Source record

Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2608.16951.

Pipeline notes

The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.

A framework where an LLM-based Scientist agent iteratively applies the scientific method (hypothesis, implementation, testing, feedback) inside an evaluation environment, with a second Kuhn agent injecting paradigm-shifting conjectures to escape local optima. Demonstrated by discovering Delta V (state-of-the-art on ProteinGym) and DALE (outperforms STREME on ENCODE motifs), using 704M tokens on a single CPU VM.

Concrete evidence that an LLM agent loop can produce state-of-the-art novel algorithms on two unrelated benchmarks, with a published token-cost figure. Useful as a reference pattern for agentic research workflows.

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