الباحثون

Mohsen Hariri

المنشورات 2

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Correcting WHERE, Preserving HOW: Compositional Generalization for Vision-Language-Action Models via Referential Guidance

Yanyan Zhang, Disheng Liu, Xinpeng Li وآخرون · 2026

While Vision-Language-Action (VLA) models enable flexible action generation, their generalization across diverse environmental elements, including manipulated objects, destinations, and backgrounds, is limited by the lack of diversity in robotic training data. Trained end-to-end on such data, VLAs tend to exploit visua …

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How to Loop MoE: Flatten the Experts, Untie the Attention

Shouren Wang, Chuang Ma, Mohsen Hariri وآخرون · 2026

Looped Transformers reuse one block of layers several times: by spending extra computation they push a model of fixed size further, and so use its parameters more fully; while sparse mixture-of-experts (MoE) models activate only a few of many experts for each token. Looped MoE bridges these two design philosophies and …

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