Search: “applications”

Overcoming the Modality Gap in Context-Aided Forecasting

arXiv:2603.12451v3 Announce Type: replace Abstract: Context-aided forecasting (CAF) holds promise for integrating domain knowledge and forward-looking information, enabling AI systems to surpass tradi

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Physics-informed Active Polarimetric 3D Imaging for Specular Surfaces

DGX agent

arXiv:2602.19470v2 Announce Type: replace Abstract: 3D imaging of specular surfaces remains challenging in real-world scenarios, such as in-line inspection or hand-held scanning, requiring fast and ac

applicationsarxiv-cs-cv

23 Apr 2026

Quantum Adaptive Self-Attention for Quantum Transformer Models

arXiv:2504.05336v3 Announce Type: replace-cross Abstract: Integrating quantum computing into deep learning architectures is a promising but poorly understood endeavor: when does a quantum layer actual

RADS: Reinforcement Learning-Based Sample Selection Improves Transfer Learning in Low-resource and Imbalanced Clinical Settings

arXiv:2604.20256v1 Announce Type: new Abstract: A common strategy in transfer learning is few shot fine-tuning, but its success is highly dependent on the quality of samples selected as training examp

Scalable AI Inference: Performance Analysis and Optimization of AI Model Serving

arXiv:2604.20420v1 Announce Type: cross Abstract: AI research often emphasizes model design and algorithmic performance, while deployment and inference remain comparatively underexplored despite being

Semantic-guided Gaussian Splatting for High-Fidelity Underwater Scene Reconstruction

arXiv:2509.00800v3 Announce Type: replace Abstract: Accurate 3D reconstruction in degraded imaging conditions remains a key challenge in photogrammetry and neural rendering. In underwater environments

Stateless Decision Memory for Enterprise AI Agents

arXiv:2604.20158v1 Announce Type: new Abstract: Enterprise deployment of long-horizon decision agents in regulated domains (underwriting, claims adjudication, tax examination) is dominated by retrieva

Structured Disagreement in Health-Literacy Annotation: Epistemic Stability, Conceptual Difficulty, and Agreement-Stratified Inference

arXiv:2604.19943v1 Announce Type: new Abstract: Annotation pipelines in Natural Language Processing (NLP) commonly assume a single latent ground truth per instance and resolve disagreement through lab

Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech

arXiv:2604.19801v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. Ho

VTouch++: A Multimodal Dataset with Vision-Based Tactile Enhancement for Bimanual Manipulation

arXiv:2604.20444v1 Announce Type: cross Abstract: Embodied intelligence has advanced rapidly in recent years; however, bimanual manipulation-especially in contact-rich tasks remains challenging. This

Wan-Image: Pushing the Boundaries of Generative Visual Intelligence

arXiv:2604.19858v1 Announce Type: new Abstract: We present Wan-Image, a unified visual generation system explicitly engineered to paradigm-shift image generation models from casual synthesizers into p

What Language Models Know But Don't Say: Non-Generative Prior Extraction for Generalization

arXiv:2601.17609v2 Announce Type: replace Abstract: In domains like medicine and finance, large-scale labeled data is costly and often unavailable, leading to models trained on small datasets that str

A Bolu: A Structured Dataset for the Computational Analysis of Sardinian Improvisational Poetry

arXiv:2604.19584v1 Announce Type: new Abstract: The growing interest of Natural Language Processing (NLP) in minority languages has not yet bridged the gap in the preservation of oral linguistic herit

A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities

arXiv:2604.19653v1 Announce Type: new Abstract: Human mobility data are used in numerous applications, ranging from public health to urban planning. Human mobility is inherently sensitive, as it can c

Adaptive MSD-Splitting: Enhancing C4.5 and Random Forests for Skewed Continuous Attributes

arXiv:2604.19722v1 Announce Type: cross Abstract: The discretization of continuous numerical attributes remains a persistent computational bottleneck in the induction of decision trees, particularly a

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Assessing VLM-Driven Semantic-Affordance Inference for Non-Humanoid Robot Morphologies

arXiv:2604.19509v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated remarkable capabilities in understanding human-object interactions, but their application to robotic sys

safetyarxiv-cs-ro

Model Releases

AutomationBench

model-releasesarxiv-cs-ai

arXiv:2604.18934v1 Announce Type: new Abstract: Existing AI benchmarks for software automation rarely combine cross-application coordination, autonomous API discovery, and policy adherence. Real busin

Bayesian Event-Based Model for Disease Subtype and Stage Inference

arXiv:2512.03467v2 Announce Type: replace Abstract: Chronic diseases often progress differently across patients. Rather than randomly varying, there are typically a small number of subtypes for how a

Benign Overfitting in Adversarial Training for Vision Transformers

arXiv:2604.19724v1 Announce Type: cross Abstract: Despite the remarkable success of Vision Transformers (ViTs) across a wide range of vision tasks, recent studies have revealed that they remain vulner

Beyond Coefficients: Forecast-Necessity Testing for Interpretable Causal Discovery in Nonlinear Time-Series Models

arXiv:2604.18751v1 Announce Type: cross Abstract: Nonlinear machine-learning models are increasingly used to discover causal relationships in time-series data, yet the interpretation of their outputs

Budgeted Online Influence Maximization

arXiv:2604.19672v1 Announce Type: new Abstract: We introduce a new budgeted framework for online influence maximization, considering the total cost of an advertising campaign instead of the common car

Conditional Diffusion Modeling with Attention for Probabilistic Battery Capacity Prediction under Real-World Condition

arXiv:2510.17414v2 Announce Type: replace Abstract: Accurate prediction of lithium-ion battery capacity and its associated uncertainty is essential for reliable battery management but remains challeng

