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Decision Boundary-aware Generation for Long-tailed Learning

arXiv:2605.01468v1 Announce Type: new Abstract: Long-tailed data bias decision boundaries toward head classes and degrade tail class accuracy. Diffusion-based generative augmentation address this prob

safetyarxiv-cs-cv

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Decision-Focused Learning via Tangent-Space Projection of Prediction Error

DGX agent

arXiv:2605.01361v1 Announce Type: new Abstract: Decision-Focused Learning (DFL) trains predictors to improve downstream decision quality, but computing regret gradients typically requires differentiat

applicationsarxiv-cs-lg

5 May 2026

Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation

model-releasesarxiv-cs-cl

arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste

Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation

model-releasesarxiv-cs-cv

arXiv:2605.01448v1 Announce Type: cross Abstract: Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge f

Tutorials

Decouple and Cache: KV Cache Construction for Streaming Video Understanding

arXiv:2605.01858v1 Announce Type: new Abstract: Streaming video understanding requires processing unbounded video streams with limited memory and computation, posing two key challenges. First, continu

tutorialsarxiv-cs-cv

Deep learning-based pavement performance modeling using multiple distress indicators and road work history

arXiv:2605.01914v1 Announce Type: new Abstract: The deterioration of pavement is a complex and dynamic process determined by different factors including material, environment, design, and some other u

Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals

arXiv:2605.00849v1 Announce Type: cross Abstract: Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant

Deep neural networks with Fisher vector encoding for medical image classification

model-releasesarxiv-cs-cv

arXiv:2605.01667v1 Announce Type: new Abstract: Orderless encoding methods have shown to improve Convolutional Neural Networks (CNNs) for image classification in the context of limited availability of

Deep Thinking by Markov Chain of Continuous Thoughts

arXiv:2509.25020v2 Announce Type: replace Abstract: Transformer-based models can perform complicated reasoning by generating reasoning paths token by token. While effective, this approach often requir

Deep Time Series Models: A Comprehensive Survey and Benchmark

arXiv:2407.13278v3 Announce Type: replace Abstract: Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other dat

Deep Variational Inference Symbolic Regression

arXiv:2605.01067v1 Announce Type: new Abstract: Symbolic regression discovers explicit, interpretable equations without assuming a functional form in advance. A Bayesian approach strengthens this thro

Deeper detection limits in astronomical imaging using self-supervised spatiotemporal denoising

arXiv:2602.17205v2 Announce Type: replace-cross Abstract: The detection limit of astronomical imaging observations is limited by several noise sources. Some of that noise is correlated between neighbo

researcharxiv-cs-ai

Agents

Deepgram STT is now natively available on @togethercompute. One platform, full voice-agent stack: Deepgram transcription, Together-hosted LL…

Deepgram STT is now natively available on @togethercompute. One platform, full voice-agent stack: Deepgram transcription, Together-hosted LLMs, Aura-2 TTS. Sub-3-second round trip on reference builds.

agentstogether-ai--x

Hardware

Deepinfra lands $107M in funding to build out its dedicated inference cloud for open-source models

Dedicated inference cloud startup Deepinfra Inc. is looking to expand its global capacity after raising 107 million in a Series B round of funding led by 500 Global and Georges Harik, who was one of G

hardwaresiliconangle

DeepSeek v4 works fine, but it’s not the frontier-pressing moment we saw with Kimi 2.6. On Notion eval data, it’s similar performance to GPT…

model-releaseskimi-moonshot--x

DeepSeek v4 works fine, but it’s not the frontier-pressing moment we saw with Kimi 2.6. On Notion eval data, it’s similar performance to GPT 5.2, with understandable failings. Most interesting — it do

