61 citations · 93 across the 8 of their papers we have counts for
9 papers
Continual Fine-Tuning with Provably Accurate and Parameter-Free Task Retrieval
Hang Thi-Thuy Le, Long Minh Bui, Minh Hoang +1
Continual fine-tuning aims to adapt a pre-trained backbone to new tasks sequentially while preserving performance on earlier tasks whose data are no longer available. Existing appr…
LeBenchmark 2.0: a Standardized, Replicable and Enhanced Framework for Self-supervised Representations of French Speech
Titouan Parcollet, Ha Nguyen, Solene Evain +19
Self-supervised learning (SSL) is at the origin of unprecedented improvements in many different domains including computer vision and natural language processing. Speech processing…
Pre-training for Speech Translation: CTC Meets Optimal Transport
Phuong-Hang Le, Hongyu Gong, Changhan Wang +3
The gap between speech and text modalities is a major challenge in speech-to-text translation (ST). Different methods have been proposed to reduce this gap, but most of them requir…
Integrating Semantic Information into Sketchy Reading Module of Retro-Reader for Vietnamese Machine Reading Comprehension
Hang Thi-Thu Le, Viet-Duc Ho, Duc-Vu Nguyen +1
Machine Reading Comprehension has become one of the most advanced and popular research topics in the fields of Natural Language Processing in recent years. The classification of an…
Lightweight Adapter Tuning for Multilingual Speech Translation
Hang Le, Juan Pino, Changhan Wang +3
Adapter modules were recently introduced as an efficient alternative to fine-tuning in NLP. Adapter tuning consists in freezing pretrained parameters of a model and injecting light…
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from Speech
Solene Evain, Ha Nguyen, Hang Le +15
Self-Supervised Learning (SSL) using huge unlabeled data has been successfully explored for image and natural language processing. Recent works also investigated SSL from speech. T…