惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

U
Unit 42
V
V2EX
Martin Fowler
Martin Fowler
博客园 - Franky
P
Proofpoint News Feed
P
Palo Alto Networks Blog
H
Hackread – Cybersecurity News, Data Breaches, AI and More
B
Blog
The Register - Security
The Register - Security
Latest news
Latest news
S
Security @ Cisco Blogs
Simon Willison's Weblog
Simon Willison's Weblog
Recorded Future
Recorded Future
大猫的无限游戏
大猫的无限游戏
M
Microsoft Research Blog - Microsoft Research
Scott Helme
Scott Helme
T
Tailwind CSS Blog
cs.CV updates on arXiv.org
cs.CV updates on arXiv.org
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Application and Cybersecurity Blog
Application and Cybersecurity Blog
T
True Tiger Recordings
有赞技术团队
有赞技术团队
I
Intezer
Cisco Talos Blog
Cisco Talos Blog
Hacker News - Newest:
Hacker News - Newest: "LLM"
The GitHub Blog
The GitHub Blog
cs.AI updates on arXiv.org
cs.AI updates on arXiv.org
T
Tenable Blog
博客园 - 叶小钗
Hugging Face - Blog
Hugging Face - Blog
Hacker News: Ask HN
Hacker News: Ask HN
S
Security Archives - TechRepublic
F
Future of Privacy Forum
爱范儿
爱范儿
PCI Perspectives
PCI Perspectives
H
Help Net Security
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
T
The Blog of Author Tim Ferriss
MyScale Blog
MyScale Blog
N
Netflix TechBlog - Medium
罗磊的独立博客
Apple Machine Learning Research
Apple Machine Learning Research
MongoDB | Blog
MongoDB | Blog
Security Latest
Security Latest
美团技术团队
博客园 - 三生石上(FineUI控件)
S
Schneier on Security
量子位
C
CERT Recently Published Vulnerability Notes
SecWiki News
SecWiki News

