Search: “applications”

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

2 Oct 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Applications

Multi-Task Anti-Causal Learning for Reconstructing Urban Events from Residents' Reports

DGX agent

arXiv:2603.11546v2 Announce Type: replace Abstract: Many real-world machine learning tasks are anti-causal: they require inferring latent causes from observed effects. In practice, we often face multi

applicationsarxiv-cs-lg

2 Oct 2026

Partial AUC Maximization from Positive-unlabeled Data

arXiv:2610.00284v1 Announce Type: cross Abstract: The partial area under the receiver operating characteristic curve (pAUC) is an important performance metric for binary classification that summarizes

2 Oct 2026

PhysDEM: Physics-Defined Energy-Matching Diffusion for Spatiotemporal Field Generation under Scarce Measurements

arXiv:2610.01759v1 Announce Type: new Abstract: Generating and predicting spatiotemporal physical fields from scarce measurements is challenging, as observations are insufficient to characterize a dis

2 Oct 2026

Model Releases

A2Z GameSpec-Bench: How Faithfully Can Coding Agents Generate Games from Game Design Specifications?

model-releasesarxiv-cs-ai

arXiv:2609.39564v1 Announce Type: new Abstract: Delegating complete application development to coding agents requires preserving the intended design rather than simply producing plausible outputs thro

AdaOcc: Adaptive 3D Occupancy Prediction for Embodied Tasks

arXiv:2609.38864v1 Announce Type: new Abstract: Embodied tasks demand accurate, flexible, and semantically rich 3D scene representations. 3D semantic occupancy is well suited to this requirement, as i

Autoregressive Frontier Expansion: Growing Trees with Graph Machine Learning

arXiv:2609.38506v1 Announce Type: new Abstract: Tree-like branching structures are common in nature, from botanical trees to neurons, blood vessels and respiratory trees. Their branching shape often r

BayesNDE: Bayesian Generative Modeling for Neural Density Estimation

arXiv:2609.39843v1 Announce Type: cross Abstract: Density estimation is a fundamental problem in statistics and machine learning. In this work, we introduce BayesNDE, a neural density estimator based

Conformal Adversarial Generative Ensemble

arXiv:2609.38196v1 Announce Type: cross Abstract: Accurate time series forecasting is critical across various domains, yet traditional ensemble methods often suffer from the disproportionate influence

Data-Driven Priors for Uncertainty-Aware Risk Prediction of Clinical Deterioration using Multimodal Data

arXiv:2603.08459v2 Announce Type: replace Abstract: Safe predictions are a crucial requirement for integrating predictive models into clinical decision support systems. One approach to improving trust

From Benchmarks to Production: Transferring Time Series Anomaly Detection Methods for Electricity Production Monitoring

arXiv:2609.39257v1 Announce Type: cross Abstract: Accurate forecasting of electricity production is essential for maintaining the operational efficiency and strategic planning of energy utilities. In

From Codebase to Culprit (C2C): Reducing the Search Space for Bugs with Semantic Retrieval and Hierarchical Reinforcement Learning

arXiv:2609.38402v1 Announce Type: cross Abstract: We introduce C2C (From Codebase to Culprit), a framework for precise bug localization that progressively reduces the debugging search space across mul

Tutorials

ModSec-Learn: Boosting ModSecurity with Machine Learning

arXiv:2406.13547v2 Announce Type: replace Abstract: ModSecurity is widely recognized as the standard open-source Web Application Firewall (WAF), maintained by the OWASP Foundation. It detects maliciou

tutorialsarxiv-cs-lg

Beyond Conditional Independence: Root Cause Analysis with Deep Causal Models

arXiv:2609.36771v1 Announce Type: cross Abstract: Root cause analysis (RCA) is a critical problem in many real-world scenarios. RCA enables the identification of faulty or failing mechanisms in a syst

Devils in Question Relay: Source-Conditioned Relay Steering to Mitigate Hallucinations in Audio-visual Large Language Models

arXiv:2609.37568v1 Announce Type: new Abstract: Audio-visual large language models (AVLLMs) have made remarkable progress in multimodal understanding and reasoning through interactions among visual, a

applicationsarxiv-cs-cl

Efficient Audiovisual Speech Processing via MUTUD: Multimodal Training and Unimodal Deployment

arXiv:2501.18157v2 Announce Type: replace-cross Abstract: Building reliable speech systems often requires combining multiple modalities, like audio and visual cues. While such multimodal solutions fre