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Debiased neural operators for estimating functionals

arXiv:2604.19296v1 Announce Type: new Abstract: Neural operators are widely used to approximate solution maps of complex physical systems. In many applications, however, the goal is not to recover the

safetyarxiv-cs-lg

Design Rules for Extreme-Edge Scientific Computing on AI Engines

arXiv:2604.19106v1 Announce Type: cross Abstract: Extreme-edge scientific applications use machine learning models to analyze sensor data and make real-time decisions. Their stringent latency and thro

Enabling Vibration-Based Gesture Recognition on Everyday Furniture via Energy-Efficient FPGA Implementation of 1D Convolutional Networks

arXiv:2510.23156v2 Announce Type: replace-cross Abstract: The growing demand for smart home interfaces has increased interest in non-intrusive sensing methods like vibration-based gesture recognition.

Evaluating Histogram Matching for Robust Deep learning-Based Grapevine Disease Detection

arXiv:2604.19510v1 Announce Type: new Abstract: Variability in illumination is a primary factor limiting deep learning robustness for field-based plant disease detection. This study evaluates Histogra

Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation

arXiv:2604.19678v1 Announce Type: new Abstract: Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that

FG^2-GDN: Enhancing Long-Context Gated Delta Networks with Doubly Fine-Grained Control

arXiv:2604.19021v1 Announce Type: new Abstract: Linear attention mechanisms have emerged as promising alternatives to softmax attention, offering linear-time complexity during inference. Recent advanc

Formally Verified Patent Analysis via Dependent Type Theory: Machine-Checkable Certificates from a Hybrid AI + Lean 4 Pipeline

arXiv:2604.18882v1 Announce Type: new Abstract: We present a formally verified framework for patent analysis as a hybrid AI + Lean 4 pipeline. The DAG-coverage core (Algorithm 1b) is fully machine-ver

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems

arXiv:2604.19663v1 Announce Type: cross Abstract: Counterfactual explanations (CEs) provide an intuitive way to understand recommender systems by identifying minimal modifications to user-item interac

Graph Data Augmentation with Contrastive Learning on Covariate Distribution Shift

arXiv:2512.00716v2 Announce Type: replace-cross Abstract: Covariate distribution shift occurs when certain structural features present in the test set are absent from the training set. It is a common

Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modeling

arXiv:2604.18753v1 Announce Type: cross Abstract: An active challenge in developing multimodal machine learning (ML) models for healthcare is handling missing modalities during training and deployment

Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning

arXiv:2604.18862v1 Announce Type: cross Abstract: Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bu

IMPACT: Importance-Aware Activation Space Reconstruction

arXiv:2507.03828v4 Announce Type: replace Abstract: Large language models (LLMs) achieve strong performance across diverse domains but remain difficult to deploy in resource-constrained environments d

Implicit Neural Field-Based Process Planning for Multi-Axis Manufacturing: Direct Control over Collision Avoidance and Toolpath Geometry

arXiv:2511.17578v2 Announce Type: replace Abstract: Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a pos

applicationsarxiv-cs-ro

InHabit: Leveraging Image Foundation Models for Scalable 3D Human Placement

arXiv:2604.19673v1 Announce Type: new Abstract: Training embodied agents to understand 3D scenes as humans do requires large-scale data of people meaningfully interacting with diverse environments, ye

Joint Magnetometer-IMU Calibration via Maximum A Posteriori Estimation

arXiv:2505.16662v4 Announce Type: replace Abstract: This paper presents a new method for jointly calibrating a magnetometer and inertial measurement unit (IMU), focusing on balancing calibration accur

applicationsarxiv-cs-ro

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

arXiv:2604.19028v1 Announce Type: new Abstract: One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face

Local Updates in Distributed Optimization: Provable Acceleration and Topology Effects

arXiv:2601.03442v4 Announce Type: replace-cross Abstract: Inspired by the success of performing multiple local optimization steps between communication rounds in federated learning, incorporating such

Position: No Retroactive Cure for Infringement during Training

arXiv:2604.18649v1 Announce Type: cross Abstract: As generative AI faces intensifying legal challenges, the machine learning community has increasingly relied on post-hoc mitigation -- especially mach

PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models

arXiv:2604.19684v1 Announce Type: new Abstract: Explainable artificial intelligence (XAI) has predominantly focused on generating model-centric explanations that approximate the behavior of black-box

Prompt to Pwn: Automated Exploit Generation for Smart Contracts

arXiv:2508.01371v3 Announce Type: replace-cross Abstract: Smart contracts are important for digital finance, yet they are hard to patch once deployed. Prior work has mainly explored LLMs for smart con

Quantum spatial best-arm identification via quantum walks

arXiv:2509.05890v3 Announce Type: replace-cross Abstract: Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to t

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RESFL: An Uncertainty-Aware Framework for Responsible Federated Learning by Balancing Privacy, Fairness and Utility

arXiv:2503.16251v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has gained prominence in machine learning applications across critical domains by enabling collaborative model trainin

safetyarxiv-cs-cv

RoLegalGEC: Legal Domain Grammatical Error Detection and Correction Dataset for Romanian

arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass

S2MAM: Semi-supervised Meta Additive Model for Robust Estimation and Variable Selection

arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke

SAW-INT4: System-Aware 4-Bit KV-Cache Quantization for Real-World LLM Serving

arXiv:2604.19157v1 Announce Type: new Abstract: KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and hi

Seeing Candidates at Scale: Multimodal LLMs for Visual Political Communication on Instagram

arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang