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Zhi-Nan Hou

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#artificial intelligence Preprint Sep 2026

Efficient Reasoning via Constrained Optimization in Latent Space

Large Reasoning Models (LRMs) have shown remarkable reasoning capabilities, yet they still suffer from overthinking, generating redundant reasoning steps which incur substantial token consumption. Existing methods, such as suppressing reflective keywords or forcing shorter reasoning lengths, attempt to mitigate this is...

Zhi-Nan Hou, Xing-Chen Li, Ke-You You · 0 citations
Preprint Sep 2026

GeoTrussRover: Morphological Computation with Contact-Semantic Control Primitives

Reconfigurable robots can change their contact geometry when a fixed body cannot negotiate an obstacle. A variable-geometry truss (VGT) distributes this shape change through a load-bearing structure, but coupling it to a mobile base creates a high-dimensional coordination problem. GeoTrussRover combines an electrically...

Mu-Yuan Ma, Yi Zhang, Yang Yang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

What Matters in On-Policy Distillation? A Perspective on Data Efficiency and Data Selection

On-Policy Distillation (OPD) has emerged as a widely adopted post-training paradigm for enhancing large language models in reasoning domains. However, the data-centric mechanisms in OPD remain relatively underexplored. This paper presents a empirical study of data efficiency and data selection in OPD. We begin by inves...

Zhi-Nan Hou, Jiaqi Zhang, Xun-Liang Cai et al. · 2 citations

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