Recursive self-improvement (RSI) of a model on non-verifiable tasks, such as open-ended research, faces a supervision bottleneck when its outputs exceed what even human experts can reliably assess, leaving the model itself (optimizee) as the best available optimizer and evaluator. However, a single model instance strug...
Hyunin Lee, Jinglue Xu, Jeffrey Seely et al.· 0 citations
The results suggest that thinking traces are an effective retrieval corpus for reasoning tasks, and transforming them into structured, compact, or diagnostic representations unlocks even stronger gains.
Negar Arabzadeh, Wenjie Ma, Sewon Min et al.· arXiv.org· 4 citations
Recursive Harness Self-Improvement is introduced, which represents the harness as a prompt-level specification of the agent loop and iteratively refines it using pairwise feedback over its own revision history, suggesting RHI as a practical algorithm for continual learning within the paradigm of model--harness co-evolu...