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.CV2026

ScAle: Attention Head Scaling as a Minimal Adapter for Spatial Reasoning in Vision Language Models

Rahul Chowdhury, Timothy A Rupprecht, Xuan Shen +2

Spatial reasoning remains a persistent challenge for many vision language models (VLMs), and improving it typically requires fine-tuning with substantial additional parameters. Our…

cs.CV2026

PhyGround: Benchmarking Physical Reasoning in Generative World Models

Juyi Lin, Arash Akbari, Yumei He +13

Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…

cs.LG2026

CUDAHercules: Benchmarking Hardware-Aware Expert-level CUDA Optimization for LLMs

Shiyang Li, Zijian Zhang, Guangyan Sun +5

Large language models show promise for automated CUDA programming, however even the strongest coding models (e.g., Claude-Opus-4.6) may still fall short of expert-level, architectu…

cs.LG2026

Effective MoE-based LLM Compression by Exploiting Heterogeneous Inter-Group Experts Routing Frequency and Information Density

Zhendong Mi, Yixiao Chen, Pu Zhao +4

Mixture-of-Experts (MoE) based Large Language Models (LLMs) have achieved superior performance, yet the massive memory overhead caused by storing multiple expert networks severely…

cs.CL2026

Open-Source Multimodal Moxin Models with Moxin-VLM and Moxin-VLA

Pu Zhao, Arash Akbari, Xuan Shen +16

Recently, Large Language Models (LLMs) have undergone a significant transformation, marked by a rapid rise in both their popularity and capabilities. Leading this evolution are pro…