Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

Kavli Affiliate: Wei Gao| Summary:Standard benchmarks evaluate time series foundation models (TSFMs) using aggregate metrics, but these can mask severe failures in critical operating regimes. We introduce regime-stratified evaluation and apply it to three TSFMs on two standard traffic speed benchmarks. Traffic exhibits abrupt regime switching between free-flow and congested states, producing bimodal speed distributions […]


Continue.. Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

Kavli Affiliate: Wei Gao| Summary:Standard benchmarks evaluate time series foundation models (TSFMs) using aggregate metrics, but these can mask severe failures in critical operating regimes. We introduce regime-stratified evaluation and apply it to three TSFMs on two standard traffic speed benchmarks. Traffic exhibits abrupt regime switching between free-flow and congested states, producing bimodal speed distributions […]


Continue.. Do Time Series Foundation Model Benchmarks Hide Regime-Dependent Failures? Evidence from Traffic Speed Forecasting

SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation

Kavli Affiliate: Wei Gao| Summary:Agentic kernel optimization automates manual GPU kernel tuning via iterative generation, validation, and profiling with reasoning LLMs, casting the optimization task as feedback-guided search. However, our workload characterization reveals three system-level inefficiencies that limit search efficiency: (1) long generation latency due to LLM reasoning, (2) insufficient profiling feedback, and (3) underutilized […]


Continue.. SpecGen: Accelerating Agentic Kernel Optimization with Speculative Generation

Characterization of ultrathin nickel films deposited by thermal laser evaporation

Kavli Affiliate: Austin Minnich | Summary:Thermal laser evaporation is a physical vapor deposition technique of increasing interest because of its ability to evaporate essentially any solid element, even the most refractory such as W. However, many films deposited by this method, especially non-epitaxial films, remain to be characterized; further, key system components such as the […]


Continue.. Characterization of ultrathin nickel films deposited by thermal laser evaporation

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Kavli Affiliate: Wei Gao| Summary:Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support systems may require human oversight, and audit workflows may inspect traces for misleading or biased input. In such settings, two responses can receive the same […]


Continue.. Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Kavli Affiliate: Wei Gao| Summary:Reasoning models are increasingly used in settings where the final answer is not the only object of review: educational tools may show students intermediate steps, decision-support systems may require human oversight, and audit workflows may inspect traces for misleading or biased input. In such settings, two responses can receive the same […]


Continue.. Beyond Accuracy: Measuring Bias Acknowledgment in Chain-of-Thought Reasoning for Responsible AI Evaluation

Data-driven surrogate models for forecasting experimentally measured fluid flows

Kavli Affiliate: Morteza Gharib| Summary:Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-evolution of experimentally measured cylinder wakes in the […]


Continue.. Data-driven surrogate models for forecasting experimentally measured fluid flows

Data-driven surrogate models for forecasting experimentally measured fluid flows

Kavli Affiliate: Morteza Gharib| Summary:Data-driven modeling shows significant promise for faster-than-real-time forecasting of fluid flows. For real-world engineering applications (e.g., flow control), models must contend with limited, imperfect, and incomplete experimental measurements. In this work, we present an analysis of data-driven surrogate models trained to forecast the time-evolution of experimentally measured cylinder wakes in the […]


Continue.. Data-driven surrogate models for forecasting experimentally measured fluid flows

Exploring Exoplanets with Interferometry

Kavli Affiliate: Dimitri Mawet| Summary:(Extract from the Executive Summary) Humanity stands at the threshold of answering one of its most profound questions: Does life exist beyond Earth? Ongoing and upcoming space missions, together with powerful ground-based instruments, have prepared the way for a transformational next step – the detailed characterization of Earth analogs orbiting Sun-like […]


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Dominant in-plane anomalous Hall effect in a monoclinic room-temperature ferromagnet

Kavli Affiliate: Linda Ye| Summary:Ferromagnetic metals are characterized by enhanced dissipationless transverse transport responses via the anomalous Hall effect, offering a route towards magnetic sensing and spintronic readout functionalities. In most ferromagnets, the anomalous Hall current is constrained to lie in the plane perpendicular to the magnetization (or applied magnetic field). Recently, it has been […]


Continue.. Dominant in-plane anomalous Hall effect in a monoclinic room-temperature ferromagnet