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YouZhi-LLM achieves unprecedented concurrency and accuracy in financial LLMs by dramatically reducing KV-cache overhead, setting a new standard for deployment efficiency.
AI-generated images betray themselves with a subtle "spectral tail uplift" in their frequency spectrum, offering a surprisingly robust cue for detection.
State-of-the-art shot boundary detection gets a major upgrade with a Transformer-based approach that not only improves accuracy but also offers more interpretable boundaries, thanks to a novel relational prediction framework and synthetic training data.
Learning robotic reward functions from a million trajectories reveals that comparing entire trajectories, not just individual frames, unlocks better generalization and learning from suboptimal data.
