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AI & Data Science Preprint PDF DOI

Frequency-Aware Semantic Fusion with Gated Injection for AI-generated Image Detection

Shuchang Zhou, Shangkun Wu, Jiwei Wei, Ke Liu, Ran Ran, Caiyan Qin, Yang Yang ยท 2026

AI-generated images are becoming increasingly realistic and diverse, posing significant challenges for generalizable detection. While Vision Foundation Models (VFMs) provide rich semantic representatiโ€ฆ

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AI & Data Science Preprint PDF DOI

KellyBench: A Benchmark for Long-Horizon Sequential Decision Making

Thomas Grady, Kip Parker, Iliyan Zarov, Henry Course, Chengxi Taylor, Ross Taylor ยท 2026

Language models are saturating benchmarks for procedural tasks with narrow objectives. But they are increasingly being deployed in long-horizon, non-stationary environments with open-ended goals. In tโ€ฆ

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Computer Science Preprint PDF DOI

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning

Bowen Sun, Chaozhuo Li, Yaodong Yang, Yiwei Wang, Chaowei Xiao ยท 2026

Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a sequence of individually benign queries that collectiโ€ฆ

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AI & Data Science Preprint PDF DOI

Rethinking Agentic Reinforcement Learning In Large Language Models

Fangming Cui, Ruixiao Zhu, Cheng Fang, Sunan Li, Jiahong Li ยท 2026

Reinforcement Learning (RL) has traditionally focused on training specialized agents to optimize predefined reward functions within narrowly defined environments. However, the advent of powerful Largeโ€ฆ

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Physics Preprint PDF DOI

Optimisation of a silicon-tungsten electromagnetic calorimeter energy response to photons

Yukun Shi, Vincent Boudry ยท 2026

An innovative path for the detectors at future colliders to achieve higher performances is to use a Particle Flow approach, which requires highly granular calorimeters to image individual showers. Theโ€ฆ

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AI & Data Science Preprint PDF DOI

CastFlow: Learning Role-Specialized Agentic Workflows for Time Series Forecasting

Bokai Pan, Mingyue Cheng, Zhiding Liu, Shuo Yu, Xiaoyu Tao, Yuchong Wu, Qi Liu, Defu Lian, Enhong Chen ยท 2026

Recently, large language models (LLMs) have shown great promise in time series forecasting. However, most existing LLM-based forecasting methods still follow a static generative paradigm that directlyโ€ฆ

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Physics Preprint PDF DOI

Heisenberg-limited Hamiltonian learning without short-time control

Myeongjin Shin, Junseo Lee, Changhun Oh ยท 2026

Characterizing quantum systems by learning their underlying Hamiltonians is a central task in quantum information science. While recent algorithmic advances have achieved near-optimal efficiency in thโ€ฆ

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AI & Data Science Preprint PDF DOI

Taming Noise-Induced Prototype Degradation for Privacy-Preserving Personalized Federated Fine-Tuning

Yuhua Wang, Qinnan Zhang, Xiaodong Li, Huan Zhang, Yifan Sun, Wangjie Qiu, Hainan Zhang, Yongxin Tong, Zhiming Zheng ยท 2026

Prototype-based Personalized Federated Learning (ProtoPFL) enables efficient multi-domain adaptation by communicating compact class prototypes, but directly sharing them poses privacy risks. A common โ€ฆ

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Engineering Preprint PDF DOI

Learning-Based Hierarchical Scene Graph Matching for Robot Localization Leveraging Prior Maps

Nimrod Millenium Ndulue, Jose Andres Millan-Romera, Matteo Giorgi, Holger Voos, Jose Luis Sanchez-Lopez ยท 2026

Accurate localization is a fundamental requirement for autonomous robots operating in indoor environments. Scene graphs encode the spatial structure of an environment as a hierarchy of semantic entitiโ€ฆ

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AI & Data Science Preprint PDF DOI

Focus Session: Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification

Behnaz Ranjbar, Kirankumar Raveendiran, Sudeep Pasricha, Samarjit Chakraborty, Cecilia Carbonelli, Akash Kumar ยท 2026

The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software โ€ฆ

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AI & Data Science Preprint PDF DOI

Machine Unlearning for Class Removal through SISA-based Deep Neural Network Architectures

