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Data-Free Continual Learning for World Action Model with Rectified Generative Replay

arXiv:2610.18038v1 Announce Type: cross Abstract: World action models (WAMs) built on pretrained video generation models adapt quickly to new robotic tasks, but they forget previously learned tasks un

safetyarxiv-cs-cv

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Data Free Training of Diffusion Models for Lattice Field Theories

DGX agent

arXiv:2610.18863v1 Announce Type: cross Abstract: Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative s

model-releasesarxiv-cs-lg

14 Oct 2026

Data-Topology Compatibility Enables Personalization in Decentralized Learning

arXiv:2610.15126v1 Announce Type: cross Abstract: Decentralized learning must balance collaboration with personalization across heterogeneous agents. This paper studies when cooperation can support st

Agents

Davinci-Tool: Scaling Agentic Tool-Use Supervision with Verifiable Executable Environments

arXiv:2610.16867v1 Announce Type: new Abstract: Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achiev

agentsarxiv-cs-lg

DC-Flow: Target-Conditioned Cyclic Peptide Design via Delayed-Coupling Flow Matching

arXiv:2610.15391v1 Announce Type: new Abstract: Target-conditioned cyclic peptide design requires coordinating interfacial side chains with macrocyclic closure. Existing end-to-end generators concurre

DDVR-Net: Degradation-Aware Decoupling and Visibility-Guided Restoration for Historical Document Recognition

model-releasesarxiv-cs-cv

arXiv:2610.16956v1 Announce Type: new Abstract: Historical document analysis is crucial for cultural heritage preservation and low-resource language digitization. However, real historical documents of

Decentralized Bandit Learning of Markov Perfect Equilibria

arXiv:2610.14333v1 Announce Type: new Abstract: We study decentralized bandit learning in discounted infinite-horizon, general-sum Markov games with continuous actions. Agents observe the public state

Agents

Declarative Reactive Robot Behaviors from Imperative Language Models

arXiv:2610.17083v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly trained on imperative programming languages, and existing work on LLM-based robot programming reflects th

agentsarxiv-cs-ro

Decomposing A Neural Learner

arXiv:2610.14388v1 Announce Type: cross Abstract: Neural learners for classification and regression are often criticized as black boxes. We propose a probabilistic decomposition of neural learners tha

tutorialsarxiv-cs-lg

Decoupling Knowledge Forgetting and Refusal Learning in MLLM Unlearning

arXiv:2610.14605v1 Announce Type: cross Abstract: Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information. This surface-level criterion, how

Deep Jump Gaussian Processes for Surrogate Modeling of High-Dimensional Piecewise Continuous Functions

arXiv:2510.21974v3 Announce Type: replace Abstract: We introduce Deep Jump Gaussian Processes (DJGP), a novel method for surrogate modeling of a piecewise continuous function on a high-dimensional dom

Deep Learning and Elicitability for McKean-Vlasov FBSDEs With Common Noise

arXiv:2512.14967v3 Announce Type: replace Abstract: We present a novel numerical method for solving McKean-Vlasov forward-backward stochastic differential equations (MV--FBSDEs) with common noise, com

Deep Learning-based Mechanical Characterization of Synthetically Generated Plant Fibers under Transverse Compression

arXiv:2610.16529v1 Announce Type: new Abstract: Plant fibers are increasingly used as sustainable reinforcements in composites, but the intrinsic variability of their microstructure causes substantial

tutorialsarxiv-cs-cv

Deep Learning-based Semantic Segmentation of Dental Radiographs: Comparative Evaluation of PSPNet, DeepLabv3, UNet, and UNet++

arXiv:2610.15061v1 Announce Type: new Abstract: Accurate and efficient analysis of dental radiographs has become increasingly important for disease diagnosis and clinical decision making. In particula

Deep learning from a control vantage point

arXiv:2610.14385v1 Announce Type: cross Abstract: This article offers an overview of recent developments in deep learning from a control vantage point. It reviews several classes of models including f

Deep learning methods for gamma event selection in TAIGA-IACT image analysis in stereo-mode

arXiv:2610.16269v1 Announce Type: cross Abstract: In astrophysical complex TAIGA there are four Imaging Atmospheric Cherenkov telescopes (IACTs), located at a distance of 300-500 m from each other, du

