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This work introduces InteractBench, a benchmark comprising 322 high-quality interactive problems curated from Codeforces, AtCoder, IOI, and ICPC, and assesses whether model-generated code can acquire information and track state dynamically.
SmartRAG is presented, a fully on-device framework that organizes an intelligent assistant around four coordinated modules -- Perception, Memory, Focus, and Thinking -- keeping inference costs bounded and at the core of EvoNER, a continually learnable named-entity recognizer that incrementally expands its label inventory through teacher-distilled updates.
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