5 papers
Neural Nonmyopic Bayesian Optimization in Dynamic Cost Settings
Sang T. Truong, Duc Q. Nguyen, Willie Neiswanger +4
Bayesian optimization (BO) is a common framework for optimizing black-box functions, yet most existing methods assume static query costs and rely on myopic acquisition strategies.…
The Sound of Syntax: Finetuning and Comprehensive Evaluation of Language Models for Speech Pathology
Fagun Patel, Duc Q. Nguyen, Sang T. Truong +3
According to the U.S. National Institutes of Health, more than 3.4 million children experience speech disorders that require clinical intervention. The number of speech-language pa…
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
Gantavya Bhatt, Yifang Chen, Arnav M. Das +9
Supervised finetuning (SFT) on instruction datasets has played a crucial role in achieving the remarkable zero-shot generalization capabilities observed in modern large language mo…
Bridging Associative Memory and Probabilistic Modeling
Rylan Schaeffer, Nika Zahedi, Mikail Khona +9
Associative memory and probabilistic modeling are two fundamental topics in artificial intelligence. The first studies recurrent neural networks designed to denoise, complete and r…
Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models
Sang T. Truong, Duc Q. Nguyen, Toan Nguyen +4
Recent advancements in large language models (LLMs) have underscored their importance in the evolution of artificial intelligence. However, despite extensive pretraining on multili…