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Visually plausible charts generated by LLMs often mask significant data-level hallucinations, revealing a critical gap in current AI capabilities.
AsymSpec achieves 90% accuracy with 1.7x speedups by leveraging asymmetric context access, redefining efficiency in agentic LLMs.
SITA achieves target-aware compression that outperforms traditional methods, striking a balance between efficiency and specificity in long-sequence recommendations.
