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Shunian Chen

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#artificial intelligence Preprint Sep 2026

Aperture: Merge-Consistent Rotary States for Compressed Tokens

Aperture stores Fourier moments of the token's weighted support at the model's rotary frequencies, and it is proved that these moments have minimal real dimension among continuous states sufficient for the selected expected rotary interactions.

Yu-Hao Du, Shu-Nian Chen · 0 citations
#artificial intelligence Preprint Sep 2026

The Price of Token Boundaries: Compression Certificates and Prediction

Pre-tokenisation restricts which text fragments can become prediction units, but its compression cost is obscured when tokenisers are compared only under the same boundaries. We measure this cost by bounding the minimum token count from both sides, with and without a regular-expression boundary rule. Nonnegative prices...

Yu-Hao Du, Shu-Nian Chen · 0 citations
#artificial intelligence Preprint Sep 2026

World Models with Predictable Long-Horizon Marginals

Three properties of a world model are distinguished: the distribution it approaches, the rate of approach, and the conditional dynamics it learns, which derive an absolute convergence bound from finite initialization banks and control departure from the reference through conditional action-space divergence.

Yu-Hao Du, Shu-Nian Chen · 0 citations
Jul 2026

SpatialCLI: Learning to Reason With Spatial Tools, Then Without Them

SpatialCLI is proposed, a framework that teaches VLMs to reason with spatial tools and progressively internalize the specialist perceptual capabilities they provide and introduces SpatialCLI-Bench, a 516-example benchmark for compositional perception across localization, segmentation, depth, and pose.

Yang Zhou, Zixuan Huang, Sunzhu Li et al. · 0 citations

AutoJudger : An Adaptive Evaluation Framework for Efficient Benchmarking of MLLMs

This work introduces A 2 -Judger, a novel MLLM-based A gentic instantiation of A uto Judger equipped with semantic-aware retrieval and dynamic memory that significantly improves sample efficiency while maintaining reliable evaluation results.

Xuanwen Ding, Chengjun Pan, Zejun Li et al. · 0 citations

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