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The results show that sharing observations across objectives and ignoring irrelevant objective-wise distinctions can substantially reduce the sampling cost, as confirmed by experiments on synthetic and real-world tasks.
This paper proposes Whiteboard, the first LLM imagination evaluation benchmark, and investigates whether imagination derives from the same generative tendency as hallucination and what key factors shape it.
Across diverse benchmarks and world-model families, BasinLens exposes reproducible and locally persistent failure modes that conventional evaluations fail to reveal, showing that average-case benchmarks can mask important vulnerabilities in world-model-driven control.
Control Memory Interference is introduced, a controlled diagnostic and data-generation framework for studying how agent memory evolves under different memory relationships and shows that memory evolution is shaped not only by memory scale, but also by interactions among accumulated experiences.
Deep-OCR (DeepSeek-OCR) advances document recognition by treating the visual modality as an optical compression medium, enabling long-context OCR at low token cost. However, its increased complexity may introduce new security vulnerabilities. In this paper, we present, to the best of our knowledge, the first pure black...
The Emergent Modular Atomic Network (EMAN), an optimization-driven framework for exposing an antisymmetric growth direction through latent relative phases without instantiating a second path, and for monitoring multiple decision signals during training to transform local optimization evidence into a structural decision...
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