Q-Learning With World Models
arXiv:2608.17163v1 Announce Type: cross Abstract: Off-policy reinforcement learning (RL) has become increasingly sample-efficient, enabling applications such as RL fine-tuning of Vision-Language-Actio
Knowledge catalogue
arXiv:2608.17163v1 Announce Type: cross Abstract: Off-policy reinforcement learning (RL) has become increasingly sample-efficient, enabling applications such as RL fine-tuning of Vision-Language-Actio
arXiv:2608.17598v1 Announce Type: new Abstract: Despite the rapid progress of deep neural networks in visual recognition, their adoption in high-risk medical applications remains limited due to reliab
AI inference infrastructure is becoming a system-level challenge as organizations move generative and agentic applications into production. Graphics processing unit performance remains essential, but
arXiv:2608.17723v1 Announce Type: new Abstract: Analog gauges remain common in industrial environments where manual inspection is costly or hazardous. The engineering application addressed here is dir
arXiv:2608.15195v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) have emerged as a promising approach in medical imaging, producing broadly applicable systems that can be efficiently ad
arXiv:2608.14581v1 Announce Type: cross Abstract: Thermal monitoring in practical applications is often constrained by sparse sensing, measurement noise, and limited spatial resolution, which hinder t
arXiv:2608.14737v1 Announce Type: cross Abstract: This study analyses LLMs in imbalanced binary classification, using study screening in systematic reviews as the application domain. An experiment was
arXiv:2608.14570v1 Announce Type: new Abstract: Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. How
arXiv:2608.16564v1 Announce Type: new Abstract: Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A
arXiv:2603.16959v2 Announce Type: replace-cross Abstract: Exemplified by the chemical vapor deposition growth of two-dimensional dendrites, which has potential applications in catalysis and presents a
arXiv:2608.14655v1 Announce Type: cross Abstract: Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, th
arXiv:2608.14653v1 Announce Type: cross Abstract: Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data sele
arXiv:2608.15084v1 Announce Type: cross Abstract: Test-time augmentation (TTA) has proven effective for improving model robustness and uncertainty estimation in computer vision, yet its application to
arXiv:2607.18483v2 Announce Type: replace-cross Abstract: The digital substrate - data, algorithms, infrastructure, platforms, applications - is being governed without adequate conceptual foundations.
An artificial intelligence startup called Hypercubic Inc. is taking on the problem of modernizing legacy applications written in the COBOL programming language after raising 5.3 million in seed fundin
arXiv:2608.14783v1 Announce Type: new Abstract: Part-aware 3D object generation is essential for graphics applications such as controllable modeling, editing, and articulation, where objects are repre
arXiv:2411.10023v3 Announce Type: replace Abstract: Deep neural networks have enabled numerous studies and applications on both Euclidean data, such as images and text, and non-Euclidean data, such as
arXiv:2505.23594v2 Announce Type: replace-cross Abstract: Multilook coherent imaging is a widely used technique in applications such as digital holography, ultrasound imaging, and synthetic aperture r
arXiv:2608.16442v1 Announce Type: new Abstract: Inspection is a core capability in many mobile robotics applications, including industrial facility monitoring, infrastructure maintenance, agriculture,
arXiv:2608.14951v1 Announce Type: new Abstract: Low-rank matrix decompositions can uncover patterns and structure in data and have a number of different applications across many disciplines. Extension
arXiv:2608.14566v1 Announce Type: new Abstract: Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.e., whet
arXiv:2608.16167v1 Announce Type: cross Abstract: High-precision radio map construction is essential for emerging 6G Integrated Sensing and Communication (ISAC) applications, including digital twins a
arXiv:2608.15784v1 Announce Type: new Abstract: Soft piezoresistive strain sensors are one of the most common sensing solutions for wearable and soft robotic applications due to their flexibility and
arXiv:2603.07571v3 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection is critical in safety-sensitive applications. While this challenge has been addressed from various perspec
arXiv:2608.14161v1 Announce Type: new Abstract: LLMs exhibit social biases that can produce inaccurate and discriminatory inferences, posing risks in high-stakes applications. While prior work has mad
arXiv:2608.14385v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models have been widely adopted in real-time interactive applications such as coding assistants, real-time audio-video intera
arXiv:2502.00023v2 Announce Type: replace-cross Abstract: Our research explores the development and application of musical agents, human-in-the-loop generative AI systems designed to support music per
arXiv:2507.02169v2 Announce Type: replace Abstract: Machine learning models are often used in applications where their inputs change due to routine interactions, strategic manipulation, or noise. In s
