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Research

Deep Delta Learning

DGX agent

arXiv:2601.00417v3 Announce Type: replace-cross Abstract: Transformer residual streams evolve by additive accumulation: each layer appends a feature update to a shared hidden state, but has no direct

researcharxiv-cs-ai

14 May 2026

Tutorials

Deep Learning as Neural Low-Degree Filtering: A Spectral Theory of Hierarchical Feature Learning

DGX agent

arXiv:2605.13612v1 Announce Type: new Abstract: Understanding how deep neural networks learn useful internal representations from data remains a central open problem in the theory of deep learning. We

All entries

Deep Delta Learning

Deep Learning as Neural Low-Degree Filtering: A Spectral Theory of Hierarchical Feature Learning

DeePen: Penetration Testing for Audio Deepfake Detection

DeepFilters: Scattering-Aware Pupil Engineering with Learned Digital Filter Reconstruction for Extended Depth of Field Microscopy

Delightful Distributed Policy Gradient

Delightful Exploration

Dense vs Sparse Pretraining at Tiny Scale: Active-Parameter vs Total-Parameter Matching

Deontic Argumentation

Descriptive Collision in Sparse Autoencoder Auto-Interpretability: When One Explanation Describes Many Features

Design of Magnetic Continuum Robots with Tunable Force Response Using Rotational Ring Pairs

Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations

Differences in Text Generated by Diffusion and Autoregressive Language Models

Differentiable Evolutionary Reinforcement Learning

Differentiable Learning of Lifted Action Schemas for Classical Planning

Differentially Private Nonparametric Confidence Intervals Under Minimal Distributional Assumptions

DiffST: Spatiotemporal-Aware Diffusion for Real-World Space-Time Video Super-Resolution

Diffusion-Inspired Reconfiguration of Transformers for Uncertainty Calibration

Diffusion Model's Generalization Can Be Characterized by Inductive Biases toward a Data-Dependent Ridge Manifold

DiffusionHijack: Supply-Chain PRNG Backdoor Attack on Diffusion Models and Quantum Random Number Defense

Digital Twins as Synthetic Controls in Single-Arm Trials

DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport

DisaBench: A Participatory Evaluation Framework for Disability Harms in Language Models

DisAgg: Distributed Aggregators for Efficient Secure Aggregation in Federated Learning

DiscoverLLM: From Executing Intents to Discovering Them

Discovery of Hidden Miscalibration Regimes

Discrete Diffusion for Complex and Congested Multi-Agent Path Finding with Sparse Social Attention

Discrete MeanFlow: One-Step Generation via Conditional Transition Kernels

Discrete Stochastic Localization for Non-autoregressive Generation

Distinguishing performance gains from learning when using generative AI

DistractMIA: Black-Box Membership Inference on Vision-Language Models via Semantic Distraction

Distribution Shift in Missing Data Imputation: A Risk-Based Perspective and Importance-Weighted Correction under MAR

Distributionally Robust Safety Under Arbitrary Uncertainties: A Safety Filtering Approach

DIVER:Diving Deeper into Distilled Data via Expressive Semantic Recovery

Diversity of Extensions in Abstract Argumentation

Do Activation Verbalization Methods Convey Privileged Information?

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack

Do Fair Models Reason Fairly? Counterfactual Explanation Consistency for Procedural Fairness in Credit Decisions

Do Heavy Tails Help Diffusion? On the Subtle Trade-off Between Initialization and Training

DocAtlas: Multilingual Document Understanding Across 80+ Languages

Does Engram Do Memory Retrieval in Autoregressive Image Generation?

Does language matter for spoken word classification? A multilingual generative meta-learning approach

Domain Adaptation of Large Language Models for Polymer-Composite Additive Manufacturing Using Retrieval-Augmented Generation and Fine-Tuning

DP-KFC: Data-Free Preconditioning for Privacy-Preserving Deep Learning

DP-Muon: Differentially Private Optimization via Matrix-Orthogonalized Momentum

Drag within Prior Distribution: Text-Conditioned Point-Based Image Editing within Distribution Constraints

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts

Driving Intents Amplify Planning-Oriented Reinforcement Learning

Dual-Pathway Circuits of Object Hallucination in Vision-Language Models