الباحثون

Jasper Gerigk

المنشورات 2

نسخة أولية وصول مفتوح

When Listening Becomes Easier: Scrubbing Visual Cues for Shortcut-Free VLAs

Shortcut learning is a prevalent issue in robot learning. The limited diversity of robot demonstration datasets can mislead policies into exploiting spurious correlations between tasks and irrelevant features, such as viewpoint or background. Collecting sufficiently diverse robot demonstrations is costly and inefficien …

نسخة أولية وصول مفتوح

SCOPD: Sparse-Context On-Policy Self-Distillation for Efficient Vision-Language Models

Ahmadreza Jeddi, Enming Zhang, Jasper Gerigk وآخرون · 2026

Reasoning vision-language models (VLMs) process images and videos as long sequences of visual tokens, making inference expensive. Training-free token pruning reduces this cost, but aggressive compression can sharply degrade performance, often attributed to irreversible loss of task-relevant visual information. We show …

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