A Uniform Determination of the Bulk Metallicities and Alpha Enrichments of Confirmed Exoplanet Systems with TRES

Posted by klaurent Harvard

Kavli Affiliate: David Charbonneau | Summary:We present a uniform spectroscopic characterization of 625 F, G, and K stars hosting 859 confirmed exoplanets using high-resolution archival optical spectra from the Tillinghast Reflector Echelle Spectrograph (TRES). We use the neural network spectral code uberMS, which combines spectra with broadband photometry to estimate precise and accurate stellar parameters. […]


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Uncovering and Shaping the Latent Representation of 3D Scene Topology in Vision-Language Models

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Decades of cognitive science establish that humans navigate environments by forming cognitive maps, defined as allocentric and topology-preserving representations of 3D space. While modern Vision-Language Models (VLMs) demonstrate emergent spatial reasoning from 2D egocentric inputs, it remains unclear whether they construct an analogous 3D internal representation. In this paper, we demonstrate […]


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Colossal Magnetoresistance and Phonon Driven Exchange Dynamics in Eu$_5$Sn$_2$As$_6$

Posted by klaurent Berkeley

Kavli Affiliate: Joel Moore | Summary:The emergence of colossal magnetoresistance in a new generation of Eu$^2+$-based antiferromagnets is intriguing given stark contrasts to the archetypal perovskite manganites and doped Eu-chalcogenides. In this study the thermal conductivity and magnetostriction of Eu$_5$Sn$_2$As$_6$ — one such representative — have been measured to better understand the role of the […]


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Electrically controlled Heat Assisted Magnetic Recording in Intercalated 2D Magnets

Posted by klaurent Berkeley

Kavli Affiliate: James Analytis| Summary:The ever-increasing demand for fast, reliable, and energy-efficient information storage continues to push magnetic memory technologies toward their fundamental limits. Conventional scaling strategies, which rely on reducing bit size, inevitably run into the "magnetic recording trilemma," where signal-to-noise ratio, thermal stability, and writability cannot all be optimized simultaneously. Heat-assisted magnetic recording […]


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ReActor: Reinforcement Learning for Physics-Aware Motion Retargeting

Posted by klaurent Cornell

Kavli Affiliate: David Muller | Summary:Retargeting human kinematic reference motion onto a robot’s morphology remains a formidable challenge. Existing methods often produce physical inconsistencies, such as foot sliding, self-collisions, or dynamically infeasible motions, which hinder downstream imitation learning. We propose a bilevel optimization framework that jointly adapts reference motions to a robot’s morphology while training […]


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ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Agentic reinforcement learning (RL) has emerged as a key driver for improving the multi-step reasoning and tool-use capabilities of LLMs. However, its efficiency is bottlenecked by long-tail rollouts with multi-turn environment interactions, making static GPU provisioning a poor fit: overprovisioning wastes GPUs on stragglers, while underprovisioning increases contention and slows training. […]


Continue.. ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL

ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Agentic reinforcement learning (RL) is reshaping LLM post-training, but end-to-end training time is dominated by compute-intensive, multi-turn rollouts whose resource demand varies significantly across training steps. Resource-fixed systems cannot adapt to this variation, while resource-elastic approaches that provision external GPUs on demand suffer from high allocation overhead and limited availability. We […]


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Pair-Breaking and Dimensionality in Spin-Orbit Coupled Superconductors

Posted by klaurent Caltech

Kavli Affiliate: Joseph Falson | Summary:The response of ultra-thin superconducting materials under parallel magnetic fields is often leveraged to obtain insight into the nature of the condensate, including features attributable to unconventional forms of pairing. Despite there being multiple competing mechanisms responsible for suppressing superconductivity, it is common for these analyses to overlook certain depairing […]


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ResiHP: Taming LLM Training Failures with Dynamic Hybrid

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Hybrid parallelism underpins large-scale LLM training across tens of thousands of GPUs. At such scale, hardware failures on individual devices lead to performance skew across devices, diminishing overall training efficiency. Existing resilient systems overlook sequence length variability in datasets and device performance skew under hybrid parallelism. As a result, (1) iteration […]


Continue.. ResiHP: Taming LLM Training Failures with Dynamic Hybrid

ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism

Posted by klaurent Caltech

Kavli Affiliate: Wei Gao| Summary:Hybrid parallelism underpins large-scale LLM training across tens of thousands of GPUs. At such scale, hardware failures on individual devices lead to performance skew across devices, diminishing overall training efficiency. Existing resilient systems overlook sequence length variability in datasets and device performance skew under hybrid parallelism. As a result, (1) iteration […]


Continue.. ResiHP: Taming LLM Training Failures with Dynamic Hybrid Parallelism