Author

Shahram Najam Syed

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#machine learning Preprint Sep 2026

Not All Layers Need Tuning: Diagnosing and Directing Adaptation in Vision-Language-Action Models

Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to every network region as if every region requires equal adjustment. This paper tests that assumption on five architecturally diverse VLAs (OpenVLA-OFT, $\pi_0$, SmolVLA, DTP...

Shahram Najam Syed, Arthur Jakobsson, Prayuj Sachdev et al. · 0 citations

#artificial intelligence Apr 2026

Wiggle and Go! System Identification for Zero-Shot Dynamic Rope Manipulation

This work introduces Wiggle and Go!, a two-stage framework for zero-shot rope manipulation: a brief, safe wiggle action is observed to predict descriptive rope parameters, which then conditions a trajectory optimizer for zero-shot goal-conditioned execution.

Arthur Jakobsson, Abhinav Mahajan, Karthik Pullalarevu et al. · arXiv.org · 1 citation · ⚡1

Preprint Aug 2026

Hierarchical Skill Retrieval for Data-Efficient Adaptation of Vision-Language-Action Models

While Vision-Language-Action (VLA) models pretrained on large-scale robot datasets provide a strong foundation for robot manipulation, their performance can degrade when adapted to new tasks with limited task-specific demonstrations. Retrieval offers a practical way to reuse existing demonstrations for data-efficient a...

Haoran Hao, Shahram Najam Syed, Jeff G. Schneider et al. · 0 citations