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Decoupling Wavelet Sub-bands for Single Source Domain Generalization in Fundus Image Segmentation

arXiv:2603.28463v2 Announce Type: replace Abstract: Domain generalization in fundus imaging is challenging due to variations in acquisition conditions across devices and clinical settings. The inabili

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Deep Clustering for Climate: Analyzing Teleconnections through Learned Categorical States

DGX agent

arXiv:2604.22909v1 Announce Type: new Abstract: Understanding and representing complex climate variability is essential for both scientific analysis and predictive modeling. However, identifying meani

researcharxiv-cs-lg

28 Apr 2026

Deep Learning-Enabled Dissolved Oxygen Sensing in Biofouling Environments for Ocean Monitoring

arXiv:2604.24236v1 Announce Type: cross Abstract: The escalating climate crisis and ecosystem degradation demand intelligent, low-cost sensors capable of robust, long-term monitoring in real-world env

Tutorials

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

arXiv:2604.23874v1 Announce Type: cross Abstract: Deep learning approaches have shown remarkable promise in turbulence closure modeling for large eddy simulations (LES). The differentiable physics par

tutorialsarxiv-cs-lg

Tutorials

DeepCausalMMM: A Deep Learning Framework for Marketing Mix Modeling with Causal Structure Learning

arXiv:2510.13087v3 Announce Type: replace Abstract: Marketing Mix Modeling (MMM) estimates the impact of marketing activities on business outcomes such as sales or revenue. Traditional MMM approaches

tutorialsarxiv-cs-lg

DeepImagine: Learning Biomedical Reasoning via Successive Counterfactual Imagining

arXiv:2604.23054v1 Announce Type: cross Abstract: Predicting the outcomes of prospective clinical trials remains a major challenge for large language models. Prior work has shown that both traditional

Local Ai

DeepSignature: Digitally Signed, Content-Encoding Watermarks for Robust and Transparent Image Authentication

arXiv:2604.23016v1 Announce Type: cross Abstract: AI-powered generative models have significantly expanded the possibilities for editing, manipulating, and creating high-quality images. Particularly,

local-aiarxiv-cs-ai

DeepTaxon: An Interpretable Retrieval-Augmented Multimodal Framework for Unified Species Identification and Discovery

model-releasesarxiv-cs-cl

arXiv:2604.24029v1 Announce Type: cross Abstract: Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a

Defective Task Descriptions in LLM-Based Code Generation: Detection and Analysis

arXiv:2604.24703v1 Announce Type: cross Abstract: Large language models are widely used for code generation, yet they rely on an implicit assumption that the task descriptions are sufficiently detaile

Defusing the Trigger: Plug-and-Play Defense for Backdoored LLMs via Tail-Risk Intrinsic Geometric Smoothing

arXiv:2604.24162v1 Announce Type: cross Abstract: Defending against backdoor attacks in large language models remains a critical practical challenge. Existing defenses mitigate these threats but typic

Applications

Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring

arXiv:2511.23036v2 Announce Type: replace-cross Abstract: Explaining online time series monitoring models is crucial across sensitive domains such as healthcare and finance, where temporal and context

applicationsarxiv-cs-ai

Applications

DenoGrad: A Gradient-Based Framework for Data Refinement in Tabular and Time-Series Learning

arXiv:2511.10161v2 Announce Type: replace Abstract: In the Data-Centric Artificial Intelligence (AI) paradigm, improving data quality is essential for robust machine learning. However, many denoising

applicationsarxiv-cs-ai

Deploy DINO with Many-to-Many Association

arXiv:2604.23670v1 Announce Type: new Abstract: Motivated by the limited generalization of supervised image matching models to unseen image domains, we explore the zero-shot deployment of DINO feature

Local Ai

Deployment-Aligned Low-Precision Neural Architecture Search for Spaceborne Edge AI

arXiv:2604.24492v1 Announce Type: cross Abstract: Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, inc

local-aiarxiv-cs-ai

DepthKV: Layer-Dependent KV Cache Pruning for Long-Context LLM Inference

arXiv:2604.24647v1 Announce Type: cross Abstract: Long-context reasoning is a critical capability of large language models (LLMs), enabling applications such as long-document understanding, summarizat

researcharxiv-cs-ai

Designing escalation criteria for international AI incident response: criteria, triggers, and thresholds

arXiv:2604.23183v1 Announce Type: cross Abstract: AI incident reporting requirements are emerging in regulation and policy, yet no operational criteria exist for determining when a detected AI inciden

