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Atomic benchmarks for sixth-period elements (Cs-Rn) are established to sub-millihartree precision under correlation-consistent effective core potentials (ccECPs) using coupled-cluster [up to CCSDT(Q)] and full configurat...
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Recent advances in general-purpose AI models and agentic systems have enabled them to perform some CAD tasks. A systematic assessment is now needed to establish what these systems can accomplish and how well their output...
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We introduce avatar referring segmentation, which selects regions of animatable Gaussian avatars from language queries. A query can also specify a pose or motion to select matching intervals. This lets users interact wit...
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Motivated by recursive self-improvement (RSI), we study how LLM agents can learn through external memory without updating model parameters. Extracting useful experience from a single attempt is difficult: flawed reasonin...
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Multi-agent scientific discovery with large language models raises a coupled learning problem: research assignments determine both which experiments are pursued and the experiences from which agents adapt. We introduce M...
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We consider the metric distortion framework for voting, where $n$ voters and $m$ candidates are embedded in an unknown metric space. A voting rule selects a candidate using only voters' ordinal preferences, and its disto...
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Reverse target fishing identifies protein targets for a query molecule and is central to drug discovery and repurposing. Discriminative approaches adapted from virtual screening face sparse, long-tailed associations and ...
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Lattice inverse-design methods can generate cells that match prescribed effective properties, but property feasibility does not imply material efficiency. Removing redundant material from an existing lattice while preser...
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Living organisms control water to transport matter, transfer energy and drive chemical reactions. In this perspective, we argue that porous silicon can give engineering materials comparable control over water. Its pore a...
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Large, unlabeled datasets of prior experience have become increasingly available for agentic tasks in domains such as robotics and coding. A common recipe for these tasks is to train a policy using the prior data, and th...
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Online scene change detection requires an agent to detect what has changed in a previously mapped environment while it is still on site, observing from unconstrained viewpoints and without access to future observations. ...
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Long-running assistants often interpret follow-up requests whose referents, constraints, and active goals were established many turns earlier. The central challenge is therefore not only context length, but retrieval int...
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Individually competent robot skills can fail when composed: tools may lack a required capability, completion signals may misrepresent physical progress, and one skill may leave a state that violates its successor's prere...
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For a fixed finite set $N$ of at least two agents, we investigate the lattice $L_N$ of coalition logics between minimal coalition logic (MCL) and classical coalition logic (CL), with extensions required to be structural....
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Frequency-domain methods have shown strong potential for low-light image enhancement (LLIE) because they can effectively regulate global illumination. However, most existing methods assume that amplitude and phase can be...