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Causal attention in Post-Norm Transformers amplifies token similarity, leading to a collapse that training dynamics fail to repair, revealing critical insights into model behavior.
By integrating received signal strength with traditional bearing measurements, this method eliminates the need for lateral sensor motion, revolutionizing motion estimation for energy emitters.
OrthoPilot outperformed seasoned orthopaedic experts in diagnostic reasoning, achieving a 10.6% increase in management success for complex musculoskeletal cases.
Faithful supervision through a novel warm-start strategy boosts VLM accuracy and stabilizes training by grounding responses in visual evidence.
Weight regularization, often overlooked in parameter-efficient continual learning, can still significantly improve the stability-plasticity trade-off, even when using low-rank adapters.
