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SpinQuant: LLM quantization with learned rotations
In this work, we identify a collection of applicable rotation parameterizations that lead to identical outputs in full-precision Transformer architectures, and find that some random rotations lead to much better quantization than others, with an up to 13 points difference in downstream zero-shot reasoning performance.
SqueezeSAM: User friendly mobile interactive segmentation
A common user expectation is that a click on a specific part of an object will result in the segmentation of the entire object.
Generating Notifications for Missing Actions: Don't Forget to Turn the Lights Off!
The overall prediction accuracy is 46. 2% when only 10 frames of an action are seen (2/3 of a sec).
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