Designing Instance-Level Sampling Schedules via REINFORCE with James-Stein Shrinkage

arXiv:2511.22177v2 Announce Type: replace-cross Abstract: Most post-training methods for text-to-image samplers focus on model weights: either fine-tuning the backbone for alignment or distilling it f

safetyarxiv-cs-cv

Designing Robots to Support Parent-Child Connections: Opportunities Through Robot-Mediated Communication

arXiv:2604.23976v1 Announce Type: new Abstract: The sense of family connectedness may support positive outcomes including individual well-being, resilience, and healthy family functioning. However, as

researcharxiv-cs-ro

Detecting and Evaluating Medical Hallucinations in Large Vision Language Models

arXiv:2406.10185v2 Announce Type: replace Abstract: Large Vision Language Models (LVLMs) are increasingly integral to healthcare applications, including medical visual question answering and imaging r

DextER: Language-driven Dexterous Grasp Generation with Embodied Reasoning

arXiv:2601.16046v2 Announce Type: replace-cross Abstract: Language-driven dexterous grasp generation requires the models to understand task semantics, 3D geometry, and complex hand-object interactions

safetyarxiv-cs-cv

DGHMesh: A Large-scale Dual-radar mmWave Dataset and Generalization-focused Benchmark for Human Mesh Reconstruction

arXiv:2604.22827v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar has shown great potential for contactless, privacy-preserving, and robust human sensing, yet existing mmWave-based human

Diagnostic-Driven Layer-Wise Compensation for Post-Training Quantization of Encoder-Decoder ASR Models

arXiv:2601.02455v2 Announce Type: replace-cross Abstract: Deploying Automatic Speech Recognition (ASR) models on memory-constrained edge devices requires aggressive low-bit weight quantization. Layer-

researcharxiv-cs-cl

Dialysis Risk Prediction and Treatment Effect Estimation for AKI patients using Longitudinal Electronic Health Records

arXiv:2604.24547v1 Announce Type: new Abstract: Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures infl

researcharxiv-cs-lg

Differentiable Faithfulness Alignment for Cross-Model Circuit Transfer

model-releasesarxiv-cs-cl

arXiv:2604.24302v1 Announce Type: new Abstract: Mechanistic interpretability has made it possible to localize circuits underlying specific behaviors in language models, but existing methods are expens

DiffuSAM: Diffusion-Based Prompt-Free SAM2 for Few-Shot and Source-Free Medical Image Segmentation

arXiv:2604.24719v1 Announce Type: new Abstract: Segmentation models such as Segment Anything Model (SAM) and SAM2 achieve strong prompt-driven zero-shot performance. However, their training on natural

Diffusion-Guided Feature Selection via Nishimori Temperature: Noise-Based Spectral Embedding

arXiv:2604.24692v1 Announce Type: new Abstract: We propose Noise-Based Spectral Embedding (NBSE), a physics-informed framework for selecting informative features from high-dimensional data without gre

researcharxiv-cs-lg

Diffusion Model as a Generalist Segmentation Learner

arXiv:2604.24575v1 Announce Type: new Abstract: Diffusion models are primarily trained for image synthesis, yet their denoising trajectories encode rich, spatially aligned visual priors. In this paper

Diffusion Templates: A Unified Plugin Framework for Controllable Diffusion

arXiv:2604.24351v1 Announce Type: cross Abstract: Controllable diffusion methods have substantially expanded the practical utility of diffusion models, but they are typically developed as isolated, ba

Discovering Agentic Safety Specifications from 1-Bit Danger Signals

arXiv:2604.23210v1 Announce Type: new Abstract: Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for

Discovering Failure Modes in Vision-Language Models using RL

arXiv:2604.04733v2 Announce Type: replace-cross Abstract: Vision-language Models (VLMs), despite achieving strong performance on multimodal benchmarks, often misinterpret straightforward visual concep

Discriminator-Guided Adaptive Diffusion for Source-Free Test-Time Adaptation under Image Corruptions

arXiv:2604.23636v1 Announce Type: new Abstract: In this work, we study Source-Free Unsupervised Domain Adaptation under corruption-induced domain shifts, where performance degradation is caused by nat

Distilling Self-Consistency into Verbal Confidence: A Pre-Registered Negative Result and Post-Hoc Rescue on Gemma 3 4B

arXiv:2604.24070v1 Announce Type: cross Abstract: Small instruct-tuned LLMs produce degenerate verbal confidence under minimal elicitation: ceiling rates above 95%, near-chance Type-2 AUROC, and Inval

