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From the 1 of 11 linked papers with an AI index.

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11 papers

cs.CV2026

CoverPrune: Coverage-Driven Token Pruning for 3D VLMs via Optimal Transport

Peng Ling, Yingda Yin, Lingting Zhu +5

While 3D Vision-Language Models (3D VLMs) have demonstrated remarkable spatial reasoning capabilities, they suffer from massive visual token counts that create severe computational…

math.PR2026

A Direct Route to Markov Chain Convergence via Asymptotic Equivalence with the Target

Patrick Forré, Patrick Forré

For a Markov kernel with an invariant probability measure , we give a self-contained proof of the Markov chain convergence theorem via a criterion called asymptotic equivale…

cs.LG2026

AVQ-Attention: Adaptive Vector-Quantized Attention

Winfried van den dool, Patrick Forré, Amir Habibian +2

The paper introduces Adaptive Vector-Quantized (AVQ) Attention, which dynamically allocates codebook capacity to the most important regions of the key space, preserving O(MN) compl…

cs.GT2026

Möbius transforms and Shapley values for vector-valued functions on weighted directed acyclic multigraphs

Patrick Forré, Abel Jansma

Möbius inversion and Shapley values are two mathematical tools for characterizing and decomposing higher-order structure in complex systems. The former defines higher-order intera…

cs.IT2026

Abstract Markov Random Fields

Leon Lang, Clélia de Mulatier, Rick Quax +1

Markov random fields are known to be fully characterized by properties of their information diagrams, or I-diagrams. In particular, for Markov random fields, regions in the I-diagr…

math.ST2026

Are Bayesian networks typically faithful?

Philip Boeken, Patrick Forré, Joris M. Mooij

Faithfulness is a common assumption in causal inference, often motivated by the fact that the faithful parameters of linear Gaussian and discrete Bayesian networks are typical, and…