Neural topology optimization of ship structures under propulsion machinery vibrations

arXiv:2609.38089v1 Announce Type: cross Abstract: Ship structural vibrations contribute to noise, fatigue, and equipment damage, while dynamic-compliance topology optimization can produce pathological

Phaedra: Learning High-Fidelity Discrete Tokenization for the Physical Science

arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be

Pixel-Level Transformers in Remote Sensing: A Canopy Height Case Study

arXiv:2609.37809v1 Announce Type: cross Abstract: Predicting canopy height from medium-resolution satellite imagery is a common and scalable approach for assessing the condition of the world's forests

RecKG: Knowledge Graph for Recommender Systems

arXiv:2501.03598v2 Announce Type: replace-cross Abstract: Knowledge graphs have proven successful in integrating heterogeneous data across various domains. However, there remains a noticeable dearth o

Adaptive Weighted h-Transform Sampling for Coarse-Guided Visual Generation

arXiv:2603.12057v3 Announce Type: replace Abstract: Coarse-guided visual generation, which synthesizes fine visual samples from degraded or low-fidelity coarse references, is essential for various rea

ENet-GP: Unified Document Image Restoration

arXiv:2609.33758v1 Announce Type: new Abstract: Reliable document digitization in uncontrolled capture settings is challenging because real images exhibit multiple interacting degradations rather than

FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge

HAGI++: Head-Assisted Gaze Imputation and Generation

arXiv:2511.02468v2 Announce Type: replace-cross Abstract: Mobile eye-tracking is crucial for capturing human visual attention in real-world and XR settings, supporting research and human-computer inte

Multi-Terrain Mastery: A Comprehensive Controller for Bipedal Locomotion

arXiv:2609.33174v1 Announce Type: new Abstract: Advancing bipedal robots to navigate diverse terrains remains a significant challenge in robotics. Traditional locomotion controllers excel on specific

applicationsarxiv-cs-ro

Recent Advances in Medical Imaging Segmentation: A Survey

arXiv:2505.09274v2 Announce Type: replace Abstract: Medical imaging is a cornerstone of modern healthcare, driving advancements in diagnosis, treatment planning, and patient care. Among its various ta

T-MoXAI: A Hierarchical Explainability Framework for Temporal Multimodal Data

arXiv:2609.33685v1 Announce Type: new Abstract: Artificial Intelligence (AI) models for temporal multimodal data have potential in healthcare and agriculture, but their opacity can limit trust and ado

Transfer Calibrated Prediction Powered Inference

arXiv:2609.34156v1 Announce Type: new Abstract: Prediction-powered inference (PPI) and its power-tuned extension (PPI++) improve confidence intervals by combining a small gold-standard labeled sample

Video Captioning in Low-Light Conditions through Efficient Uncertainty-Aware Caption Correction

arXiv:2609.31697v1 Announce Type: new Abstract: Low-light conditions can significantly degrade the ability of vision-language models (VLMs) to accurately describe human actions in videos. In this work

Adapting Visualization Techniques for Time-Series Anomaly Detection: From Convolutional Neural Networks to Convolutional-Recurrent Neural Networks

arXiv:2411.04707v4 Announce Type: replace Abstract: Deep neural networks achieve strong performance on complex tasks but are often regarded as 'black boxes,' which limits their adoption in domains whe

28 Sept 2026

Provable Speech Attributes Conversion via Latent Independence

arXiv:2510.05191v3 Announce Type: replace-cross Abstract: Conditional generation and disentangled representation learning are central to controlled generation across audio, vision, and multimodal doma

28 Sept 2026

Agents

On the Effectiveness of Kernel-Level Evidence for Agent Security

arXiv:2609.28915v1 Announce Type: cross Abstract: LLM agents are deployed into infrastructure that grants them broad host authority, yet existing agent-security benchmarks and defenses operate almost

agentsarxiv-cs-ai

25 Sept 2026

Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data

arXiv:2505.15465v2 Announce Type: replace Abstract: This paper introduces Synthetic Enclosed Echoes (SEE), a novel dataset designed to enhance robot perception and 3D reconstruction capabilities in un

applicationsarxiv-cs-ro

25 Sept 2026

A Resilience Recovery Method for Complex Traffic Network Security Based on Trend Forecasting

arXiv:2609.27903v1 Announce Type: new Abstract: Due to the rapid development of information technology, a huge and complex traffic network has been established across various sectors, including aviati

