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Zachary W. Ulissi, Brandon M. Wood, Aditi S. Krishnapriyan et al. · 6 Mar 2026
AllScAIP is an attention-based machine-learning interatomic potential model that scales efficiently to large systems through data-driven all-to-all node attention while maintaining energy conservation and achieving state-of-the-art accuracy in molecular dynamics simulations.
25 Jun 2026
Outcome-based reinforcement learning provides a stable optimization backbone for language agents, but its sparse trajectory-level rewards provide little guidance on which intermediate decisions should be reinforced or suppressed.
9 Aug 2026
Modern LLM agents are often improved by modifying prompts, tools, or workflows manually, while the executable scaffold surrounding the model---the \emph{harness}---is typically treated as a fixed artifact after deployment.