Archives AI News

IQNN-CS: Interpretable Quantum Neural Network for Credit Scoring

arXiv:2510.15044v1 Announce Type: new Abstract: Credit scoring is a high-stakes task in financial services, where model decisions directly impact individuals’ access to credit and are subject to strict regulatory scrutiny. While Quantum Machine Learning (QML) offers new computational capabilities, its…

Internalizing World Models via Self-Play Finetuning for Agentic RL

arXiv:2510.15047v1 Announce Type: new Abstract: Large Language Models (LLMs) as agents often struggle in out-of-distribution (OOD) scenarios. Real-world environments are complex and dynamic, governed by task-specific rules and stochasticity, which makes it difficult for LLMs to ground their internal knowledge…

Hybrid Autoencoder-Based Framework for Early Fault Detection in Wind Turbines

arXiv:2510.15010v1 Announce Type: new Abstract: Wind turbine reliability is critical to the growing renewable energy sector, where early fault detection significantly reduces downtime and maintenance costs. This paper introduces a novel ensemble-based deep learning framework for unsupervised anomaly detection in…

ES-C51: Expected Sarsa Based C51 Distributional Reinforcement Learning Algorithm

arXiv:2510.15006v1 Announce Type: new Abstract: In most value-based reinforcement learning (RL) algorithms, the agent estimates only the expected reward for each action and selects the action with the highest reward. In contrast, Distributional Reinforcement Learning (DRL) estimates the entire probability…

Physics-informed data-driven machine health monitoring for two-photon lithography

arXiv:2510.15075v1 Announce Type: new Abstract: Two-photon lithography (TPL) is a sophisticated additive manufacturing technology for creating three-dimensional (3D) micro- and nano-structures. Maintaining the health of TPL systems is critical for ensuring consistent fabrication quality. Current maintenance practices often rely on…

FG-CLIP 2: A Bilingual Fine-grained Vision-Language Alignment Model

arXiv:2510.10921v2 Announce Type: replace-cross Abstract: Fine-grained vision-language understanding requires precise alignment between visual content and linguistic descriptions, a capability that remains limited in current models, particularly in non-English settings. While models like CLIP perform well on global alignment, they often…

Online Correlation Clustering: Simultaneously Optimizing All $ell_p$-norms

arXiv:2510.15076v1 Announce Type: new Abstract: The $ell_p$-norm objectives for correlation clustering present a fundamental trade-off between minimizing total disagreements (the $ell_1$-norm) and ensuring fairness to individual nodes (the $ell_infty$-norm). Surprisingly, in the offline setting it is possible to simultaneously approximate…