1 citations · 1 across the 3 of their papers we have counts for
4 papers
TabFlex: Scaling Tabular Learning to Millions with Linear Attention
Yuchen Zeng, Tuan Dinh, Wonjun Kang +1
Leveraging the in-context learning (ICL) capability of Large Language Models (LLMs) for tabular classification has gained significant attention for its training-free adaptability a…
SuoiAI: Building a Dataset for Aquatic Invertebrates in Vietnam
Tue Vo, Lakshay Sharma, Tuan Dinh +5
Understanding and monitoring aquatic biodiversity is critical for ecological health and conservation efforts. This paper proposes SuoiAI, an end-to-end pipeline for building a data…
Investigating Training Strategies and Model Robustness of Low-Rank Adaptation for Language Modeling in Speech Recognition
Yu Yu, Chao-Han Huck Yang, Tuan Dinh +10
The use of low-rank adaptation (LoRA) with frozen pretrained language models (PLMs) has become increasing popular as a mainstream, resource-efficient modeling approach for memory-c…
Low-rank Adaptation of Large Language Model Rescoring for Parameter-Efficient Speech Recognition
Yu Yu, Chao-Han Huck Yang, Jari Kolehmainen +15
We propose a neural language modeling system based on low-rank adaptation (LoRA) for speech recognition output rescoring. Although pretrained language models (LMs) like BERT have s…