Large language models (LLMs) demonstrate strong performance, but they often lack transparency. We introduce GeoLAN, a training framework that treats token representations as geometric trajectories and applies stickiness conditions inspired by recent developments related to the Kakeya Conjecture. We have developed two differentiable regularizers, Katz-Tao Convex Wolff (KT-CW) and Katz-Tao Attention (KT-Attn), that promote isotropy and encourage diverse attention. Our experiments with Gemma-3 (1B, 4B, 12B) and Llama-3-8B show that GeoLAN frequently maintains task accuracy while improving geometric […]

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The Protocol The magnetic rack hissed. Kael let go of the plasma torch. Click. The green light on the wall turned solid. The tool was secured. His hands were empty. For the first time in ten years, Kael didn’t check his pockets for inventory. He didn’t pat his hip for a weapon. He just stood there, the weight gone, his hands trembling slightly from the absence of a burden. Vvvvt. The bone-conduction implant behind his ear vibrated. “PROTOCOL […]

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In Cursor, you can connect any LLM via API that is compatible with the OpenAI request format. This means you can connect Claude via API and pay for tokens. However, if you have a Claude subscription, you can only use it in Claude Code. There, the request format is Anthropic, which differs from OpenAI. You cannot take your Claude subscription and add it to Cursor because the request formats are incompatible. You cannot make requests to the Claude […]

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arXiv:2602.17678v1 Announce Type: new Abstract: Reproducible container builds promise a simple integrity check for software supply chains: rebuild an image from its Dockerfile and compare hashes. We build a Docker measurement pipeline and apply it to a stratified sample of 2,000 GitHub repositories that contained a Dockerfile. We found that only 56% produce any buildable image, and just 2.7% of those are bitwise reproducible without any infrastructure configurations. After modifying infrastructure configurations, we raise bitwise reproducibility by 18.6%, […]

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Constitutional AI is a method to oversee and control LLMs based on a set of rules written in natural language. These rules are typically written by human experts, but could in principle be learned automatically given sufficient training data for the desired behavior. Existing LLM-based prompt optimizers attempt this but are ineffective at learning constitutions since (i) they require many labeled examples and (ii) lack structure in the optimized prompts, leading to diminishing improvements as prompt size grows. […]

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arXiv:2603.17060v2 Announce Type: new Abstract: Background: Cheating in university education is commonly described as context dependent and influenced by assessment design, institutional norms, and student interpretation. In software engineering education, programming oriented coursework has historically involved ambiguity around collaboration, reuse, and external assistance. Recently, large language models (LLMs) have introduced additional mediation in the production of code and related artifacts. Aims: This study investigates how software engineering students describe experiences of using LLMs in ways they perceived as […]

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arXiv:2604.20845v1 Announce Type: new Abstract: Next Point-of-Interest (POI) recommendation plays a crucial role in location-based services by predicting users’ future mobility patterns. Existing methods typically compute a single user representation from historical trajectories and use it to score all candidate POIs uniformly. However, this candidate-agnostic paradigm overlooks that the relevance of historical visits inherently depends on which candidate is being evaluated. In this paper, we propose CaST-POI, a candidate-conditioned spatiotemporal model for next POI recommendation. Our key insight […]

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Note: This is a short edition. Based on the full paper published December 28, 2025: The Augmented Self: AI Scaffolds, Offloading, and the Drift Toward Dependency A subtle change is underway in how knowledge work begins. More and more, the first coherent version of a thought arrives already shaped—quickly, fluently, and with plausible next steps attached. This can feel like simple convenience. But when the starting point changes, the rest of the workflow changes with it: what gets practiced, what […]

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Byline: Malana VanTyler Artificial intelligence is a double-edged sword for global enterprises. On the one hand, it optimizes efficiency. On the other hand, it multiplies security risks, such as data leakage via large language models (LLMs). Chetan Pathade, a GenAI Security Engineer, has taken on this challenge. With a rare mix of practical skill and analytical prowess, he helps secure cloud infrastructure from cyberattacks. Securing the AI Shift Enterprises race to deploy LLMs and generative systems at scale. […]

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