Author

Amir Salarpour

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Preprint Oct 2026

Lang3DSeg: Annotation-Free Open-Vocabulary 3D Segmentation with Point Transformers

Accurate 3D semantic perception is critical for safe autonomous navigation. However, supervised LiDAR segmentation remains tied to closed taxonomies and to the cost of point-wise manual annotation. Open-vocabulary methods avoid that cost by projecting the output of 2D vision-language models onto LiDAR and distilling it...

Cigdem Kokenoz, Amir Salarpour, Alkim Domeke et al. · 0 citations

Preprint Aug 2026

GATE: Reliability-Gated Gaussian Evidence Fusion for Training-Free Test-Time Adaptation of Vision-Language Models

GATE is introduced, a training-free two-pass transductive test-time adaptation framework that uses the unlabeled target set while keeping the image encoder, text encoder, and prompt parameters fully frozen, and demonstrates the benefit of reliability-gated distributional evidence for frozen VLM adaptation.

Pedram MohajerAnsari, Amir Salarpour, Run-Min Wang et al. · 0 citations

Jul 2026

Adversarial Prompts for Acceptance Collapse in Speculative Decoding

ADSD is introduced, which is the first prompt-suffix attack that collapses verifier acceptance by pushing draft probability mass toward tokens the target is unlikely to accept, and successfully generates highly effective adversarial suffixes.

Run-Min Wang, Chaoyi Zhou, Xi Liu et al. · arXiv.org · 0 citations

Preprint Aug 2026

Distilling Vision-Language Models for Robust Traffic Sign Perception in Autonomous Vehicles

Evaluated on GTSRB and LISA across four backbones and three physical attack types, LAMDA is the only method among ten evaluated that consistently improves robustness across all attack-backbone-dataset combinations, while preserving or improving clean accuracy in nearly all cases.

Pedram MohajerAnsari, Amir Salarpour, M. Pesé · 0 citations