Massive activations are constant large values in LLMs that function as indispensable bias terms and concentrate attention probabilities on specific tokens.
Outlier-efficient hopfield layers for large transformer-based models
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APRTrack applies hierarchical adversarial perturbations at modality and spatial levels plus footprint-calibrated Hopfield retrieval to improve robustness of RGB-Event tracking under occlusion and modal failure.
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Massive Activations in Large Language Models
Massive activations are constant large values in LLMs that function as indispensable bias terms and concentrate attention probabilities on specific tokens.
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Active Adversarial Perturbation-driven Associative Memory Retrieval for RGB-Event Visual Object Tracking
APRTrack applies hierarchical adversarial perturbations at modality and spatial levels plus footprint-calibrated Hopfield retrieval to improve robustness of RGB-Event tracking under occlusion and modal failure.