The authors assembled a diagnostic benchmark covering three substantially different tasks: optimizing molecules, selecting sentinel nodes in networks and generating efficient GPU kernels.
LLM optimizers often stall within narrow families of design principles
Across three optimization domains, distinct candidates frequently concealed convergence on a restricted set of underlying strategies.
Big Tech
Nian Ran · Tianhe Jia · Zhengyang Mu · Yue Wang · Sebastian Brulin · Markus Olhofer · +3 more
The University of Manchester · University of Chinese Academy of Sciences · UKRI AI Centre for Doctoral Training in Decision Making for Complex Systems · Zhongguancun Academy · NVIDIA
Research Digest··2 min read
Thread:Decision models (System One)
Ran and colleagues investigate why feedback-driven LLM optimizers often improve rapidly and then plateau.
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