Skip to content
English

Switch theme

arXiv 2610.29784 · cs.CL · 2026-10-21

Evolving with Open Worlds: Towards Recursive Self-Improvement for Future Forecasting

Zhipeng Chen, Yunsen Liang, Yanxi Chen, Hongkang Zhao, Lingyun Feng, Ruiyang Ren, Guoxin Chen, Jia Deng and 7 more

Affiliation unverified

In latest · #363 Added on 2026-10-26

One-line takeaway

DeepEvolve studies recursive self-improvement using future-event forecasting as a continuously changing, verifiable environment, turning the reasoning trajectory behind each prediction back into agent capability.

DeepEvolve 以未来事件预测为环境研究递归自我改进:智能体在持续变化、可客观验证的世界里交互,把每次预测背后的推理轨迹转化为能力。

19HF upvotes
4GitHub stars
0Citations (Semantic Scholar)
35.6Buzz score

Read on arXiv PDF Hugging Face discussion Code

About this data

Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-26.

The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.

Data updated: Latest AI papers(UTC+8)