A real experiment with GPT-5.3 Codex, a browser game arcade, and a methodology gap nobody seems to have solved yet. Let’s be honest about the two camps developers fall into when using AI coding agents today. Camp 1: Vibe Coders. Single prompt, see what happens, iterate reactively, ship something that mostly works. Fast. Messy. Surprisingly effective for simple projects. Camp 2: Spec Driven developers. Formal requirements. Structured documentation. Change proposals. Review cycles before touching a line of code. […]

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arXiv:2602.00905v1 Announce Type: new Abstract: Although the stabilization of underactuated systems remains a challenging problem, the total energy shaping approach provides a general framework for addressing this objective. However, the practical implementation of this method is hindered by the need to analytically solve a set of partial differential equations (PDEs), which constitutes a major obstacle. In this paper, a rotary inverted pendulum system is considered, and an interconnection and damping assignment passivity-based control (IDA-PBC) scheme is developed by […]

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In one of the recent interviews, Elon Musk has warned humanity that artificial intelligence could lead to “civilization destruction”. While talking about AI, so advanced that it will threaten our society, to most experts seems preliminary, one thing is certain: we depend on artificial intelligence as much as AI depends on us. Artificial intelligence systems run in your phone to help you capture better pictures, find relevant materials online, and optimize your storage space. But it all comes […]

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arXiv:2601.14495v1 Announce Type: new Abstract: There are several paradigms for integrating interactive and automated theorem provers, combining the convenience of powerful automation with strong soundness guarantees. We introduce a new approach for reconstructing proofs found by SMT solvers which we intend to be complementary with existing techniques. Rather than verifying or replaying a full proof produced by the SMT solver, or at the other extreme, rediscovering the solver’s proof from just the set of premises it uses, we […]

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arXiv:2602.06191v1 Announce Type: new Abstract: We study localization and control for unstable systems under coarse, single-bit sensing. Motivated by understanding the fundamental limitations imposed by such minimal feedback, we identify sufficient conditions under which the initial state can be recovered despite instability and extremely sparse measurements. Building on these conditions, we develop an active localization algorithm that integrates a set-based estimator with a control strategy derived from Voronoi partitions, which provably estimates the initial state while ensuring the […]

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arXiv:2510.13060v2 Announce Type: replace-cross Abstract: Reverse Kullback-Leibler (KL) divergence-based regularization with respect to a fixed reference policy is widely used in modern reinforcement learning to preserve the desired traits of the reference policy and sometimes to promote exploration (using uniform reference policy, known as entropy regularization). Beyond serving as a mere anchor, the reference policy can also be interpreted as encoding prior knowledge about good actions in the environment. In the context of alignment, recent game-theoretic approaches have […]

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Advances in multi-modal large language models (MLLMs) have inspired time series understanding and reasoning tasks, that enable natural language querying over time series, producing textual analyses of complex temporal dynamics. Recent attempts hybridize numerical time series with their visualized plots, facilitating precise value reasoning and visual structure comprehension for comprehensive time series understanding of MLLMs. However, effective cross-modal integration remains challenging due to fine-grained temporal misalignment across modalities and severe entanglement between shared and modality-specific semantics, which hinder […]

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arXiv:2604.04984v1 Announce Type: new Abstract: This work studies a variational formulation and numerical solution of a regularized morphoelasticity problem of shape evolution. The foundation of our analysis is based on the governing equations of linear elasticity, extended to account for volumetric growth. In the morphoelastic framework, the total deformation is decomposed into an elastic component and a growth component, represented by a growth tensor $G$. While the forward one-step problem — computing displacement given a growth tensor — […]

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arXiv:2603.28959v1 Announce Type: new Abstract: The exploration-exploitation trade-off is central to sequential decision-making and black-box optimization, yet how Large Language Models (LLMs) reason about and manage this trade-off remains poorly understood. Unlike Bayesian Optimization, where exploration and exploitation are explicitly encoded through acquisition functions, LLM-based optimization relies on implicit, prompt-based reasoning over historical evaluations, making search behavior difficult to analyze or control. In this work, we present a metric-level study of LLM-mediated search policy learning, studying how LLMs […]

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