Autonomous R&D agents now write, run, and improve executable artifacts under automated evaluation-but largely as laboratory instruments: shown on curated benchmarks, with gains that are hard to trace to a cause and costs well above what sustained engineering practice absorbs. The limitation is structural. Most systems...
Jin Li, Ahmed Murtadha, Zhiying Wang et al.· 1 citation
Praxist is introduced, a lineage-centered generational system that converts reproducible artifacts and evaluator outcomes into a typed evidence graph of findings, lane-structured frontiers, and agendas, and Separating local artifact construction from cohort-level evidence synthesis lets later attempts inherit validated...
Jin Li, Ahmed Murtadha, Zhiying Wang et al.· 0 citations
Scaling Large Language Models (LLMs) has been driven mainly by enlarging the Transformer backbone, but for an already-strong model this requires another round of costly pretraining. We study whether an existing backbone can keep improving by allocating more computation to each token while leaving the Transformer backbo...
Aiwei Liu, Cheng Shi, Chuhan Wu et al.· 2 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
