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#artificial intelligence Preprint Oct 2026

The Trinity:Capability-Driven Recursive Self-Improvement for Multimodal Agents

The Trinity is introduced, a recursive self-improvement framework coupling world generation with Harness evolution through three roles: Creator, Explorer, and Evolver, which introduces Capability-Driven Real2Sim2Real: for heterogeneous tasks at the same node, Creator abstracts their common requirements into simplified,...

Wei-Dong Tang, Rui-Heng Wang, Jing-Xuan Zhang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

CUA-Sandbox: Efficient Environments for Computer-Use Agent Reinforcement Learning

CUA-Sandbox is introduced, which separates private state capsules from shared runtimes through state-scoped execution and transactional lifecycle operations, including resets and branches, while retaining the original software interfaces and task evaluators.

Xin Yan, Zheng-Bo Jiao, Jia-Qi Liu et al. · 0 citations
#artificial intelligence Preprint Aug 2026

SpikeOPD: Stable On-Policy Distillation for Autoregressive Spiking Language Models

Spiking neural networks (SNNs) offer a path to energy-efficient language modeling through sparse encoding and event-driven computation, but training capable spiking language models from scratch remains difficult. A practical alternative is ANN-to-SNN migration through knowledge distillation (KD), where a pretrained art...

En-Qiao Lu, Xingrui Yu, Yi-Wei Fu et al. · 0 citations

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