3 citations · 3 across the 3 of their papers we have counts for
5 papers
Visual Semantic Entropy: Do Vision Language Models Recognize Visual Ambiguity?
Ta Duc Huy, Trang Nguyen, Townim Chowdhury +5
Vision-language models can produce confident answers on visually ambiguous inputs, resulting in biased predictions. Common entropy-based methods, such as Semantic Entropy (SE), rel…
Localizing Before Answering: A Hallucination Evaluation Benchmark for Grounded Medical Multimodal LLMs
Dung Nguyen, Minh Khoi Ho, Huy Ta +11
Medical Large Multi-modal Models (LMMs) have demonstrated remarkable capabilities in medical data interpretation. However, these models frequently generate hallucinations contradic…
AR&D: A Framework for Retrieving and Describing Concepts for Interpreting AudioLLMs
Townim Faisal Chowdhury, Ta Duc Huy, Siqi Pan +2
Despite strong performance in audio perception tasks, large audio-language models (AudioLLMs) remain opaque to interpretation. A major factor behind this lack of interpretability i…
From Healthy Scans to Annotated Tumors: A Tumor Fabrication Framework for 3D Brain MRI Synthesis
Nayu Dong, Townim Chowdhury, Hieu Phan +3
The scarcity of annotated Magnetic Resonance Imaging (MRI) tumor data presents a major obstacle to accurate and automated tumor segmentation. While existing data synthesis methods…
Looking in the mirror: A faithful counterfactual explanation method for interpreting deep image classification models
Townim Faisal Chowdhury, Vu Minh Hieu Phan, Kewen Liao +5
Counterfactual explanations (CFE) for deep image classifiers aim to reveal how minimal input changes lead to different model decisions, providing critical insights for model interp…