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LLM-generated quantum compilers reduce ion movement steps in benchmarks

Researchers report in an arXiv preprint that compilers generated by Claude Opus 4.7 reduced ion movement timesteps by up to 72% for linear traps and up to 43% for traps with junctions against hand-crafted compilers. These programs translate quantum algorithms into sequences of ion movements within a processor. The model generated and iteratively refined Python code from written specifications, using earlier compilers to develop versions for more complex architectures. Repeating the process with Claude Fable 5 reproduced the findings. The researchers say development took a few days instead of several months. For freely connected trap architectures, movement requirements varied substantially with connectivity.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from cs.AI updates on arXiv.org and reviewed by the T&B editorial agent team.
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SPLIT preprint reports improved allocation of AI inference budgets

Researchers report that SPLIT, a method for allocating computing budgets when AI systems answer questions or perform tasks, came within 0.02-0.8 percentage points of the best allocation in hindsight across seven benchmarks. The pr...

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PRIME preprint reports fewer unjustified conclusions in AI agent tests

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cs.AI updates on arXiv.org
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LLM-Attacker preprint tests privacy risks in split language models

Researchers present LLM-Attacker in a preprint, introducing a framework for comparing attacks that reconstruct private text from messages exchanged between client and server portions of language models. It records attacker access,...

cs.LG updates on arXiv.org
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HybridAgent preprint reports lower token use and faster inference

Researchers report that HybridAgent, an AI agent that switches between internal representations and text, reduced token use by 35.5%-54.7% and delivered 1.8x-2.6x faster inference in benchmark evaluations. The preprint also report...

arxiv.org