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LLMs are counterintuitively worse at spotting nonsensical errors than plausible lies, and their ability to reject factual distortions collapses by up to 49% in East Asian languages despite showing parity on standard benchmarks.
By routing image patches to specialized LoRA experts, MoECLIP achieves state-of-the-art zero-shot anomaly detection, demonstrating the power of patch-level adaptation.