Deep Mesoscopic Dynamics

arXiv:2610.17885v1 Announce Type: new Abstract: Microscopic simulations resolve spatial patterns but are feasible only over small domains and short timescales, whereas bulk descriptions erase those pa

tutorialsarxiv-cs-lg

Deep Neural Mixed Models for Nonlinear Longitudinal Prediction with Subject-Specific Heterogeneity

arXiv:2610.15323v1 Announce Type: cross Abstract: Longitudinal health data often exhibit within-subject correlation, subject-specific heterogeneity, and complex nonlinear predictor--response relations

tutorialsarxiv-cs-lg

Deep Speech Representations Track Word Timing along a Low-Dimensional Circular Trajectory

arXiv:2610.16273v1 Announce Type: cross Abstract: Speech timing is fundamental for speech models to recognize words accurately, but how word-timing information is represented in speech models remains

DeepFlow: Two Convergent Differentiable Approaches for Pairwise Conditional Random Fields

arXiv:2610.16546v1 Announce Type: new Abstract: Basic probabilistic models form the basis of modern deep learning largely by defining the final activation layer of a network and allowing the networks

Deeply unrolled alternating projections for phase retrieval

arXiv:2610.17316v1 Announce Type: cross Abstract: Deep unrolling methods for inverse problems augment traditional reconstruction algorithms with learned priors to improve their performance. These meth

Deficit-Driven Stratified Acquisition for Building STRATA-S12: An Open SAR-Optical Corpus for Self-Supervised Learning

model-releasesarxiv-cs-cv

arXiv:2610.17680v1 Announce Type: cross Abstract: Building a co-registered SAR-optical corpus for self-supervised Earth Observation is above all an acquisition problem, yet the main multi-modal datase

DEFlow: Deep Equilibrium Flow Maximum-Entropy Reinforcement Learning

arXiv:2610.16597v1 Announce Type: new Abstract: Expressive flow policies can represent multiple high-value actions, but sampling them with few integration steps while retaining tractable action densit

safetyarxiv-cs-lg

DEFT: Disentanglement-Enhanced Fine-Tuning for EEG Foundation Models

arXiv:2610.14497v1 Announce Type: new Abstract: EEG foundation models (EFMs) have improved EEG representation learning by transferring knowledge from large-scale multi-subject pretraining to downstrea

DEFT-VLA: Stage-Localized Force Specialization for Contact-Rich Robotic Manipulation

arXiv:2610.14854v1 Announce Type: new Abstract: Contact-rich manipulation poses a stage-dependent sensory conflict: vision and proprioception are essential for localization and approach, when force is

researcharxiv-cs-ro

Degrees of Freedom in Multi-Agent Coordination: Between Centralized and Decentralized Regimes

arXiv:2610.17751v1 Announce Type: cross Abstract: Large language model (LLM)-based multi-agent systems (MAS) are commonly organized around two coordination regimes. Centralized coordination provides e

DeKoR: Decomposed Knowledge Routing for Efficient GNN--LLM Fusion

arXiv:2610.14710v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for text-attributed graph learning by leveraging rich pre-trained knowledge and language unders

Delta Flow Matching for Robot Foundation Models

arXiv:2610.15794v1 Announce Type: new Abstract: Flow matching is a common generative recipe for robot foundation models. Vision-language-action models (VLAs) generate action chunks, while world-action

safetyarxiv-cs-ro

DeltaNet-PC: Test-Time Memory Without Backpropagation Through Time

arXiv:2610.15185v1 Announce Type: new Abstract: Test-time memorization of sequential information is a foundational capability for any intelligent system that needs to rapidly store and retrieve data,

DeltaTTG: Training Multi-Turn Agents with a Token-to-Go Progress Meter

arXiv:2610.17666v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) for multi-turn agents relies on sparse terminal rewards that say little about individual steps. Wi

Demiurge: Forging Navigable 4D Worlds via Autoregressive Video Rerendering

arXiv:2610.14685v1 Announce Type: new Abstract: Recent advances in video diffusion enable novel-view video synthesis from a single input video, supporting world modeling, embodied intelligence, and ro

Demystifying Hidden-State Recurrence: Switchable Latent Reasoning with On-Policy Reinforcement Learning

arXiv:2606.13106v2 Announce Type: replace Abstract: Latent chain-of-thought compresses reasoning through continuous hidden-state recurrence, but existing approaches are difficult to optimize with stan

