1 citations · 1 across the 5 of their papers we have counts for
5 papers
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi +2
Safety aligned Large Language Models (LLMs) are vulnerable to harmful fine-tuning attacks -- a few harmful data mixed in the fine-tuning dataset can break the LLMs's safety alignme…
CLIPSonic: Text-to-Audio Synthesis with Unlabeled Videos and Pretrained Language-Vision Models
Hao-Wen Dong, Xiaoyu Liu, Jordi Pons +5
Recent work has studied text-to-audio synthesis using large amounts of paired text-audio data. However, audio recordings with high-quality text annotations can be difficult to acqu…
Full-band General Audio Synthesis with Score-based Diffusion
Santiago Pascual, Gautam Bhattacharya, Chunghsin Yeh +2
Recent works have shown the capability of deep generative models to tackle general audio synthesis from a single label, producing a variety of impulsive, tonal, and environmental s…
Generative Adversarial Speaker Embedding Networks for Domain Robust End-to-End Speaker Verification
Gautam Bhattacharya, Joao Monteiro, Jahangir Alam +1
This article presents a novel approach for learning domain-invariant speaker embeddings using Generative Adversarial Networks. The main idea is to confuse a domain discriminator so…
Adapting End-to-End Neural Speaker Verification to New Languages and Recording Conditions with Adversarial Training
Gautam Bhattacharya, Jahangir Alam, Patrick Kenny
In this article we propose a novel approach for adapting speaker embeddings to new domains based on adversarial training of neural networks. We apply our embeddings to the task of…