Author

Feiyang Kang

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#artificial intelligence Preprint Oct 2026

Hybrid Latent Attention for Looped Language Models

Looped language models apply the same stack of layers T times to each token, which deepens the model without adding parameters but multiplies its key-value (KV) cache by T. The larger cache limits how many sequences a GPU can decode at once and slows each decoding step, which reads the whole cache. We propose Hybrid La...

Yu-Han Chen, Si-Yuan Zhang, Nan Wang et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Belief-Calibrated Optimization: An Explicit World Model for Agentic Optimization

Belief-Calibrated Optimization is introduced, a method that writes that belief down as a persistent in-context document and continually revises that document as new candidates are evaluated, and reaches a higher train passrate than a matched control that lacks only the world model.

Yu-Han Chen, Zhi-Hua Tian, Mahavir Dabas et al. · 1 citation