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RF monitoring stacks must compress and interpret highrate spectra under tight latency and power budgets. We targetthe common case where the front-end produces windowedFFT power spectra (magnitude-only) and the back-end must(1) compress to a compact… Flash-Attention MHLA for RF SpectrumCompression: SpectrumEncoder with Token-Dropout and RoPEAblations
Overall Impression Your paper presents an intriguing and timely application of reinforcement learning (RL) to MIMO beam steering for non-invasive neuromodulation, emphasizing real-time adaptation and safety constraints. The camera-in-the-loop approach is a novel hook that… Neural MIMO Beam Steering for Non-Invasive Neuromodulation
Exhaustive parameter sweeps are the de facto method for benchmarking RF pipelines, butthey scale poorly with dimensionality[2]. For example, a 10-parameter grid with 10 points eachrequires 1010 evaluations. Active learning promises to achieve comparable confidence… Active Learning for Synthetic RF Benches: From Random Grids to Agentic Sweeps
There’s nothing quite like NotebookLM out there today. Nothing worth your time, at least. Here’s what it can do for you. Blake Stimac – Aug. 13, 2025 10:56 a.m. PT
🔍 MyGlass APK Analysis – Key Findings Critical Discovery: Glass Pairing Protocol Elements From examining the original MyGlass APK structure, I found several crucial components that explain why the Glass 700C is stuck on “Install MyGlass”: 1. Glass-Specific… Glass Pairing Protocol
