, Mike Lewis +3
Distilling state-of-the-art transformer models into lightweight student models is an effective way to reduce computation cost at inference time. The student models are typically co…
Luna: Linear Unified Nested Attention
Xuezhe Ma, Xiang Kong, Sinong Wang +4
The quadratic computational and memory complexities of the Transformer's attention mechanism have limited its scalability for modeling long sequences. In this paper, we propose Lun…
Entailment as Few-Shot Learner
Sinong Wang, Han Fang, Madian Khabsa +2
Large pre-trained language models (LMs) have demonstrated remarkable ability as few-shot learners. However, their success hinges largely on scaling model parameters to a degree tha…
On Unifying Misinformation Detection
Nayeon Lee, Belinda Z. Li, Sinong Wang +4
In this paper, we introduce UnifiedM2, a general-purpose misinformation model that jointly models multiple domains of misinformation with a single, unified setup. The model is trai…
On the Influence of Masking Policies in Intermediate Pre-training
Qinyuan Ye, Belinda Z. Li, Sinong Wang +5
Current NLP models are predominantly trained through a two-stage "pre-train then fine-tune" pipeline. Prior work has shown that inserting an intermediate pre-training stage, using…