3 papers
cs.AI2025
Rebellion: Noise-Robust Reasoning Training for Audio Reasoning Models
Tiansheng Huang, Virat Shejwalkar, Oscar Chang +2
Instilling reasoning capabilities in large models (LMs) using reasoning training (RT) significantly improves LMs' performances. Thus Audio Reasoning Models (ARMs), i.e., audio LMs…
cs.SD2025
Multilingual and Multi-Accent Jailbreaking of Audio LLMs
Jaechul Roh, Virat Shejwalkar, Amir Houmansadr
Large Audio Language Models (LALMs) have significantly advanced audio understanding but introduce critical security risks, particularly through audio jailbreaks. While prior work h…
cs.CR2025
Decoding FL Defenses: Systemization, Pitfalls, and Remedies
Momin Ahmad Khan, Virat Shejwalkar, Yasra Chandio +2
While the community has designed various defenses to counter the threat of poisoning attacks in Federated Learning (FL), there are no guidelines for evaluating these defenses. Thes…