A Faster Pytorch Implementation of Multi-Head Self-Attention
Official PyTorch Implementation of 'Entropy-Guided Attention for Private LLMs' (PPAI Workshop. AAAI 2025)
[IROS 2024] Language-driven Grasp Detection with Mask-guided Attention
CLI toolkit that ingests qk-sniffer dumps, measures per-head positional predictability and attention plasticity, and exports CSV stats plus ready-to-share plots.
This work proposes STAC, a novel framework for weakly supervised defect localization that leverages saliency-guided transformer attention and pixel-level contrastive learning to achieve precise defect maps using only image-level labels.
Train your attention like a transformer trains its weights. Selective, sustained & N-back exercises grounded in the Q/K/V attention framework.
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