Tae-Sun Chung — accepted AI-conference papers

2024

Multi-Channel Spatio-Temporal Transformer for Sign Language Production

COLING 2024main

The task of Sign Language Production (SLP) in machine learning involves converting text-based spoken language into corresponding sign language expressions. Sign language conveys meaning through the continuous movement of multiple articulators, including manual and non-manual channels. However, most…

Cited by 3 Source ↗PDF ↗Scholar ↗

2022

PCEE-BERT: Accelerating BERT Inference via Patient and Confident Early Exiting

Zhen Zhang, Wei Zhu, Jinfan Zhang, Peng Wang, Rize Jin, Tae-Sun Chung

NAACL 2022findings

BERT and other pretrained language models (PLMs) are ubiquitous in modern NLP. Even though PLMs are the state-of-the-art (SOTA) models for almost every NLP task (CITATION), the significant latency during inference prohibits wider industrial usage. In this work, we propose Patient and Confident Early…

Cited by 36 Source ↗PDF ↗code ↗Scholar ↗