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Measuring AI by how much faster developers work is like judging electricity by how much faster it spun a steam-era factory. A fuller measure asks what new work becomes possible. We surveyed 331 software developers at Mic...
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Optimizing product listings for generative search requires language agents not only to rewrite effectively but also to continually self-improve by retaining successful strategies across diverse categories. However, exist...
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This paper presents a novel multiclass first order macroscopic traffic model for mixed-autonomy in signalized urban networks, called MIXSim. Human driven vehicles (HDVs) and Connected and Automated Vehicles (CAVs) are re...
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Although linguistic differences between human-written and Large Language Model (LLM)-generated texts have been extensively studied, their implications for the cognitive effort involved in reading remain less explored. In...
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Deep neural networks demonstrate remarkable generalization despite being highly over-parameterized, challenging traditional statistical learning theories. While several theoretical paradigms such as margin-based bounds, ...
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The electronic self-energy determines the single-particle Green's function and, through it, quasiparticle energies and spectral functions, but computing it from first principles is expensive and it is a difficult machine...
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Publication count is not study count. A model can identify shared trial lineage correctly in a direct task yet over-credit a second publication from the same trial when aggregating evidence. We evaluate this behavior in ...
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Understanding and simulating how subjective cognition and mental states emerge, evolve, and shape behavior is essential for advancing artificial intelligence toward deeper social cognition and general intelligence. Exist...
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The design space of modern AI/HPC systems has expanded rapidly across compute architectures, including GPUs, dataflow processors, and RISC-V accelerators; memory tech- nologies, including HBM, GDDR, and SRAM; and interco...
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AI agents are growing more capable and persistent, and are being deployed in ever larger numbers. As more start collaborating, AI control measures must remain effective when they covertly collude on a harmful objective. ...
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Data Petri nets are an extension of plain Petri nets where, intuitively speaking, tokens carry data values, and transitions may perform equality tests on data values involved. Likewise, data vector addition systems with ...
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Conventional sleep staging provides a coarse-grained representation that obscures within-stage depth variation. We developed ECG-SDI, a single-lead electrocardiography (ECG) framework for continuous sleep-depth profiling...
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We derive a tight generalization bound for deterministic neural We derive a tight generalization bound for deterministic neural networks based on their last hidden layer representations. By evaluating representation qual...
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Recent deep facial phenotyping methods can support the recognition of genetic syndromes, but patient images are often scarce and unevenly distributed across disorders. Synthetic facial images offer a way to supplement th...
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Perceived gender inference from names is important for inclusive scientometrics research, yet existing methods perform poorly on non-Western scholars. We address this gap for Chinese names, which appear in two forms, Han...