1 citations · 2 across the 6 of their papers we have counts for
6 papers
Scaling Open Discrete Audio Foundation Models with Interleaved Semantic, Acoustic, and Text Tokens
Potsawee Manakul, Woody Haosheng Gan, Martijn Bartelds +3
Current audio language models are predominantly text-first, either extending pre-trained text LLM backbones or relying on semantic-only audio tokens, limiting general audio modelin…
Who can we trust? LLM-as-a-jury for Comparative Assessment
Mengjie Qian, Guangzhi Sun, Mark J. F. Gales +1
Large language models (LLMs) are increasingly applied as automatic evaluators for natural language generation assessment often using pairwise comparative judgements. Existing appro…
Unlearning vs. Obfuscation: Are We Truly Removing Knowledge?
Guangzhi Sun, Potsawee Manakul, Xiao Zhan +1
Unlearning has emerged as a critical capability for large language models (LLMs) to support data privacy, regulatory compliance, and ethical AI deployment. Recent techniques often…
SkillAggregation: Reference-free LLM-Dependent Aggregation
Guangzhi Sun, Anmol Kagrecha, Potsawee Manakul +2
Large Language Models (LLMs) are increasingly used to assess NLP tasks due to their ability to generate human-like judgments. Single LLMs were used initially, however, recent work…
Enhancing Low-Resource Language and Instruction Following Capabilities of Audio Language Models
Potsawee Manakul, Guangzhi Sun, Warit Sirichotedumrong +2
Audio language models process audio inputs using textual prompts for tasks like speech recognition and audio captioning. Although built on multilingual pre-trained components, most…
TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
Jeff Hwang, Moto Hira, Caroline Chen +21
TorchAudio is an open-source audio and speech processing library built for PyTorch. It aims to accelerate the research and development of audio and speech technologies by providing…