A Sample-Based Approach for Hierarchical Information-Theoretic Compression of Probabilistic Occupancy Grids

arXiv:2609.27330v1 Announce Type: new Abstract: We develop a sample-based framework for constructing information-driven hierarchical multi-resolution representations of probabilistic occupancy grids.

applicationsarxiv-cs-ro

Data-driven discrete-time deep recurrent neural network-based modeling for dissipative systems

arXiv:2609.27186v1 Announce Type: new Abstract: Physical AI has gained increasing attention for its role in developing AI systems that better understand, predict, and control real-world dynamics. Achi

InsurTech innovation using natural language processing

arXiv:2507.21112v4 Announce Type: replace Abstract: With the rapid rise of InsurTech, traditional insurance companies are increasingly exploring alternative data sources and advanced technologies to s

applicationsarxiv-cs-cl

NeuroRule: Making Black-Box Neural Networks Explainable through Rule-set Evolution

arXiv:2609.26841v1 Announce Type: cross Abstract: High-capacity neural network models have achieved state-of-the-art performance across diverse classification tasks, yet they frequently operate as bla

RoomLight: A 2.5D Illumination Prior for Indoor Environments

arXiv:2609.28300v1 Announce Type: new Abstract: Ill-posed inverse problems require priors to constrain the solution space toward plausible outcomes. In inverse rendering, learned priors modeling the d

Untangling the Geometry and Speed for RF Sensing Spectrograms

arXiv:2609.26960v1 Announce Type: cross Abstract: A fundamental challenge in RF sensing is that Doppler signatures observed by a link entangle the target's motion with the sensing geometry, resulting

ZoomDiff: A High-Fidelity Diffusion Model for Dual-Camera Smooth Zooming

arXiv:2609.28083v1 Announce Type: new Abstract: Digital zoom transitions between dual cameras often exhibit conspicuous discontinuities in geometric structure and chromatic consistency, degrading the

BDSLI: A hybrid CNN-Transformer model for Bengali Sign Language interpretation

arXiv:2609.26088v1 Announce Type: new Abstract: This study introduces a novel hybrid CNN-Transformer architecture to address the limited progress in Bengali SLR, focusing on isolated sign word recogni

Graph-Based Inference for Feedback-Driven Word Deduction: A Scalable Framework for the Jotto Problem

arXiv:2609.25056v1 Announce Type: new Abstract: A feedback-based word deduction framework based on the Jotto problem is proposed, and the problem space is represented as a weighted graph where all val

applicationsarxiv-cs-cl

Laryngeal Structure Segmentation in High-Speed Videoendoscopy Using Deep Learning

arXiv:2609.26636v1 Announce Type: new Abstract: Laryngeal high-speed videoendoscopy (HSV) offers an effective means of observing the motion of different laryngeal structures along with vibratory behav

Marginal Log-Likelihood Increments under Dirichlet-Smoothed Markov Estimation

arXiv:2609.25675v1 Announce Type: new Abstract: For a Dirichlet-smoothed transition model, the effect of adding one workflow trace to the training archive is an exact change in reference-weighted log

Memory-Free Continual Learning with Null Space Adaptation for Zero-Shot Vision-Language Models

arXiv:2510.21175v2 Announce Type: replace Abstract: Pre-trained vision-language models (VLMs), such as CLIP, have demonstrated remarkable zero-shot generalization, enabling deployment in a wide range

Quantum Model Parallelism for MRI-Based Classification of Alzheimer's Disease Stages

arXiv:2602.00128v2 Announce Type: replace Abstract: With increasing life expectancy, AD has become a major global health concern. While classical AI-based methods have been developed for early diagnos

Robust Photoplethysmography Signal Denoising via Mamba Networks

arXiv:2510.11058v2 Announce Type: replace Abstract: Photoplethysmography (PPG) is widely used in wearable health monitoring, but its reliability is often degraded by noise and motion artifacts, limiti