๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Utkarsh Mishra
@utkarshm0410
Intern@Nvidia SRL, Robotics PhD Student @GeorgiaTech || Prev. intern at Amazon FAR, TRI|| Robot Learning || IITR'21 || ๐ŸŽธ๐ŸŽข๐Ÿค–|| He/Him || views are mine.
๊ฐ€์ž… July 2015
731 ํŒ”๋กœ์ž‰ ์ค‘    629 ํŒฌ
WAMs are popular because of their promise of better generalization. Is that true? We started playing with Video-Action-Model (VAMs) and realized a gap: video model backbones can compositionally generalize but VAMs often do not. We coin this the Video-Action-Generalization (VAG) gap and present a study on how to explain and improve it. More details: ๐Ÿงต below
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