cs.LG updates on arXiv.org

Harnesses for Inference-Time Alignment over Execution Trajectories CausalGuard: Conformal Inference under Graph Uncertainty ConTact: Contact-First Antibody CDR Design via Explicit Interface Reasoning Representation Gap: Explaining the Unreasonable Effectiveness of Neural Networks from a Geometric Perspective A Reproducible Log-Driven AutoML Framework for Interpretable Pipeline Optimization in Healthcare Risk Prediction Holomorphic Neural ODEs with Kolmogorov-Arnold Networks for Interpretable Discovery of Complex Dynamics Provable Joint Decontamination for Benchmarking Multiple Large Language Models Skill Weaving: Efficient LLM Improvement via Modular Skillpacks Aerodynamic force reconstruction using physics-informed Gaussian processes On-Policy Consistency Training Improves LLM Safety with Minimal Capability Degradation Tailoring Teaching to Aptitude: Direction-Adaptive Self-Distillation for LLM Reasoning PeakFocus: Bridging Peak Localization and Intensity Regression via a Unified Multi-Scale Framework for Electricity Load Forecasting Dynamic Mixture of Latent Memories for Self-Evolving Agents PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation Correcting Class Imbalance in Prior-Data Fitted Networks for Tabular Classification Double descent for least-squares interpolation on contaminated data: A simulation study Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs OPPO: Bayesian Value Recursion for Token-Level Credit Assignment in LLM Reasoning How Many Different Outputs Can a Transformer Generate? No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation Tabular foundation models for robust calibration of near-infrared chemical sensing data TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery Detecting Atypical Clients in Federated Learning via Representation-Level Divergence ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data Short-Term-to-Long-Term Memory Transfer for Knowledge Graphs under Partial Observability Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning ECPO: Evidence-Coupled Policy Optimization for Evidence-Certified Candidate Ranking Engineering Hybrid Physics-Informed Neural Networks for Next-Generation Electricity Systems: A State-of-the-Art Review Symbolic Density Estimation for Discrete Distributions Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents AutoMCU: Feasibility-First MCU Neural Network Customization via LLM-based Multi-Agent Systems Leveraging Self-Paced Curriculum Learning for Enhanced Modality Balance in Multimodal Conversational Emotion Recognition Equilibrium Propagation and Hamiltonian Inference in the Diffusive Fitzhugh-Nagumo Model Objective-Induced Bias and Search Dynamics in Multiobjective Unsupervised Feature Selection Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs I-SAFE: Wasserstein Coherence Metrics for Structural Auditing of Scientific AI Models Machine learning prediction of obstructive coronary artery disease using opportunistic coronary calcium and epicardial fat assessments from CT calcium scoring scans Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation Evaluation of Pipelines for Data Integration into Knowledge Graphs Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics ARC-STAR: Auditable Post-Hoc Correction for PDE Foundation Models TBP-mHC: full expressivity for manifold-constrained hyper connections through transportation polytopes Three Costs of Amortizing Gaussian Process Inference with Neural Processes SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization Bandit Convex Optimization with Gradient Prediction Adaptivity Manifold-Guided Attention Steering Thermodynamic Irreversibility of Training Algorithms What are the Right Symmetries for Formal Theorem Proving? Departure from Regularity: Degree Heterogeneity and Eigengap as the Structural Drivers of ASE-LSE Latent Subspace Disagreement Beyond Scalar Objectives: Expert-Feedback-Driven Autonomous Experimentation for Scientific Discovery at the Nanoscale Cross-domain benchmarks reveal when coordinated AI agents improve scientific inference from partial evidence Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling Ex-GraphRAG: Interpretable Evidence Routing for Graph-Augmented LLMs Predicting Performance of Symbolic and Prompt Programs with Examples DualOptim+: Bridging Shared and Decoupled Optimizer States for Better Machine Unlearning in Large Language Models Beyond Single Slot: Joint Optimization for Multi-Slot Guaranteed Display Advertising How Sparsity Allocation Shapes Label-Free Post-Pruning Recoverability One LR Doesn't Fit All: Heavy-Tail Guided Layerwise Learning Rates for LLMs Graph neural network explanations reveal a topological signature of disease-associated hubs in biological networks Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series Embedding-Based Federated Learning with Runtime Governance for Iron Deficiency Prediction When Are Teacher Tokens Reliable? Position-Weighted On-Policy Self-Distillation for Reasoning $\textit{BlockFormer}$ : Transformer-based inference from interaction maps Expectation Consistency Loss: Rethink Confidence Calibration under Covariate Shift stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning AgForce Enables Antigen-conditioned Generative Antibody Design Models Can Model, But Can't Bind: Structured Grounding in Text-to-Optimization Quantitative coronary calcification analysis for prediction of myocardial ischemia using non-contrast CT calcium scoring One-Way Policy Optimization for Self-Evolving LLMs Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning Toward Understanding Adversarial Distillation: Why Robust Teachers Fail Dropout Universality: Scaling Laws and Optimal Scheduling at the Edge-of-Chaos MMD-Balls as Credal Sets: A PAC-Bayesian Framework for Epistemic Uncertainty in Test-Time Adaptation Noise Schedule Design for Diffusion Models: An Optimal Control Perspective Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions IKNO: Infinite-order Kernel Neural Operators From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability Can Transformers Learn to Verify During Backtracking Search? Visibility nowcasting in South Korea: a machine learning approach to class imbalance and distribution shift Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations Algebraic Machine Learning for Small-to-Medium Datasets Is Competitive against Strong Standard Baselines EmoTrack: Robust Depression Tracking from Counseling Transcripts across Session Regimes When to Switch, Not Just What: Transition Quality Prediction in Clash Royale Provable Robustness against Backdoor Attacks via the Primal-Dual Perspective on Differential Privacy CASE-NET: Deep Spatio-Temporal Representation Learning via Causal Attention and Channel Recalibration for Multivariate Time Series Classification On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents Reinforced Graph of Thoughts: RL-Driven Adaptive Prompting for LLMs Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity Same Architecture, Different Capacity: Optimizer-Induced Spectral Scaling Laws Calibration, Uncertainty Communication, and Deployment Readiness in CKD Risk Prediction: A Framework Evaluation Study Support-aware offline policy selection for advertising marketplaces Alike Parts: A Feature-Informed Approach to Local and Global Prototype Explanations SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection Explainable AI for Data-Driven Design of High-Dimensional Predictive Studies
Automatic Contextual Audio Denoising
Diep Luong, · 2026-05-23 · via cs.LG updates on arXiv.org

View PDF HTML (experimental)

Abstract:Audio context determines which sound components and sources are relevant and which can be perceived as irrelevant (noise) by listeners. For example, traffic noise is informative in urban surveillance but noise for a phone call at the same location. Most current audio denoising systems apply fixed target-noise definitions, often removing useful components in one context while failing to suppress irrelevant components. To address this, we introduce the concept automatic contextual audio denoising (ACAD) which defines target and noise based on the inferred context. In this work, we restrict context to be associated with an acoustic scene class. We label sound events outside the event distribution of a scene class (noise) as out-of-context (OC) and events typical for that scene as in-context (IC). We implement a deep learning method that automatically infers the context of the audio signal and removes OC components, and benchmark it against variants: without context inference, with oracle context, and with separately provided uninformative context. On paired clean/noisy data across diverse contexts, where OC components in one context may be IC in another, our proposed method outperforms other approaches across standard objective metrics, indicating that the model can infer context and context-dependent processing can enhance denoising.
Subjects: Sound (cs.SD); Machine Learning (cs.LG); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2605.22262 [cs.SD]
  (or arXiv:2605.22262v1 [cs.SD] for this version)
  https://doi.org/10.48550/arXiv.2605.22262

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Diep Luong [view email]
[v1] Thu, 21 May 2026 10:06:34 UTC (16,832 KB)