DLM: Unified Decision Language Models for Offline Multi-Agent Sequential Decision Making

arXiv:2604.23557v1 Announce Type: cross Abstract: Building scalable and reusable multi-agent decision policies from offline datasets remains a challenge in offline multi-agent reinforcement learning (

DNNs, Dataset Statistics, and Correlation Functions

arXiv:2511.21715v2 Announce Type: replace-cross Abstract: This paper argues that dataset structure is important in image recognition tasks (among other tasks). Specifically, we focus on the nature and

researcharxiv-cs-lg

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models

arXiv:2604.22822v1 Announce Type: cross Abstract: Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verifica

Applications

Do Protective Perturbations Really Protect Portrait Privacy under Real-world Image Transformations?

arXiv:2604.23688v1 Announce Type: new Abstract: Proactive defense methods protect portrait images from unauthorized editing or talking face generation (TFG) by introducing pixel-level protective pertu

applicationsarxiv-cs-cv

Do Quantum Transformers Help? A Systematic VQC Architecture Comparison on Tabular Benchmarks

arXiv:2604.23931v1 Announce Type: cross Abstract: Variational quantum circuits (VQCs) are a leading approach to quantum machine learning on near-term devices, yet it remains unclear which circuit arch

Do Synthetic Trajectories Reflect Real Reward Hacking? A Systematic Study on Monitoring In-the-Wild Hacking in Code Generation

arXiv:2604.23488v1 Announce Type: new Abstract: Reward hacking in code generation, where models exploit evaluation loopholes to obtain full reward without correctly solving the tasks, poses a critical

safetyarxiv-cs-lg

Do Transaction-Level and Actor-Level AML Queues Agree? An Empirical Evaluation of Granularity Effects on the Elliptic++ Graph

arXiv:2604.23494v1 Announce Type: new Abstract: Graph-based anti-money laundering (AML) systems on blockchain networks can score suspicious activity at two granularity levels -- transactions or actor

Does Machine Unlearning Preserve Clinical Safety? A Risk Analysis for Medical Image Classification

arXiv:2604.23854v1 Announce Type: new Abstract: The application of Deep Learning in medical diagnosis must balance patient safety with compliance with data protection regulations. Machine Unlearning e

Tutorials

Doloris: Dual Conditional Diffusion Implicit Bridges with Sparsity Masking Strategy for Unpaired Single-Cell Perturbation Estimation

arXiv:2506.21107v3 Announce Type: replace Abstract: Estimating single-cell responses across various perturbations facilitates the identification of key genes and enhances drug screening, significantly

tutorialsarxiv-cs-lg

Domain-Adapted Fine-Tuning of ECG Foundation Models for Multi-Label Structural Heart Disease Screening

model-releasesarxiv-cs-lg

arXiv:2604.23385v1 Announce Type: new Abstract: Transthoracic echocardiography is the reference standard for confirming structural heart disease (SHD), but first-line screening is limited by cost, wor

Local Ai

Domain-Filtered Knowledge Graphs from Sparse Autoencoder Features

arXiv:2604.23829v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) extract millions of interpretable features from a language model, but flat feature inventories aren't very useful on their ow

local-aiarxiv-cs-ai

Domain Fine-Tuning vs. Retrieval-Augmented Generation for Medical Multiple-Choice Question Answering: A Controlled Comparison at the 4B-Parameter Scale

model-releasesarxiv-cs-cl

arXiv:2604.23801v1 Announce Type: new Abstract: Practitioners deploying small open-weight large language models (LLMs) for medical question answering face a recurring design choice: invest in a domain

Don't Make the LLM Read the Graph: Make the Graph Think

arXiv:2604.23057v1 Announce Type: new Abstract: We investigate whether explicit belief graphs improve LLM performance in cooperative multi-agent reasoning. Through 3,000+ controlled trials across four

Don't Pause! Every prediction matters in a streaming video

arXiv:2604.24317v1 Announce Type: new Abstract: Streaming video models should respond the moment an event unfolds, not after the moment has passed. Yet existing online VideoQA benchmarks remain largel

DPEPO: Diverse Parallel Exploration Policy Optimization for LLM-based Agents

arXiv:2604.24320v1 Announce Type: new Abstract: Large language model (LLM) agents that follow the sequential 'reason-then-act' paradigm have achieved superior performance in many complex tasks.However

safetyarxiv-cs-cl

DPRM: A Plug-in Doob h transform-induced Token-Ordering Module for Diffusion Language Models

arXiv:2604.24357v1 Announce Type: cross Abstract: Diffusion language models generate without a fixed left-to-right order, making token ordering a central algorithmic choice: which tokens should be rev