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Robust-TO addresses the Blind Trust Problem in video reasoning by integrating per-frame trustworthiness into an agentic framework, improving accuracy under realistic perturbations through calibrated evidence weighting and reliability-aware reasoning.
CONF-KV is a KV-cache management system that uses model uncertainty to dynamically adjust cache retention, improving memory efficiency for long-context LLM inference while maintaining accuracy within 1.5-2.1 perplexity points.