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D3S2: Diffusion-Guided Dataset Distillation for Semantic Segmentation

arXiv:2605.25022v1 Announce Type: cross Abstract: Dataset distillation (DD) aims to compress large-scale datasets into compact synthetic sets while preserving training efficacy. However, existing stud

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Clear filters

Dale meets Langevin: A Multiplicative Denoising Diffusion Model

DGX agent

arXiv:2510.02730v2 Announce Type: replace Abstract: Exponentiated gradient descent (EGD), a biologically motivated optimisation algorithm that respects Dale's law, produces log-normally distributed sy

safetyarxiv-cs-lg

26 May 2026

DarkForest: Less Talk, Higher Accuracy for Multi-Agent LLMs

arXiv:2605.25188v1 Announce Type: new Abstract: Multi-agent LLM systems improve reasoning by combining outputs from multiple agents, but interaction-heavy methods can introduce error propagation and h

Data-Driven Optimization of Tactile Sensor Configurations for Efficient Dexterous Manipulation

arXiv:2409.20473v3 Announce Type: replace Abstract: Tactile sensing is critical for learning-based dexterous manipulation, yet principled guidelines for sensor placement remain largely absent. While d

safetyarxiv-cs-ro

Data-Specific Hyper-Parameter Design: A Paradigm Shift in Reservoir Computing

model-releasesarxiv-cs-lg

arXiv:2605.25221v1 Announce Type: cross Abstract: Reservoir computing typically relies on large, randomly generated reservoirs, enabling simple, often linear readouts. Over the past two decades, most

DBPnet: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Wheel Load Estimation

arXiv:2605.24860v1 Announce Type: cross Abstract: Advanced driver assistance systems (ADAS) play an important role in modern automotive intelligence, significantly enhancing vehicle safety and stabili

Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2605.25393v1 Announce Type: new Abstract: Large Language Models (LLMs) and Multimodal LLMs (MLLMs) have demonstrated immense potential in autonomous driving (AD) by offering human-like reasoning

Agents

Decoding ML Decision: An Agentic Reasoning Framework for Large-Scale Ranking System

arXiv:2602.18640v2 Announce Type: replace Abstract: Modern large-scale ranking systems operate within a sophisticated landscape of competing objectives, operational constraints, and evolving product r

agentsarxiv-cs-ai

Decoding Stimulus Reconstruction-Based Auditory Attention Robustly in Unbalanced EEG Datasets

arXiv:2605.25605v1 Announce Type: cross Abstract: In the past decade, numerous studies have applied deep neural networks (DNNs) to decode auditory attention (AAD) from Electroencephalogram (EEG) signa

Decompose-and-Refine: Structured Legal Question Answering with Parametric Retrieval

model-releasesarxiv-cs-cl

arXiv:2605.24454v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance in the legal domain, demonstrating notable potential in Legal Question Answering (LQA). Howev

Deep Learning-Enabled Prediction of Geoeffective CMEs Using SOHO and SDO Observations

arXiv:2605.24748v1 Announce Type: cross Abstract: Understanding and forecasting the geoeffectiveness of a coronal mass ejection (CME) is crucial for protecting infrastructure in the near-Earth space e

Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting

arXiv:2605.24548v1 Announce Type: new Abstract: Time series driven by unobserved latent states frequently exhibit abrupt jump discontinuities whose timing and magnitude cannot be predicted from observ

DeepEN: A Deep Reinforcement Learning Framework for Personalized Enteral Nutrition in Critical Care

arXiv:2510.08350v3 Announce Type: replace-cross Abstract: Objective: Enteral nutrition (EN) delivery in the ICU remains suboptimal due to limited personalization and uncertainty regarding appropriate

DeepSeekMath Meets Order Book: Group-Aware Policy Optimization for High-Frequency Directional Trading

arXiv:2605.25527v1 Announce Type: new Abstract: This paper studies reinforcement learning for high-frequency trading on limit order books by pairing an Order-Flow-based state model with policy-gradien

DeGRe: Dense-supervised Generative Reranking for Recommendation

arXiv:2605.25749v1 Announce Type: cross Abstract: In multi-stage recommender systems, reranking optimizes overall utility by capturing intra-list contextual dependencies, yet its central challenge lie

