arXiv:2602.05082v1 Announce Type: cross Abstract: In recent years, explaining decisions made by complex machine learning models has become essential in high-stakes domains such as energy systems, healthcare, finance, and autonomous systems. However, the reliability of these explanations, namely, whether they remain stable and consistent under realistic, non-adversarial changes, remains largely unmeasured. Widely used methods such as SHAP and Integrated Gradients (IG) are well-motivated by axiomatic notions of attribution, yet their explanations can vary substantially even under system-level conditions, […]

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Before I got a laptop, I used to work on my phone with a keyboard connected via an OTG. It wasn’t a fancy phone – just a Galaxy J2 with a micro-USB port. I used a membrane keyboard with a cheap $0.4 OTG adapter, but it got the job done. I put the savings towards a laptop and once I bought my first laptop, forgot all about that OTG hack I was using. Fast forward to 2026 – […]

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arXiv:2602.07095v1 Announce Type: new Abstract: Recent advances in image editing models have demonstrated remarkable capabilities in executing explicit instructions, such as attribute manipulation, style transfer, and pose synthesis. However, these models often face challenges when dealing with implicit editing instructions, which describe the cause of a visual change without explicitly detailing the resulting outcome. These limitations arise because existing models rely on uniform editing strategies that are not equipped to handle the complex world knowledge and reasoning required […]

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je travail sur un pfe et je dois faire implémentation de qlq algorithme pour l’optimisation des feux de signalisation adaptatifs , j’ai terminé de configurer mon réseau (routes, feux, vehichules, ect) je dois faire une comparaison entre des scénario , scénario fixe ,Algo MA2C , MA2C avec améliorations et ppo ect mais je ne sais pas comment faire je dois aussi develloper une app pour visualiser les métriques et pour la comparaison et je travail avec SUMO , […]

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arXiv:2602.20200v1 Announce Type: new Abstract: Hierarchical Vision-Language-Action (VLA) models have rapidly become a dominant paradigm for robotic manipulation. It typically comprising a Vision-Language backbone for perception and understanding, together with a generative policy for action generation. However, its performance is increasingly bottlenecked by the action generation proceess. (i) Low inference efficiency. A pronounced distributional gap between isotropic noise priors and target action distributions, which increases denoising steps and the incidence of infeasible samples. (ii) Poor robustness. Existing policies […]

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arXiv:2603.10021v1 Announce Type: new Abstract: Gemini said Lawmakers today face continuous calls to “future proof” the legal system against generative artificial intelligence, algorithmic decision-making, targeted advertising, and all manner of emerging technologies. This Article takes a contrarian stance: it is not the law that needs bolstering for the future, but the future that needs protection from the law. From the printing press and the elevator to ChatGPT and online deepfakes, the recurring historical pattern is familiar. Technological breakthroughs […]

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The Job-Shop Scheduling Problem (JSSP), under various forms of manufacturing uncertainty, has recently attracted considerable research attention. Most existing studies focus on parameter uncertainty, such as variable processing times, and typically adopt the actor-critic framework. In this paper, we explore a different but prevalent form of uncertainty in JSSP: structural uncertainty. Structural uncertainty arises when a job may follow one of several routing paths, and the selection is determined not by policy, but by situational factors (e.g., the […]

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Security is treated as a critical priority in modern software organizations. It appears in roadmaps, compliance documents, architectural reviews, and post-incident reports. Yet there is one place where security is still largely invisible: the hiring pipeline. Most engineering teams invest heavily in security tools, audits, and policies, yet devote little effort to evaluating whether new hires can write secure code. The assumption is simple and widespread. Secure coding can be taught later. What matters during hiring is speed, […]

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arXiv:2602.00884v1 Announce Type: new Abstract: Neural operators have shown promise in learning solution maps of partial differential equations (PDEs), but they often struggle to generalize when test inputs lie outside the training distribution, such as novel initial conditions, unseen PDE coefficients or unseen physics. Prior works address this limitation with large-scale multiple physics pretraining followed by fine-tuning, but this still requires examples from the new dynamics, falling short of true zero-shot generalization. In this work, we propose a […]

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