arXiv:2607.09816v3 Announce Type: replace Abstract: Class imbalance poses a fundamental challenge in risk-sensitive applications such as fraud detection and medical diagnosis, where minority-class sam
arXiv:2608.13584v1 Announce Type: cross Abstract: UltraArUco - a lightweight multilingual library and framework for low-latency, real-time marker-based tracking in mobile augmented reality. Unlike sta
arXiv:2608.13467v1 Announce Type: new Abstract: We study the Moreau--Yosida unadjusted Langevin algorithm (MYULA) for the nonsmooth composite target [ pi(dx)propto exp{-f(x)-g(x)},dx, qquad xinmathbb
arXiv:2608.12989v1 Announce Type: new Abstract: Pretrained tabular foundation models have demonstrated strong predictive capability; however, their application to large-scale datasets remains constrai
arXiv:2608.13118v1 Announce Type: new Abstract: Verification of neural networks against relational specifications, such as global robustness, is crucial for safety-critical applications of cyber-physi
arXiv:2608.12704v1 Announce Type: cross Abstract: Multi-objective bilevel optimization has wide applications in the AI area such as automated learning and multi-task meta-learning. Although recently s
arXiv:2607.14598v2 Announce Type: replace Abstract: Image registration is essential in applications such as electronic image stabilization. Scale-Invariant Feature Transform (SIFT), a widely used loca
arXiv:2608.12419v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable breakthroughs across various applications. However, their architectures remain inefficient in pret
arXiv:2603.19703v2 Announce Type: replace-cross Abstract: Estimating covariance matrices is fundamental to a wide range of statistical applications. This paper studies minimax and adaptive estimation
arXiv:2603.00048v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes
arXiv:2608.12573v1 Announce Type: new Abstract: Top-k selection is a fundamental computational primitive with applications spanning databases, information retrieval, signal processing, and modern mach
arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model
arXiv:2608.11244v1 Announce Type: new Abstract: Construction standards are critical for building safety and sustainability. Existing standard application workflows rely on keyword-based document retri
arXiv:2608.11422v1 Announce Type: new Abstract: Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imagi
arXiv:2509.24528v4 Announce Type: replace-cross Abstract: Object retrieval from a scene has become a new trend of research due to its numerous applications. Recent approaches achieve zero-shot, open-v
arXiv:2608.11495v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) serve as the backbone for high-stakes applications in Machine-Learning-as-a-Service (MLaaS). Still, their black-box deploym
arXiv:2608.12271v1 Announce Type: new Abstract: Global weather reanalyses and forecasts resolve the evolving atmospheric state on coarse grids, but site-specific applications require predictions at ar
arXiv:2508.09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks po
arXiv:2608.11480v1 Announce Type: cross Abstract: Hamilton-Jacobi (HJ) reachability provides a mathematically rigorous framework for safe control of dynamical systems, but its practical application is
arXiv:2608.12140v1 Announce Type: cross Abstract: Boosted decision trees (BDTs) are widely used in latency-critical applications, but efficient hardware deployment remains challenging. Existing design
arXiv:2608.12185v1 Announce Type: new Abstract: Deep learning models for neuroimaging have largely been developed for individual tasks, limiting knowledge transfer across applications. Here we introdu
arXiv:2608.11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoin
arXiv:2608.11461v1 Announce Type: new Abstract: Rendering haptic feedback with nonlinear virtual environments (VEs) is important in many applications that require highly accurate force feedback. This
arXiv:2608.11655v1 Announce Type: cross Abstract: Motion-centric video reasoning is fundamental to interactive applications such as robotic manipulation and autonomous navigation. However, multimodal
arXiv:2608.11905v1 Announce Type: new Abstract: In many practical applications of generative AI systems, from tax rules to airline baggage allowance, responses to natural language queries must respect
I may have stumbled onto something interesting while trying to figure out a recurring artifact in ChatGPT image generation and editing (maybe applicable to other models as well?). It started with a ve
arXiv:2608.11564v1 Announce Type: new Abstract: Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent stud
arXiv:2105.03358v4 Announce Type: replace-cross Abstract: In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism ena
arXiv:2608.12175v1 Announce Type: new Abstract: Realistic 3D human generation plays a crucial role in many graphics applications. However, current methods still struggle to generate high-quality human
arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A
arXiv:2608.10203v1 Announce Type: new Abstract: Despite the success of convolutional neural networks in image classification tasks and their general application in multi-modal models, their susceptibi
arXiv:2512.06227v3 Announce Type: replace Abstract: Real-world indicators play an important role in many Natural Language Processing (NLP) applications, such as life events for mental health analysis