DeepStage: Learning Autonomous Defense Policies Against Multi-Stage APT Campaigns

arXiv:2603.16969v2 Announce Type: replace-cross Abstract: This paper presents DeepStage, a deep reinforcement learning (DRL) framework for adaptive and stage-aware defense against Advanced Persistent

safetyarxiv-cs-lg

Tutorials

Degradation-Aware Adaptive Context Gating for Unified Image Restoration

arXiv:2605.01236v1 Announce Type: new Abstract: Unified image restoration using a single model often faces task interference due to diverse degradations. To address this, we propose DACG-IR (Degradati

tutorialsarxiv-cs-cv

Delayed homomorphic reinforcement learning for environments with delayed feedback

arXiv:2604.03641v2 Announce Type: replace Abstract: Reinforcement learning in real-world systems often involves delayed feedback, which breaks the Markov assumption and impedes both learning and contr

safetyarxiv-cs-lg

Hardware

DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning

arXiv:2510.09883v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve state-of-the-art performance on challenging benchmarks by generating long chains of intermediate steps, but th

hardwarearxiv-cs-cl

Democratizing the medieval English legal tradition

model-releasesarxiv-cs-cl

arXiv:2605.00977v1 Announce Type: cross Abstract: The record of the beginning of the most widespread legal system in the world is contained in millions of pages of handwritten text. Most of the record

Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography

arXiv:2605.02245v1 Announce Type: new Abstract: Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep arch

Denoising data using convex relaxations

arXiv:2605.02327v1 Announce Type: cross Abstract: We study the problem of denoising observations (Y_i=X_i+Z_i), where the latent variables (X_i) are sampled from a low-dimensional manifold in (R^n) an

Dependency Parsing Across the Resource Spectrum: Evaluating Architectures on High and Low-Resource Languages

arXiv:2605.02608v1 Announce Type: new Abstract: Transformer-based models achieve state-of-the-art dependency parsing for high-resource languages, yet their advantage over simpler architectures in low-

researcharxiv-cs-cl

Descending into the Modular Bootstrap

arXiv:2604.01275v2 Announce Type: replace-cross Abstract: In this paper, we attempt to explore the landscape of two-dimensional conformal field theories (2d CFTs) by efficiently searching for numerica

Detecting Adversarial Data via Provable Adversarial Noise Amplification

arXiv:2605.02109v1 Announce Type: new Abstract: The nonuniform and growing impact of adversarial noise across the layers of deep neural networks has been used in the literature, without a formal mathe

Developing a Strong Pre-Trained Base Model for Plant Leaf Disease Classification

model-releasesarxiv-cs-cv

arXiv:2605.01283v1 Announce Type: new Abstract: Plants, crops and their yields are essential to our very existence, but diseases and pests cause large losses every year. As such it is vital to ensure

Devin is already delivering real results for enterprise security teams: Devin resolved 70% of Itaú’s backlog of SonarQube, Fortify, and Vera…

applicationscognition-ai--x

Devin is already delivering real results for enterprise security teams: Devin resolved 70% of Itaú’s backlog of SonarQube, Fortify, and Veracode vulnerabilities automatically. Read the case study here

DGS-Net: Distillation-Guided Gradient Surgery for CLIP Fine-Tuning in AI-Generated Image Detection

arXiv:2511.13108v3 Announce Type: replace Abstract: The rapid progress of generative models such as GANs and diffusion models has led to the widespread proliferation of AI-generated images, raising co

Industry

DHS abuses 1930s customs law in attempt to get data on Canadian from Google

The Department of Homeland Security demanded that Google turn over location data and activity logs from a Canadian man who had criticized U.S. government actions following ICE killings, invoking a 'cu

industryars-technica

DIAGRAMS: A Review Framework for Reasoning-Level Attribution in Diagram QA

arXiv:2605.00905v1 Announce Type: new Abstract: Diagram question answering (Diagram QA) requires reasoning-level attribution that links each question-answer pair to all visual regions needed to derive

researcharxiv-cs-cl

Diet Your LLM: Dimension-wise Global Pruning of LLMs via Merging Task-specific Importance Score

arXiv:2603.23985v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable capabilities, but their massive scale poses significant challenges for practical deploymen

Local Ai

Differentiable Kernel Ridge Regression for Deep Learning Pipelines

arXiv:2605.02313v1 Announce Type: new Abstract: Deep neural networks dominate modern machine learning, while alternative function approximators remain comparatively underexplored at scale. In this wor

local-aiarxiv-cs-lg

Differentiable Multiphysics Co-Optimization via Implicit Neural Representations: A Transient Hamburger-Cooking Benchmark

arXiv:2605.01040v1 Announce Type: cross Abstract: The co-optimization of geometry and physical parameters remains challenging in transient multiphysics systems involving moving boundaries, nonlinear m

Differential Parity: Relative Fairness Between Two Sets of Decisions

arXiv:2112.11279v4 Announce Type: replace Abstract: With AI systems widely applied to assist humans in decision-making processes such as talent hiring, school admission, and loan approval; there is an

safetyarxiv-cs-lg

Local Ai

Diffusion Operator Geometry of Feedforward Representations

arXiv:2605.01107v1 Announce Type: new Abstract: Neural networks transform data through learned representations whose geometry affects separation, contraction, and generalization. Recent work studies t

local-aiarxiv-cs-lg

Agents

DigitalOcean raises 2026 and 2027 revenue outlook after AI-driven earnings beat

Shares of DigitalOcean Holdings Inc. rocketed more than 40% today after the developer-oriented cloud infrastructure provider topped Wall Street targets in its fiscal 2026 first quarter. It also lifted

agentssiliconangle

Dimensionality-Aware Anomaly Detection in Learned Representations of Self-Supervised Speech Models

arXiv:2605.02715v1 Announce Type: cross Abstract: Self-supervised speech models (S3Ms) achieve strong downstream performance, yet their learned representations remain poorly understood under natural a

Dino-NestedUNet: Unlocking Foundation Vision Encoders for Pathology Tumor Bulk Segmentation via Dense Decoding

arXiv:2605.00894v1 Announce Type: new Abstract: Vision foundation models (VFMs), such as DINOv3, provide rich semantic representations that are promising for computational pathology. However, many cur

DIPLI: Deep Image Prior Lucky Imaging for Blind Astronomical Image Restoration

arXiv:2503.15984v3 Announce Type: replace Abstract: Modern image restoration and super-resolution methods utilize deep learning due to its superior performance compared to traditional algorithms. Howe

applicationsarxiv-cs-cv

DirectEdit: Step-Level Accurate Inversion for Flow-Based Image Editing

arXiv:2605.02417v1 Announce Type: new Abstract: With recent advancements in large-scale pre-trained text-to-image (T2I) models, training-free image editing methods have demonstrated remarkable success

Disciplined Diffusion: Text-to-Image Diffusion Model against NSFW Generation

arXiv:2605.01113v1 Announce Type: new Abstract: Text-to-image (T2I) diffusion models have the ability to build high-quality pictures from text prompts, but they pose safety concerns because they can g

safetyarxiv-cs-cv

Disentangled Anatomy-Disease Diffusion (DADD) for Controllable Ulcerative Colitis Progression Synthesis

arXiv:2605.01848v1 Announce Type: new Abstract: Synthesizing longitudinal medical images at controllable disease stages while preserving patient-specific anatomy is hindered by the entanglement of pat

Disentangling Fact from Sentiment: A Dynamic Conflict-Consensus Framework for Multimodal Fake News Detection

arXiv:2512.20670v2 Announce Type: replace Abstract: Prevalent multimodal fake news detection relies on consistency-based fusion, yet this paradigm fundamentally misinterprets critical cross-modal disc

Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models

arXiv:2602.00217v2 Announce Type: replace Abstract: Large language models (LLMs) achieve remarkable performance through ever-increasing parameter counts, but scaling incurs steep computational costs.

DissolveStereo: Coarse Depth Injection for Zero-Shot Stereo Video Generation

arXiv:2411.14295v3 Announce Type: replace Abstract: Generating high-quality stereo videos requires consistent depth perception and temporal coherence across frames. Despite advances in image and video

Agents

Distributed Algorithm with Emergent Area Partitioning and Base Station's Situation Awareness for Multi-Robot Patrolling

arXiv:2605.01501v1 Announce Type: new Abstract: Patrolling with multiple robots offers efficient surveillance to detect and manage undesired situations. This necessitates improved patrol efficiency an

agentsarxiv-cs-ro

Distributional Causal Mediation via Conditional Generative Modeling

arXiv:2605.01765v1 Announce Type: cross Abstract: Mediation analysis has traditionally focused on outcome-level summary contrasts, such as mean effects, which may obscure substantial distributional ch

Divergence is Uncertainty: A Closed-Form Posterior Covariance for Flow Matching

arXiv:2605.00941v1 Announce Type: cross Abstract: Flow matching has become a leading framework for generative modeling, but quantifying the uncertainty of its samples remains an open problem. Existing