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3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Latest papers 23

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Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios
Sep 28, 2026Kelvin J. L. Koa, Xinyang Li, Ke-Wei HuangPortfolio Optimization Stochastic Differential Equations
National University of Singapore Asian Institute of Digital Finance
Psychoacoustically Aligned Latent Smoothing for Adversarial Robustness of Full-Duplex Speech-to-Speech Dialogue Models
Sep 23, 2026Kian Shamsaie, Iman ModarressiFull-Duplex Speech Models Hijacking
People Make Things
Almost Sure Convergence Analysis of Stochastic Gradient Methods with Clipping and Additive Noise
Sep 10, 2026Amartya Mukherjee, Jun LiuStochastic Gradient Descent Gradient Clipping
Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1
Constrained Online Learning with Noisy Constraint Values
Sep 7, 2026Vaneet Aggarwal\Widetilde{\Mathcal{O}}(\Sqrt{T})$ Regret Learning-Augmented Algorithms
Purdue University
Fidelity-Constrained Anchoring for Black-Box Denoisers
Aug 13, 2026Masaki SatohIterative Denoising Methods Gaussian Noise
Morpho, Inc. Tokyo, Japan
Test-Time Noise Guided Adaptation for Realistic Autoregressive Video Generation
Jul 17, 2026Dimitrios Karageorgiou, Symeon Papadopoulos, Ioannis Kompatsiaris +1Autoregressive Video Diffusion Models Autoregressive Video Generation
Information Technologies Institute, CERTH, Thessaloniki, Greece · University of Amsterdam, Amsterdam, The Netherlands
Compression Asymmetry and Trajectory Binding in Noise-Anchored Diffusion Inversion
Jul 8, 2026Yongseong Park, Joeun Kim, HoEun Kim +1Diffusion Inversion Inverse Design
Department of EECS DGIST Daegu, Republic of Korea · Department of AI DGIST Daegu, Republic of Korea
Fuzzing Large Language Models to Elicit Hidden Behaviours
Jun 28, 2026Mohammed Abu Baker, Lakshmi Babu-SaheerFuzzing Elicitation
School of Computing and Information Science Anglia Ruskin University
Denoising ICF Images with Multiplicative Uniform Noise: A Self-Supervised Study Based on the Log-Domain Noisier2Inverse Framework
Jun 26, 2026Gyeongha Hwang, Bradley Thomas Wolfe, Naima NaheedMultiplicative Gamma Noise Gaussian Noise
Department of Mathematics, Yeungnam University, Gyeongsan, Republic of Korea. · Research Technologist, P-4: Thermonuclear Plasma Physics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. · Department of Computer Science and Engineering, Benedict College, Columbia, SC 29204, USA.
The Third Challenge on Image Denoising at NTIRE 2026: Methods and Results
Jun 14, 2026Lei Sun, Hang Guo, Bin Ren +6Image Restoration Iterative Denoising Methods
INSAIT, Sofia University, “St. Kliment Ohridski”
Simplicity Suffices for Parameter Noise Injection in Stochastic Gradient Descent
Jun 10, 2026Benjamin Leblanc, Louis-Jacob Lebel, Teddy Kana +1Stochastic Gradient Descent Gaussian Noise
Universit´e Laval
DPDL: Towards Differential Privacy Preservation in Decentralized Stochastic Learning on Non-IID Data
Jun 3, 2026Yunsheng Yuan, Xue Xiao, Lina Wang +1Decentralized Learning Standard Differential-Privacy
School of Computer Science and Technology, Shandong University, Qingdao 266237, China · Inspur Cloud Information Technology Co, Ltd.
A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs
Jun 1, 2026Nicolas Stalder, Benjamin F. Grewe, Matteo Saponati +1Convolutional Neural Networks Noise-Aware
Institute of Neuroinformatics
When Determinants Are Not Enough: Private Rare Switching
May 22, 2026Xingyu ZhouSwitch Boltzmann Policies
Wayne State University, Detroit, USA.
Cascade-KDE: Robust Time-Series Restoration under Out-of-Distribution Impulse Corruptions
May 22, 2026Yuefeng Liu, Ning Yang, Ziyu YangOutliers Image Restoration
School of Digital and Intelligent Industry (School of Cyber Science and Technology), Inner Mongolia University of Science and Technology, Baotou, China
Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise
May 14, 2026Antesh Upadhyay, Arda Fazla, Abolfazl HashemiStochastic Convex Optimization Stochastic Gradient Descent
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training
May 13, 2026Hamza Cherkaoui, Hélène Halconruy, Antonio OcelloLong-Tailed Distribution Diffusion Models
SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris, Palaiseau, France · Modal’X, Université Paris Nanterre, Nanterre, France · CREST, ENSAE Paris, Institut Polytechnique de Paris, Palaiseau, France
Couple to Control: Joint Initial Noise Design in Diffusion Models
May 11, 2026Jing Jia, Liyue Shen, Guanyang WangDiffusion Models Gaussian Noise
Department of Computer Science Rutgers University Piscataway, NJ 08854 · Department of EECS University of Michigan Ann Arbor, MI 48109 · Department of Statistics Rutgers University Piscataway, NJ 08854
Colorful-Noise: Training-Free Low-Frequency Noise Manipulation for Color-Based Conditional Image Generation
May 1, 2026Nadav Z. Cohen, Ofir Abramovich, Ariel ShamirText-To-Image Diffusion Models Diffusion Models
Reichman University, Israel
Super-resolution Multi-signal Direction-of-Arrival Estimation by Hankel-structured Sensing and Decomposition
Apr 29, 2026Georgios I. Orfanidis, Dimitris A. Pados, George Sklivanitis +1Microphone Array Spectral Norm
Center for Connected Autonomy and AI and the Dept. of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL 33431 USA · Air Force Research Laboratory, AFRL/RI, Rome, NY 13441 USA
Language models recognize dropout and Gaussian noise applied to their activations
Apr 19, 2026Damiano Fornasiere, Mirko Bronzi, Spencer Kitts +3Model Activations Dropout
LawZero
Efficient Conformal Prediction for Regression Models under Label Noise
Sep 18, 2025Yahav Cohen, Jacob Goldberger, Tom TirerOnline Conformal Prediction Confidence Intervals
Faculty of Engineering Bar-Ilan University Ramat Gan, Israel
Probabilistic Analysis of Least Squares, Orthogonal Projection, and QR Factorization Algorithms Subject to Gaussian Noise
Sep 27, 2024Ali Lotfi, Julien Langou, Mohammad MeysamiSpectral Norm Singular Value Decomposition
Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5A2, Canada · Department of Applied Mathematics, University of Colorado Denver, Denver, Colorado2026 80201, USA · Department of Mathematics, The University of Tulsa, Tulsa, OK 74104, USA

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Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

Kelvin J. L. Koa, Xinyang Li, Ke-Wei Huang

National University of Singapore Asian Institute of Digital Finance

Portfolio Optimization Stochastic Differential Equations Gaussian Noise Factor

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In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture the underlying risk structures of financial data. This is challenging due to several factors: financial markets exhibit non-stationary dynamics with shifting regimes, multimodal inputs such as price and news data often contain stochastic noise, and existing diffusion-based approaches, while effective for modeling stochastic dynamics, rely on assumptions such as isotropic Gaussian noise that fail to capture the state-dependent nature of financial uncertainty. To address these challenges, we introduce RADAR, a retrieval-augmented diffusion framework that learns market representations by conditioning on similar historical regimes. RADAR leverages retrieval to construct context-dependent noise distributions, applies conditional diffusion to denoise multimodal representations, and initializes the diffusion process using empirical statistics to reflect state-dependent uncertainty. Experiments show that RADAR achieves state-of-the-art performance on key risk-adjusted metrics while producing economically meaningful signals on asset returns and correlations.

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