Author

Si-Rui Chen

2 papers indexed here

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Preprint Aug 2026

Astar: Learning to Propose Evolution Directions for Self-Evolving Industrial AI Systems

This work proposes Astar, a training-based approach that learns a specialized evolution-guiding model from the abundant iteration histories of industrial systems, and proposes a pipeline that turns noisy historical commits into a large, clean evolutionary corpus via pairwise sample expansion and noise filtering.

Jin-Xin Hu, Hao Deng, Hai-Bo Xing et al. · 2 citations

#artificial intelligence Preprint Sep 2026

Predict, Don't Iterate: Efficient Adaptive-Length Infilling for Diffusion Language Models

PILL (Probing-based InfiLling with preset-Length-free decoding), an efficient infilling method for DLMs that requires no preset initial length and adds far fewer extra forward passes than baselines, substantially reducing inference time is proposed.

Hao-Bo Xu, Si-Rui Chen, Yuan-Chen Bei et al. · 6 citations