Applications

DeIDClinic: A Risk-Aware Pseudonymization Framework for Clinical Text De-identification and Re-identification Risk Assessment

arXiv:2410.01648v2 Announce Type: replace Abstract: The increasing availability of sensitive textual data has created an urgent need for robust de-identification methods that enable compliant data sha

applicationsarxiv-cs-cl

Delayed Assignments in Online Non-Centroid Clustering with Stochastic Arrivals

arXiv:2601.16091v2 Announce Type: replace-cross Abstract: Clustering is a fundamental problem, aiming to partition a set of elements, like agents or data points, into clusters such that elements in th

researcharxiv-cs-ai

Delta Energy: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization

arXiv:2510.11296v3 Announce Type: replace-cross Abstract: Recent approaches for vision-language models (VLMs) have shown remarkable success in achieving fast downstream adaptation. When applied to rea

Agents

DemoEvolve: Overcoming Sparse Feedback in Agentic Harness Evolution with Demonstrations

arXiv:2605.24539v1 Announce Type: new Abstract: Agent harness evolution improves frozen language-model agents by modifying the executable structures around them. We study this paradigm as a form of sa

agentsarxiv-cs-ai

Tutorials

Demystifying the Mythos or Disrupting Bugonomics? From Zero-Day Asymmetry to Defender Remediation Throughput

arXiv:2605.24632v1 Announce Type: cross Abstract: Recent demonstrations of large language models producing candidate and confirmed vulnerabilities in production software have renewed the narrative tha

tutorialsarxiv-cs-ai

Applications

Deploy a Zero-Trust Mesh Network with NetBird on Vultr Marketplace

Deploy secure, encrypted mesh networking in minutes with NetBird on the Vultr Marketplace. Simplify connectivity across distributed infrastructure with WireGuard-powered networking on Vultr’s global c

applicationsvultr

Deployment-complete benchmarking

model-releasesarxiv-cs-lg

arXiv:2605.25997v1 Announce Type: new Abstract: Benchmarks increasingly guide deployment, procurement and scientific screening, yet a score supports only the response it records, not necessarily the d

Design, Control, and Motion Strategy for DELTA: Transformable Multilink Multirotor for Air-Ground Hybrid Locomotion and Manipulation

arXiv:2403.06636v2 Announce Type: replace Abstract: In recent years, multimodal locomotion capabilities have enabled robots to maneuver in both terrestrial and aerial domains. However, most of these r

researcharxiv-cs-ro

Tutorials

Designing Singing Syllabi with Virtual Avatars: AI-Assisted Syllabus Reauthoring

arXiv:2508.11872v3 Announce Type: replace-cross Abstract: Traditional syllabi often function as static reference documents rather than engaging introductions to a course. In practical teaching, we obs

tutorialsarxiv-cs-ai

Agents

Detectify debuts MCP server to let AI agents find and fix vulnerabilities in real time

Application security platform company Detectify AB today launched the Detectify MCP Server, a new integration layer that plugs the company’s security testing engines into artificial intelligence-drive

agentssiliconangle

Detecting Metastable Basins in High Dimensions via Marginal Trajectory Distribution Discrimination

arXiv:2605.24136v1 Announce Type: cross Abstract: We study the problem of identifying dynamically distinct basins of attraction in high dimensional time-homogeneous Markov processes using only traject

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy

arXiv:2605.25603v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves the problem-solving ability of large language models (LLMs), but generated reasoning traces may not faithfully

researcharxiv-cs-ai

Hardware

Develop High-Performance GPU Kernels in C++ with NVIDIA CUDA Tile

This NVIDIA Developer article guides developers on creating optimized GPU kernels using C++ with NVIDIA's CUDA Tile technology, which enables efficient parallel computation on graphics processors. The

hardwarenvidia-developer

Developer productivity is hard to manage.

researchfrancois-chollet--x

Developer productivity is hard to manage. Uber’s COO has said that it’s getting “harder to justify” its AI costs because there was no way to show a link between AI spend and any meaningful increase in

Industry

Did the Pope use AI to write about the dangers of AI?

