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This paper reproduces the reported gains of the Neural Thickets hypothesis, which claims pretrained language models sit in dense neighborhoods of task-specific experts in weight space, but shows the improvements do not r...
The paper proposes treating retrieval as a persistent local traversal through an address space, separating memory content from its address. It introduces a cost-regularised indexing objective that preserves information v...
Researchers introduce MetaRefine, a lightweight architecture that refines existing image assessment scores using original-image geometry, multi-level visual features, and the frozen model's score. Across 100 configu...
The paper presents IMPACT, a physics-informed multimodal deep learning framework for 10- to 110-minute-ahead probabilistic photovoltaic power forecasting. Its four-branch architecture combines plant-level temporal histor...
Researchers introduced EPC-RawDC, a conditional 3D latent diffusion framework for CBCT-to-CT image synthesis that incorporates scanner-specific acquisition physics rather than relying on image data alone. The method comb...
This paper introduces Assur-KB, a representation for planar mechanisms that exposes reusable constraint subassemblies, and shows it improves prediction from limited data. Theoretical results characterize transfer through...
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