activity
20242026
collaborators

6 papers

cs.CV2026

Test-Time Hallucination Control in Large Vision-Language Models

Mehran Tamjidi, Hamidreza Dastmalchi, Ali Cheraghian +3

Object Hallucination in large vision-language models (LVLMs), where models generate non-factual content about input images, remains a critical barrier to their reliability in real-…

cs.CV2026

SteerSeg: Attention Steering for Reasoning Video Segmentation

Ali Cheraghian, Hamidreza Dastmalchi, Abdelwahed Khamis +3

Video reasoning segmentation requires localizing objects across video frames from natural language expressions, often involving spatial reasoning and implicit references. Recent ap…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…