Maps differentiable logic-gate networks to CMOS silicon via netlist conversion and area-minimizing loss, with first simulated 130nm hard-macro achieving 97% MNIST accuracy at 41.8M inferences/sec and 83.88mW.
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StruMPL is a multi-task dense regression model that jointly addresses disjoint partial supervision, MNAR labels, and inter-task physical constraints for improved forest biomass estimation from Earth observation.
Memory-equipped LLM agents exhibit increasing safety violation rates as memory accumulates across independent tasks, termed temporal memory contamination, detected via a new trigger-probe protocol.
CosmoPostProcess delivers simulation-calibrated radial corrections for projection-induced selection bias (20-40% amplitude near 1 h^{-1} Mpc) and baryonic effects in Euclid richness-selected cluster weak lensing profiles.
Multi-phase observations of NGC 1427A indicate tidal torquing from a dwarf fly-by has pre-conditioned its gas for ram-pressure stripping by the Fornax intracluster medium, placing the galaxy at the onset of environmental quenching with a declining star formation rate.
A framework integrates synthetic population generation from ACS PUMS, deep contrastive learning for housing-household compatibility, and hierarchical optimization to produce a joint inventory that matches block-group demographics and spatial patterns in coastal North Carolina.
The paper delivers a unified executable benchmarking suite for tool-using agents that enforces a shared evidence-admission contract across web, code, and micro-task environments.
citing papers explorer
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Silicon Aware Neural Networks
Maps differentiable logic-gate networks to CMOS silicon via netlist conversion and area-minimizing loss, with first simulated 130nm hard-macro achieving 97% MNIST accuracy at 41.8M inferences/sec and 83.88mW.
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StruMPL: Multi-task Dense Regression under Disjoint Partial Supervision and MNAR Labels
StruMPL is a multi-task dense regression model that jointly addresses disjoint partial supervision, MNAR labels, and inter-task physical constraints for improved forest biomass estimation from Earth observation.
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Remembering More, Risking More: Longitudinal Safety Risks in Memory-Equipped LLM Agents
Memory-equipped LLM agents exhibit increasing safety violation rates as memory accumulates across independent tasks, termed temporal memory contamination, detected via a new trigger-probe protocol.
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Euclid preparation. CosmoPostProcess: A simulation calibrated framework for weak lensing selection bias in richness-selected galaxy clusters
CosmoPostProcess delivers simulation-calibrated radial corrections for projection-induced selection bias (20-40% amplitude near 1 h^{-1} Mpc) and baryonic effects in Euclid richness-selected cluster weak lensing profiles.
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Tidal pre-conditioning and ram-pressure stripping in NGC 1427A. Deep VLT/MUSE spectroscopy and FUV-to-radio observations trace a Fornax Cluster dwarf in transformation
Multi-phase observations of NGC 1427A indicate tidal torquing from a dwarf fly-by has pre-conditioned its gas for ram-pressure stripping by the Fornax intracluster medium, placing the galaxy at the onset of environmental quenching with a declining star formation rate.
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A Joint Synthetic Housing-Household Inventory
A framework integrates synthetic population generation from ACS PUMS, deep contrastive learning for housing-household compatibility, and hierarchical optimization to produce a joint inventory that matches block-group demographics and spatial patterns in coastal North Carolina.
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An Executable Benchmarking Suite for Tool-Using Agents
The paper delivers a unified executable benchmarking suite for tool-using agents that enforces a shared evidence-admission contract across web, code, and micro-task environments.
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