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Found 4 papers, 1 papers with code
AdaPTwin: Low-Cost Adaptive Compression of Product Twins in Transformers
While large transformer-based models have exhibited remarkable performance in speaker-independent speech recognition, their large size and computational requirements make them expensive or impractical to use in resource-constrained settings.
HomE: Homography-Equivariant Video Representation Learning
In this work, we propose a novel method for representation learning of multi-view videos, where we explicitly model the representation space to maintain Homography Equivariance (HomE).
Joint Transformer/RNN Architecture for Gesture Typing in Indic Languages
Gesture typing is a method of typing words on a touch-based keyboard by creating a continuous trace passing through the relevant keys.
Input-specific Attention Subnetworks for Adversarial Detection
We also demonstrate that our method (a) is more accurate for larger models which are likely to have more spurious correlations and thus vulnerable to adversarial attack, and (b) performs well even with modest training sets of adversarial examples.