Hardware

Denoise X: Self-Supervised U-Net for Quantum Mottle Suppression in Chest Radiography

arXiv:2610.18556v1 Announce Type: new Abstract: Deep learning for medical image restoration is often constrained by the need for paired training data. Acquiring perfectly registered clean-noisy radiog

hardwarearxiv-cs-cv

Dense Endoluminal Mapping and Localisation from Monocular Bronchoscopy

arXiv:2610.16570v1 Announce Type: new Abstract: Bronchoscopy inserts a camera through the airways to diagnose endoluminal disease. Locating the camera along the airway usually requires additional equi

Density-Matrix Reinforcement Learning

arXiv:2610.17214v1 Announce Type: new Abstract: What information does a reinforcement learning policy omit? At each state, a standard policy stores one probability per action. It has no place to recor

safetyarxiv-cs-lg

Dependency, Compression, and Synergy: A Unified Information-Theoretic View of Multimodal Learning

arXiv:2609.14421v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models have intensified the need to understand how different modalities share, preserve, and complement infor

Dependency Reasoning for Aspect Sentiment Quadruple Prediction

arXiv:2610.14873v1 Announce Type: cross Abstract: Aspect Sentiment Quadruple Prediction (ASQP) is fundamentally a relational reasoning problem: identifying aspect-opinion-category-sentiment quadruples

Deploy and evaluate models with Amazon SageMaker JumpStart

Learn how to deploy an available model from Amazon SageMaker JumpStart, run a lightweight and repeatable performance test using the SageMaker Python SDK, and delete the endpoint when testing is comple

tutorialsaws-ml-blog

Depth Memory

arXiv:2610.18809v1 Announce Type: new Abstract: Residual connections propagate information through a network by additively accumulating layer outputs. Recently proposed alternatives, such as Manifold-

DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment

model-releasesarxiv-cs-cv

arXiv:2610.16278v1 Announce Type: new Abstract: Existing-image self-tiling aims to transform a given image into a seamlessly repeatable tile while preserving its original semantics and local details.

Design and Analysis of a Nonlinear Parallel Mechanism Coupling for Dynamic Humanoid Legs

arXiv:2610.16604v1 Announce Type: new Abstract: Humanoids increasingly demand lightweight leg mechanisms for agile, dynamic, and energy-efficient locomotion. Reducing distal inertia through proximal a

researcharxiv-cs-ro

Design and Evaluation of a Collaborative Teleoperation Interface for Multi-Operator Multi-Robot Systems in Challenging Environments

arXiv:2610.15001v1 Announce Type: new Abstract: Multi-robot systems that combine the complementary capabilities of specialised platforms are critical for complex missions in challenging, inaccessible

researcharxiv-cs-ro

Design Choices for Multimodal Transformer Learning with Missing and Longitudinal Healthcare Data

arXiv:2610.14436v1 Announce Type: cross Abstract: Multimodal learning offers the potential to improve predictions by integrating complementary information from heterogeneous data sources. However, mul

tutorialsarxiv-cs-cv

Applications

DeTac: Dual-branch Decoupling of Texture and Force Signals in Vision-Based Tactile Sensors

arXiv:2610.16463v1 Announce Type: new Abstract: Vision-based tactile sensors enable fine-grained perception for dexterous robotic manipulation, but current marker-based designs tightly couple surface

applicationsarxiv-cs-ro

Detecting Chain-of-Thought Hijacking in Backdoored Multimodal Large Reasoning Models

arXiv:2610.16598v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning enables multimodal large reasoning models (MLRMs) to solve complex visual problems, but also exposes them to CoT hijack

Detecting Unreliable Classifications from Quantized Models

arXiv:2610.18575v1 Announce Type: new Abstract: Post-training INT8 quantization is typically validated by checking accuracy retention, which requires ground-truth labels often unavailable in low-resou

Deterministic denoising of long-duration gravitational-wave signal candidates with alpha-(de)blending

arXiv:2609.15308v1 Announce Type: cross Abstract: We present a deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotat

Applications

Deterministic Prediction as Global Velocity: Flow Matching for Probabilistic Time-Series Forecast

arXiv:2610.18621v1 Announce Type: new Abstract: Accurate uncertainty quantification is critical for many time series forecasting applications, and recent studies have increasingly adopted generative m

applicationsarxiv-cs-lg