3 papers
cs.CV2025
Promptception: How Sensitive Are Large Multimodal Models to Prompts?
Mohamed Insaf Ismithdeen, Muhammad Uzair Khattak, Salman Khan
Despite the success of Large Multimodal Models (LMMs) in recent years, prompt design for LMMs in Multiple-Choice Question Answering (MCQA) remains poorly understood. We show that e…
cs.CV2025
MAGNET: A Multi-agent Framework for Finding Audio-Visual Needles by Reasoning over Multi-Video Haystacks
Sanjoy Chowdhury, Mohamed Elmoghany, Yohan Abeysinghe +5
Large multimodal models (LMMs) have shown remarkable progress in audio-visual understanding, yet they struggle with real-world scenarios that require complex reasoning across exten…
eess.AS2025
Aurelia: Test-time Reasoning Distillation in Audio-Visual LLMs
Sanjoy Chowdhury, Hanan Gani, Nishit Anand +5
Recent advancements in reasoning optimization have greatly enhanced the performance of large language models (LLMs). However, existing work fails to address the complexities of aud…