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cs.LG2025
Revisiting the Learning Objectives of Vision-Language Reward Models
Simon Roy, Samuel Barbeau, Giovanni Beltrame +2
Learning generalizable reward functions is a core challenge in embodied intelligence. Recent work leverages contrastive vision language models (VLMs) to obtain dense, domain-agnost…
cs.CL2025
BitMar: Low-Bit Multimodal Fusion with Episodic Memory for Edge Devices
Euhid Aman, Esteban Carlin, Hsing-Kuo Pao +3
Cross-attention transformers and other multimodal vision-language models excel at grounding and generation; however, their extensive, full-precision backbones make it challenging t…