Kavli Affiliate: Jie Shan | First 5 Authors: Shuyin Ouyang, Shuyin Ouyang, , , | Summary: We introduce DSCodeBench, a new benchmark designed to evaluate large language models (LLMs) on complicated and realistic data science code generation tasks. DSCodeBench consists of 1,000 carefully constructed problems sourced from realistic problems from GitHub across ten widely used […]
Kavli Affiliate: Chris Xu | First 5 Authors: Ben Cohen, Ben Cohen, , , | Summary: We introduce Toto, a time series forecasting foundation model with 151 million parameters. Toto uses a modern decoder-only architecture coupled with architectural innovations designed to account for specific challenges found in multivariate observability time series data. Toto’s pre-training corpus […]
Kavli Affiliate: Zhiting Tian | First 5 Authors: Hanlin Zhu, Hanlin Zhu, , , | Summary: Large Language Models (LLMs) have demonstrated remarkable performance in many applications, including challenging reasoning problems via chain-of-thoughts (CoTs) techniques that generate “thinking tokens” before answering the questions. While existing theoretical works demonstrate that CoTs with discrete tokens boost the […]
Kavli Affiliate: Zhiting Tian | First 5 Authors: Jeffrey Alido, Jeffrey Alido, , , | Summary: Conventional score-based diffusion models (DMs) may struggle with anisotropic Gaussian diffusion processes due to the required inversion of covariance matrices in the denoising score matching training objective citevincent_connection_2011. We propose Whitened Score (WS) diffusion models, a novel framework based […]
Kavli Affiliate: Katja C. Nowack | Summary:Geometrically frustrated lattices can display a range of correlated phenomena, ranging from spin frustration and charge order to dispersionless flat bands due to quantum interference. One particularly compelling family of such materials is the half-valence spinel Li$B_2$O$_4$ materials. On the $B$-site frustrated pyrochlore sublattice, the interplay of correlated metallic […]
Kavli Affiliate: Dan Luo | First 5 Authors: Dan Luo, Jinyu Zhou, Le Xu, Sisi Yuan, Xuan Lin | Summary: Predicting drug-target binding affinity (DTA) is essential for identifying potential therapeutic candidates in drug discovery. However, most existing models rely heavily on static protein structures, often overlooking the dynamic nature of proteins, which is crucial […]
Kavli Affiliate: Nicholas L. Abbott| First 5 Authors: Joseph W. Abbott, Joseph W. Abbott, , , | Summary:Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accuracy at the base, reliable predictions are unlikely at any level that follows. The software package FHI-aims […]
Kavli Affiliate: Debanjan Chowdhury | Summary:Metals at the brink of electronic quantum phase transitions display high-temperature superconductivity, competing orders, and unconventional charge transport, revealing strong departures from conventional Fermi liquid behavior. Investigation of these fascinating intertwined phenomena has been at the center of research across a variety of correlated materials over the past many decades. […]
Kavli Affiliate: Zhiting Tian | First 5 Authors: Masato Ohnishi, Tianqi Deng, Pol Torres, Zhihao Xu, Terumasa Tadano | Summary: Understanding the anharmonic phonon properties of crystal compounds — such as phonon lifetimes and thermal conductivities — is essential for investigating and optimizing their thermal transport behaviors. These properties also impact optical, electronic, and magnetic […]
Kavli Affiliate: David Muller | Summary:Extracting continuum properties of quantum field theories from discretized spacetime is challenging due to lattice artifacts. Renormalization-group (RG)-improved lattice actions can preserve continuum properties, but are in general difficult to parameterize. Machine learning (ML) with gauge-equivariant convolutional neural networks provides a way to efficiently describe such actions. We test a […]