Meta learning and recursive self-improvement are old ideas. Foundation models breathe new life into them. Our new survey, “Self-Improvements in Modern Agentic Systems,” reviews how the concepts are continuing to evolve.
Paper: arxiv.org/abs/2607.13104
Project:
Postdoc Fellow at @AI_KAUST (with @SchmidhuberAI) | Previously PhD at @EdinburghUni | Working on Machine Learning and World Models
- Hey #ICLR2026, We're in Rio! Today we're presenting Huxley-Gödel Machine on the Oral 1C session (10:30 am-12, room 202 A/B. Apart from that, we also have a poster session later at 3:15 pm in Pavilion 3!
- We code only the agents that code themselves🤖🤖🤖! Wenyi Wang, @PiotrPiekosAI, @nbl_ai, Firas Laakom, @Beastlyprime, @MatOstasze, @MingchenZhuge, @SchmidhuberAI🚨Time to let agents code themselves! Meet Huxley-Gödel Machine (HGM), a game changer in coding agent development🚨 [🤖vs.🧑💻]HGM evolves by self-rewrites to match the best officially checked human-engineered agents on SWE-Bench Lite despite being optimized on a different dataset.
- Dear #ICLR2025 attendees, pls drop by our poster tomorrow if you’re interested in RNNs, world models, or some random chats. Looking forward to seeing you! Sat 26 Apr 15:00-18:00 At Hall 3 + Hall 2B #317.