Ishrak Hamim Mahi, Siam Ferdous, Md Sakib Sadman Badhon, Nabid Hasan Omi, Md Habibun Nabi Hemel, Farig Yousuf Sadeque, Md. Tanzim Reza ยท 2026

The rapid proliferation of image generation models and other artificial intelligence (AI) systems has intensified concerns regarding data privacy and user consent. As the availability of public dataseโ€ฆ

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Engineering Preprint PDF DOI

Hybrid Anomaly Detection for Bullion Coin Authentication Leveraging Acoustic Signature Analysis

Krzysztof Siwek, Tran Hoai Linh, Tomasz Gryczka, Maciej Stodolski ยท 2026

The verification of bullion coin authenticity is essential for maintaining integrity within the precious metals market; however, the increasing sophistication of counterfeits has rendered traditional โ€ฆ

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Engineering Preprint PDF DOI

MotuBrain: An Advanced World Action Model for Robot Control

MotuBrain Team, Chendong Xiang, Fan Bao, Haitian Liu, Hengkai Tan, Hongzhe Bi, James Li, Jiabao Liu, Jingrui Pang, Kiro Jing, Louis Liu, Mengchen Cai, Rongxu Cui, Ruowen Zhao, Runqing Wang, Shuhe Huang, Yao Feng, Yinze Rong, Zeyuan Wang, Jun Zhu ยท 2026

Vision-Language-Action (VLA) models achieve strong semantic generalization but often lack fine-grained modeling of world dynamics. Recent work explores video generation models as a foundation for worlโ€ฆ

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AI & Data Science Preprint PDF DOI

On the Expressive Power of GNNs to Solve Linear SDPs

Chendi Qian, Christopher Morris ยท 2026

Semidefinite programs (SDPs) are a powerful framework for convex optimization and for constructing strong relaxations of hard combinatorial problems. However, solving large SDPs can be computationallyโ€ฆ

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Physics Preprint PDF DOI

YOSO: single-frame Gerchberg-Saxton phase retrieval with AI-based data augmentation for in-line holography

Julianna Winnik, Adam Walocha, Wojciech Ogonowski, Wiktor Forjasz, Piotr Arcab, Miko{l}aj Rogalski, Aleksandra Rutkowska, Marzena Stefaniuk, Jose Angel Picazo-Bueno, Vicente Mico, Maciej Trusiak, Maria Cywinska ยท 2026

We present YOSO (You Only Shot Once), a single-frame phase retrieval framework for digital in-line holographic microscopy (DIHM) in which supervised deep learning is used to numerically generate an adโ€ฆ

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Physics Preprint PDF DOI

Data-Efficient Indentation Size Effect Correction in Steels Using Machine Learning and Physics-Guided Augmentation

Radmir Karamov, Tagir Karamov ยท 2026

Shallow nanoindentation enables mechanical characterization of thin films, individual phases and other volume-constrained materials, but measured hardness is often inflated by the indentation size effโ€ฆ

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AI & Data Science Preprint PDF DOI

GourNet: A CNN-Based Model for Mango Leaf Disease Detection

Ekram Alam, Jaydip Sanyal, Akhil Kumar Das, Arijit Bhattacharya, Farhana Sultana ยท 2026

Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both thโ€ฆ

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AI & Data Science Preprint PDF DOI

Learning to Reason: Targeted Knowledge Discovery and Fuzzy Logic Update for Robust Image Recognition

Gurucharan Srinivas, Joshua Niemeijer, Frank Koster ยท 2026

Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in the loss function or apply post-processing moduleโ€ฆ

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AI & Data Science Preprint PDF DOI

Autonomous Traffic Signal Optimization Using Digital Twin and Agentic AI for Real-Time Decision-Making

Salman Jan, Toqeer Ali Syed, Shahid Kamal, Qamar Wali, Ali Akarma ยท 2026

This article outlines a new framework of traffic light optimization through a digital twin of the transport infrastructure, managed by agentic AI to ensure real-time autonomous decisions. The frameworโ€ฆ

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Computer Science Preprint PDF DOI

Why Self-Supervised Encoders Want to Be Normal

Yuval Domb ยท 2026

We develop a geometric and information-theoretic framework for encoder-decoder learning built on the Information Bottleneck (IB) principle. Recasting IB as a rate-distortion problem with Kullback-Leibโ€ฆ

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