What Is AI Optimization & Learning Efficiency? A Complete Guide Imagine training a student to solve complex problems. You could give them thousands of practice problems, or you could teach them core principles that let them solve new problems with far fewer examples. Modern artificial intelligence faces the same choice, and the stakes are enormous. … Read more
arXiv:2606.09607v1 Announce Type: cross
Abstract: Interpretability increasingly treats groups of components, not individual units, as the basic object, and proposes to find them by clustering…
arXiv:2606.09012v1 Announce Type: cross
Abstract: Post-training quantization (PTQ) converts a trained full-precision model into low-bit weights without task-level retraining, while…
arXiv:2606.09236v1 Announce Type: cross
Abstract: Autonomous Racing has seen remarkable progress through deep Reinforcement Learning (RL), primarily for four-wheeled vehicles. However, motorbikes…
arXiv:2509.12760v5 Announce Type: replace
Abstract: We introduce the Similarity-Distance-Magnitude (SDM) activation function, a more robust and interpretable formulation of the standard softmax…
arXiv:2606.09547v1 Announce Type: cross
Abstract: Learning everyday skills, like cooking a dish, relies increasingly on instructional media such as online videos. This opens the door to the use of…
arXiv:2410.05662v4 Announce Type: replace
Abstract: Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or…
Imagine a doctor’s AI diagnostic tool recommends surgery, but neither the doctor nor the AI can explain why. This scenario highlights a critical challenge in modern artificial intelligence: we’ve built powerful systems that work remarkably well, but often we have no idea how they reach their conclusions. AI interpretability and explainability are the fields dedicated … Read more
arXiv:2603.04982v3 Announce Type: replace-cross
Abstract: Can targeted user training unlock the productive potential of generative artificial intelligence in professional settings? We study this…
arXiv:2509.17446v3 Announce Type: replace-cross
Abstract: Multimodal intent recognition (MMIR) suffers from weak semantic grounding and poor robustness under noisy or rare-class conditions. We…