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  1. LoKA: Low-precision Kernel Applications for Recommendation Models At Scale

    Published in ArXiv cs.LG Recent Papers (2026)
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  2. Learning to Focus Synthetic Aperture Radar On-line with State-Space Models

    Published in ArXiv cs.ET Recent Papers (2026)
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  3. ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

    Published in ArXiv cs.CV Recent Papers (2026)
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  4. ORCE: Order-Aware Alignment of Verbalized Confidence in Large Language Models

    Published in ArXiv cs.LG Recent Papers (2026)
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  5. The Evaluation Differential: When Frontier AI Models Recognise They Are Being Tested

    Published in ArXiv cs.HC Recent Papers (2026)
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  6. FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models

    Published in ArXiv cs.DB Recent Papers (2026)
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  7. A Causal Language Modeling Detour Improves Encoder Continued Pretraining

    Published in ArXiv cs.CL Recent Papers (2026)
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  8. A Fully Abstract Model of PCF Based on Extended Addressing Machines

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  9. Parameterized Model-checking of Discrete-Timed Networks and Symmetric-Broadcast Systems

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  10. Advanced Model Consistency Restoration with Higher-Order Short-Cut Rules

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  11. A Formal Model for Polarization under Confirmation Bias in Social Networks

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  12. Quantum Control in the Unitary Sphere: Lambda-S1 and its Categorical Model

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  13. Trakhtenbrot's Theorem in Coq: Finite Model Theory through the Constructive Lens

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  14. Satisfiability and Model Checking for the Logic of Sub-Intervals under the Homogeneity Assumption

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  15. On Thin Air Reads: Towards an Event Structures Model of Relaxed Memory

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  16. Two Variable vs. Linear Temporal Logic in Model Checking and Games

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  17. Complexity of Model Checking Recursion Schemes for Fragments of the Modal Mu-Calculus

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  18. Models for industry differentiation in decision-making systems with an application to the Ukrainian economy

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  19. Pop2net: Bipartite network generation for agent-based modeling

    Published in Journal of Open Source Software (2026)
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  20. pytau: A Python package for streamlined changepoint model analysis in neuroscience

    Published in Journal of Open Source Software (2026)
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