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Jia-Jun Zhang

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#artificial intelligence Preprint Oct 2026

AgentSWE: Can Coding Agents Build the Agent You Actually Want?

As the production of software passes into the hands of software itself, coding agents are increasingly commissioned to build agents fitted to their users'own workflows. This delegation carries a quiet assumption, that the delivered agent will faithfully serve the requirement it was built for, rather than merely appear...

Jia-Hao Wang, Hong-Jin Qian, Yuyang Hu et al. · 0 citations

RecreationWorld: Scalable and Verifiable Environments for Hybrid Computer-Use Agents

This work introduces RecreationWorld, a five-platform framework built around recreation: given a running reference, an agent must discover its behavior and build a faithful implementation with no prescribed workflow, and introduces RecreationBench, comprising 250 diverse tasks across domains and platforms.

Shuai Bai, Jia-Yong Deng, Si-Cheng Fan et al. · 1 citation
#artificial intelligence Preprint Aug 2026

Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning

DyTrim is proposed, a principle-based dynamic pruning framework that reallocates gradient budget through class-aware pruning on labeled data and confidence-based soft pruning on unlabeled data and provides theoretical guarantees that DyTrim reduces class bias and improves generalization.

Yue Cheng, Jia-Jun Zhang, Xiao-Hui Gao et al. · 1 citation
Preprint Aug 2026

Qwen-CUA: Native Computer Use for (almost) Everything

Qwen-CUA is introduced, a native computer-use agent with a 397B-A17B Qwen mixture-of-experts backbone that outperforms Qwen3.7 and remains competitive with leading proprietary systems, and scalable verifiable interaction and hybrid tool use as key directions.

Dunjie Lu, Shuai Bai, Tianyi Bai et al. · 2 citations

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