It's possible that AI was used to write parts of Pope Leo XIV's latest encyclical about AI's impact on humanity. An analysis by Linch Zhang posted on the forum LessWrong found certain paragraphs of Ma

industrythe-verge-ai

Industry

Didit raises $6M funding to build AI-native identity infrastructure

Artificial intelligence-native infrastructure provider for identity and fraud prevention Didit today announced it has raised 6 million in seed funding. New and continuing investors joining the round i

industrysiliconangle

Diff-Instruct with Diffused Reward: Towards Principled One-step Generator RL

arXiv:2605.24001v1 Announce Type: cross Abstract: Recent advances in one-step text-to-image generation have enabled real-time synthesis with remarkable efficiency and quality. Previous reinforcement l

Different Statistical Perspectives for Understanding Generalisation in Graph Neural Networks

arXiv:2605.25452v1 Announce Type: cross Abstract: Graph Neural Networks (GNN) are currently the most popular approach for learning and prediction on graph-structured data and are deployed in various f

Direct Preference Optimization for English-Mandarin Code-Switching Speech Recognition in Audio LLMs

arXiv:2605.23975v1 Announce Type: new Abstract: Audio large language models (Audio LLMs) exhibit systematic failures in transcribing code-switching speech despite strong multilingual capabilities. Foc

safetyarxiv-cs-cl

Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models

model-releasesarxiv-cs-cl

arXiv:2605.25189v1 Announce Type: cross Abstract: Reward hacking arises when a model improves a proxy reward by exploiting shortcuts rather than solving the intended task. We study this failure mode t

Discounted Beta-Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards

arXiv:2603.18444v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective post-training paradigm for improving the reasoning capabilit

Discovering Lexical Gaps Using Embeddings from Multilingual LLMs

arXiv:2605.24310v1 Announce Type: new Abstract: Lexical gaps are words that do not exist in certain languages. They pose challenges for building multilingual lexical resources, for machine translation

safetyarxiv-cs-cl

DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking

model-releasesarxiv-cs-lg

arXiv:2605.26087v1 Announce Type: cross Abstract: Frontier LLMs now perform strongly across a wide range of physics evaluations, but it is hard to disentangle genuine reasoning from recall of establis

Discrete diffusion samplers and bridges: Off-policy algorithms and applications in latent spaces

arXiv:2602.05961v2 Announce Type: replace Abstract: Sampling from a distribution p(x) propto e^{-E(x)} known up to a normalising constant is an important and challenging problem in statistics. Recent

DisDop: Distillation with Domain Priors for Open-Vocabulary Aerial Object Detection

arXiv:2605.24639v1 Announce Type: cross Abstract: With the widespread application of drones in recent years, object detection of aerial images has attracted increasing attention, especially open-vocab

Disentangled Double Machine Learning for Accurate Causal Effect Estimation

arXiv:2605.24808v1 Announce Type: cross Abstract: Confounding bias is a key challenge in causal effect estimation from observational data. Double Machine Learning (DML) addresses this issue by estimat

Distilling Game Code World Model Generation into Lightweight Large Language Models

arXiv:2605.24375v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown great ability in generating executable code from natural language, opening the possibility of automatically cons

Distinguishing Right from Wrong in Debates: Attribution Analysis of Chinese Harmful Memes

arXiv:2605.24344v1 Announce Type: new Abstract: Research on harmful meme detection has garnered significant attention, resulting in the development of numerous datasets and methods. However, progress

researcharxiv-cs-cl

Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction

arXiv:2605.24212v1 Announce Type: cross Abstract: Deploying clinical prediction models across healthcare systems often fails when key training covariates are unavailable at deployment and labeled outc

DIVER-1: Scaling Intracranial EEG Foundation Models for Transferable Representations

arXiv:2512.19097v3 Announce Type: replace-cross Abstract: Intracranial EEG (iEEG) provides direct, millisecond-scale recordings of human neural activity, but reusable representation learning is diffic

Diverse via bounded Agreement: Geometric Regularization for Multimodal Fusion

arXiv:2601.21670v3 Announce Type: replace-cross Abstract: Multimodal fusion is often treated as an optimization-balancing problem, where training signals are adjusted to prevent one modality from domi

Local Ai

Divide-and-Conquer Inference for Large-Scale Visual Recognition with Multimodal Large Language Models

arXiv:2605.24799v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a wide range of vision language tasks. However, when applied to

local-aiarxiv-cs-ai

Do Understanding and Generation Fight? A Diagnostic Study of DPO for Unified Multimodal Models

arXiv:2603.17044v2 Announce Type: replace-cross Abstract: Unified multimodal models share a language model backbone for both understanding and generating images. Can DPO align both capabilities simult