collaborators

11 papers

cs.CV2026

VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting

Juyi Lin, Amir Taherin, Arash Akbari +11

Recent large-scale Vision Language Action (VLA) models have shown superior performance in robotic manipulation tasks guided by natural language. However, current VLA models suffer…

cs.RO2026

Human Cognition in Machines: A Unified Perspective of World Models

Timothy Rupprecht, Pu Zhao, Amir Taherin +20

This report of world models distinguishes prior works by the cognitive functions they innovate. Many works claim an almost human-like cognitive capability in their world models. To…

cs.CV2026

ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models

Arash Akbari, Arman Akbari, Masih Eskandar +11

Vision-Language-Action (VLA) models exhibit remarkable action generation for embodied intelligence, but their heavy compute make deployment on edge platforms impractical. Aggressiv…

cs.LG2026

Flash-WAM: Modality-Aware Distillation for World Action Models

Arman Akbari, Ci Zhang, Arash Akbari +6

World-action models (WAMs) jointly generate future video and robot actions through iterative diffusion, achieving strong performance on manipulation benchmarks but requiring tens o…

cs.AI2026

Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs

Qitao Tan, Xiaoying Song, Arman Akbari +7

Current safety alignment of foundation models largely follows a \emph{one-size-fits-all} paradigm, applying the same refusal policy across users and contexts. As a result, models m…

cs.CV2026

PhyWorld: Physics-Faithful World Model for Video Generation

Pu Zhao, Juyi Lin, Timothy Rupprecht +10

World simulators can provide safe and scalable environments for training Physical AI systems before real-world deployment. Large video generation models are emerging as a promising…