Dyslexia impacts 5–15% of school-aged children globally, but automated screening mechanisms to detect it are rare, and such tools are relatively scarce in non-Latin scripts. The work introduces a bilingual deep learning model for dyslexia preliminary diagnosis through digitalized handwriting samples in both English and Arabic. Two computational methods were employed and compared systematically: the page-oriented classification strategy and the character-oriented classification method. For Arabic, an EnhancedCNN architecture is proposed to classify whole-page scans end-to-end by coping with […]

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Future wireless communication systems will increasingly rely on the integration of millimeter wave (mmWave) and sub-6 GHz bands to meet heterogeneous demands on high-speed data transmission and extensive coverage. To fully exploit the benefits of mmWave bands in massive multiple-input multiple-output (MIMO) systems, highly accurate channel state information (CSI) is required. However, directly estimating the mmWave channel demands substantial pilot overhead due to the large CSI dimension and low signal-to-noise ratio (SNR) led by severe path loss and […]

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arXiv:2601.20054v1 Announce Type: new Abstract: Multi-vehicle autonomous driving couples strategic interaction with hybrid (discrete-continuous) maneuver planning under shared safety constraints. We introduce IBR-GCS, an Iterative Best Response (IBR) planning approach based on the Graphs of Convex Sets (GCS) framework that models highway driving as a generalized noncooperative game. IBR-GCS integrates combinatorial maneuver reasoning, trajectory planning, and game-theoretic interaction within a unified framework. The key novelty is a vehicle-specific, strategy-dependent GCS construction. Specifically, at each best-response update, each vehicle […]

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Hi everyone, I’m working on a university project and could really use some advice from people with more experience in autonomous navigation / RL / simulation. Task: I need to design a deep learning model that directly controls a drone (x, y, z, pitch, yaw — roll probably doesn’t make much sense here 😅). The drone should autonomously patrol and map indoor and outdoor environments. Example use case: A warehouse where the drone automatically flies through all aisles […]

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arXiv:2601.08989v1 Announce Type: new Abstract: We study the Torus Puzzle, a solitaire game in which the elements of an input $m times n$ matrix need to be rearranged into a target configuration via a sequence of unit rotations (i.e., circular shifts) of rows and/or columns. Amano et al. proposed a more permissive variant of the above puzzle, where each row and column rotation can shift the involved elements by any amount of positions. The number of rotations needed […]

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Table of links Abstract 1 Introduction 2 Background and Related Work Software Security Coding Weaknesses Security Shift-Left Modern Code Review Code Review for Software Security Security Concern Handling Process in Code Review 3 Motivating Examples 4 Case Study Design Research Questions Studied Projects Data Collection Coding Weakness Taxonomy Study Overview Security Concern Identification Approach (RQ1) Alignment Analysis of Known Vulnerabilities (RQ2) Handling Process Identification (RQ3) 5 Preliminary Analysis PA1: Prevalence of Coding Weakness Comments PA2: Preliminary Evaluation of […]

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arXiv:2510.10854v2 Announce Type: replace-cross Abstract: Diffusion models have demonstrated remarkable performance in generating high-dimensional samples across domains such as vision, language, and the sciences. Although continuous-state diffusion models have been extensively studied both empirically and theoretically, discrete-state diffusion models, essential for applications involving text, sequences, and combinatorial structures, remain significantly less understood from a theoretical standpoint. In particular, all existing analyses of discrete-state models assume score estimation error bounds without studying sample complexity results. In this work, we […]

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Andrej Karpathy released autoresearch, a minimalist Python tool designed to enable AI agents to autonomously conduct machine learning experiments. The project is a stripped-down version of the nanochat LLM training core, condensed into a single-file repository of approximately ~630 lines of code. It is optimized for execution on a single NVIDIA GPU. The Autonomous Iteration Loop The framework establishes a specific division of labor between the human researcher and the AI agent. The system operates on a continuous […]

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