First Measurement of $π^+$-Ar and $p$-Ar Total Inelastic Cross Sections in the Sub-GeV Energy Regime with ProtoDUNE-SP Data

Posted by klaurent MIT

Kavli Affiliate: David Shoemaker| First 5 Authors: DUNE Collaboration, DUNE Collaboration, , , | Summary:The ProtoDUNE-SP detector, a kiloton-scale prototype for the Deep Underground Neutrino Experiment (DUNE), is the largest liquid argon time projection chamber built to date. Operated at CERN from 2018 to 2020, it collected both cosmic-ray data and a beam consisting of […]


Continue.. First Measurement of $π^+$-Ar and $p$-Ar Total Inelastic Cross Sections in the Sub-GeV Energy Regime with ProtoDUNE-SP Data

KVSwap: Disk-aware KV Cache Offloading for Long-Context On-device Inference

Posted by klaurent Peking

Kavli Affiliate: Huawei Zhang | Summary:Language models (LMs) underpin emerging mobile and embedded AI applications like meeting and video summarization and document analysis, which often require processing multiple long-context inputs. Running an LM locally on-device improves privacy, enables offline use, and reduces cost, but long-context inference quickly hits a emphmemory capacity wall as the key-value […]


Continue.. KVSwap: Disk-aware KV Cache Offloading for Long-Context On-device Inference

KVSwap: Disk-aware KV Cache Offloading for Long-Context On-device Inference

Posted by klaurent Peking

Kavli Affiliate: Huawei Zhang| First 5 Authors: Huawei Zhang, Huawei Zhang, , , | Summary:Language models (LMs) underpin emerging mobile and embedded AI applications like meeting and video summarization and document analysis, which often require processing multiple long-context inputs. Running an LM locally on-device improves privacy, enables offline use, and reduces cost, but long-context inference […]


Continue.. KVSwap: Disk-aware KV Cache Offloading for Long-Context On-device Inference

Measurement of reactor antineutrino oscillations with 1.46 ktonne-years of data at SNO+

Posted by klaurent Caltech

Kavli Affiliate: N. C. Yeh| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:The SNO+ Collaboration reports new results on reactor antineutrino oscillations using data acquired from May 2022 through July 2025. The spectral analysis of a flux dominated by nuclear reactors at 240, 350, and 355 kilometers yields the mass-squared difference $Δm^2_21=(7.93^+0.21_-0.24)times 10^-5$ eV$^2$. […]


Continue.. Measurement of reactor antineutrino oscillations with 1.46 ktonne-years of data at SNO+

Effective Hamiltonians for Ge/Si core/shell nanowires from higher order perturbation theory

Posted by klaurent Delft

Kavli Affiliate: Michael Wimmer | Summary:We theoretically explore the electronic structure of holes in cylindrical Germanium/Silicon core/shell nanowires using a perturbation theory approach. The approach yields a set of interpretable and transferable effective low-energy models for the lowest few sub-bands up to fifth order for experimentally relevant growth directions. In particular, we are able to […]


Continue.. Effective Hamiltonians for Ge/Si core/shell nanowires from higher order perturbation theory

Human-AI collaborative autonomous synthesis with pulsed laser deposition for remote epitaxy

Posted by klaurent Cornell

Kavli Affiliate: Daniel C. Ralph| First 5 Authors: Asraful Haque, Asraful Haque, , , | Summary:Autonomous laboratories typically rely on data-driven decision-making, occasionally with human-in-the-loop oversight to inject domain expertise. Fully leveraging AI agents, however, requires tightly coupled, collaborative workflows spanning hypothesis generation, experimental planning, execution, and interpretation. To address this, we develop and deploy […]


Continue.. Human-AI collaborative autonomous synthesis with pulsed laser deposition for remote epitaxy

CountSteer: Steering Attention for Object Counting in Diffusion Models

Posted by klaurent Stanford

Kavli Affiliate: Hsiao-Mei (Sherry) Cho| First 5 Authors: [#item_custom_name[1, [#item_custom_name[2, [#item_custom_name[3, [#item_custom_name[4, [#item_custom_name[5| Summary:Text-to-image diffusion models generate realistic and coherent images but often fail to follow numerical instructions in text, revealing a gap between language and visual representation. Interestingly, we found that these models are not entirely blind to numbers-they are implicitly aware of their […]


Continue.. CountSteer: Steering Attention for Object Counting in Diffusion Models