21 citations · 22 across the 18 of their papers we have counts for
18 papers · 1 filter
Fighting Hallucinations with Counterfactuals: Diffusion-Guided Perturbations for LVLM Hallucination Suppression
Hamidreza Dastmalchi, Aijun An, Ali Cheraghian +1
While large vision-language models (LVLMs) achieve strong performance on multimodal tasks, they frequently generate hallucinations -- unfaithful outputs misaligned with the visual…
HIME: Mitigating Object Hallucinations in LVLMs via Hallucination Insensitivity Model Editing
Ahmed Akl, Abdelwahed Khamis, Ali Cheraghian +3
Large Vision-Language Models (LVLMs) have demonstrated impressive multimodal understanding capabilities, yet they remain prone to object hallucination, where models describe non-ex…
Adapt-As-You-Walk Through the Clouds: Training-Free Online Test-Time Adaptation of 3D Vision-Language Foundation Models
Mehran Tamjidi, Hamidreza Dastmalchi, Mohammadreza Alimoradijazi +3
3D Vision-Language Foundation Models (VLFMs) have shown strong generalization and zero-shot recognition capabilities in open-world point cloud processing tasks. However, these mode…
ETTA: Efficient Test-Time Adaptation for Vision-Language Models through Dynamic Embedding Updates
Hamidreza Dastmalchi, Aijun An, Ali cheraghian
Pretrained vision-language models (VLMs) like CLIP show strong zero-shot performance but struggle with generalization under distribution shifts. Test-Time Adaptation (TTA) addresse…
MoKD: Multi-Task Optimization for Knowledge Distillation
Zeeshan Hayder, Ali Cheraghian, Lars Petersson +1
Compact models can be effectively trained through Knowledge Distillation (KD), a technique that transfers knowledge from larger, high-performing teacher models. Two key challenges…
Test-Time Adaptation of 3D Point Clouds via Denoising Diffusion Models
Hamidreza Dastmalchi, Aijun An, Ali Cheraghian +2
Test-time adaptation (TTA) of 3D point clouds is crucial for mitigating discrepancies between training and testing samples in real-world scenarios, particularly when handling corru…