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Doubling photocathode coverage with cost-effective MCP-PMTs cuts underground muon direction reconstruction error to just 6掳 while boosting detection efficiency by 59%, successfully isolating CJPL's first up-going neutrino-induced event.
A leading-order effective field links empirical dynamics to neural computation, revealing how human-AI interactions exhibit reproducible and interpretable patterns.
SIMAX reveals that AI-generated clinical dialogues can achieve high realism and fidelity, paving the way for scalable communication coding solutions in healthcare.
LLMs can denoise sequential recommendations by disagreeing with the recommendation model itself, leading to more robust performance against noisy user data.
By disentangling shared account behavior in the frequency domain, DisenReason dynamically infers latent users, boosting recommendation accuracy by up to 12.56% compared to methods assuming a fixed number of users.
