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Dex4D: Task-Agnostic Point Track Policy for Zero-Shot Dexterous Manipulation

arXiv:2602.15828v2 Announce Type: replace-cross Abstract: Learning generalist policies capable of accomplishing a wide range of everyday tasks remains an open challenge in dexterous manipulation. In p

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DexCast: Learning Real-World Dexterous Control from Human Videos

DGX agent

arXiv:2610.14691v1 Announce Type: new Abstract: Recent advances in 3D hand-object interaction (HOI) perception have opened new opportunities for learning dexterous robotic skills from human videos. Ho

safetyarxiv-cs-ro

14 Oct 2026

DexFLEX: Contact-Aware Foundation Controller for Command-Guided Dexterity

arXiv:2610.14372v1 Announce Type: cross Abstract: Dexterous robot hands can receive useful motion intent from teleoperation or learned policies, but successful execution also depends on contact decisi

DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine

arXiv:2610.17208v1 Announce Type: cross Abstract: Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plast

DexStitch: Learning and Composing Dexterous Skills from Human Videos via Contact-Aware Robotic Inpainting

arXiv:2610.17789v1 Announce Type: cross Abstract: A long-horizon manipulation task consists of primitive skills and the transitions connecting them. Learning skills that can be executed in sequence re

DGSfM: Depth-Guided Scale-Aware Global Structure-from-Motion

arXiv:2607.09507v2 Announce Type: replace Abstract: Global Structure-from-Motion (SfM) is an efficient paradigm for recovering camera poses and sparse 3D structure from unordered images. However, its

Diagnose-to-Generate: Eliminating Structural Distortions in Flow Models via Patch-Level Grounded Alignment

model-releasesarxiv-cs-cv

arXiv:2610.17882v1 Announce Type: new Abstract: Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Exi

Diagnosing Generalization Boundaries in AI-Based Vulnerability Detection via Calibrated Embedding Distances

arXiv:2610.14296v1 Announce Type: cross Abstract: High benchmark scores in learning-based vulnerability detection mask severe degradation under distribution shifts. This paper demonstrates that calibr

Differential Privacy Protected Preference Alignment on Survey Derived Data

arXiv:2610.16458v1 Announce Type: cross Abstract: Preference alignment enables language models to better reflect human values, but the preference data contains sensitive information, especially when d

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

arXiv:2502.05505v4 Announce Type: replace-cross Abstract: Differentially private (DP) synthetic data enables the use of sensitive datasets while providing strong privacy guarantees. Recently, Private

DiffGA: Steering Frozen Diffusion Models for Materials Design via Evolutionary Search

arXiv:2610.14999v1 Announce Type: cross Abstract: Steering candidate generation toward user-defined objectives is central to inverse materials design, yet remains difficult when objectives are black-b

DiffNash: Finding Nash Equilibrium in High-Dimensional Continuous Action Spaces with Diffusion Policies

arXiv:2610.15932v1 Announce Type: new Abstract: Computing equilibria in high-dimensional continuous games requires learning and representing rich, multi-modal strategy distributions, something convent

Diffusion-Based Auctions for Multi-Winner Banner Ads

arXiv:2610.14473v1 Announce Type: cross Abstract: We propose a new framework for banner ad auctions, leveraging diffusion models to allow for multiple bidders to co-win a single banner ad opportunity,

Diffusion-Based Posterior Sampling: A Feynman-Kac Analysis of Bias and Stability

arXiv:2605.06538v2 Announce Type: replace Abstract: Diffusion-based posterior samplers draw from measurement- or reward-conditioned posteriors using pretrained diffusion priors. Though widely used for

Hardware

DIGS: Distribution-Informed Gaussian Splatting for Training-Free Open-Vocabulary 3D Segmentation

arXiv:2610.16177v1 Announce Type: new Abstract: Open-vocabulary 3D Gaussian segmentation typically binds semantic features to the per-Gaussian state via per-scene gradient training (1-4 h) or the more

hardwarearxiv-cs-cv

DIME: Scaling Facial Representation Learning via Differential Masked Autoencoding

arXiv:2610.17015v1 Announce Type: new Abstract: Scaling up data and model capacity has driven substantial progress in visual representation learning. However, conventional pretext tasks exhibit dimini

Directional Pullback Regularization for Long-Horizon Rollout of Latent World Models in Autonomous Driving

arXiv:2610.16139v1 Announce Type: new Abstract: Learned world models for autonomous driving operate in unconstrained latent spaces, yet the physical systems they represent are governed by strict non-h

agentsarxiv-cs-ro

Hardware

DisaggKD: Efficient Knowledge Distillation through Teacher-Student Disaggregation and a Fused Loss

arXiv:2610.17644v1 Announce Type: new Abstract: Knowledge distillation (KD) frameworks place teacher and student on the same GPUs, so per-GPU memory limits the teachers that fit. DisaggKD separates th

hardwarearxiv-cs-lg

DisCo Algebra: Why Disintegration and Combination Are Not Inverses

arXiv:2610.15006v1 Announce Type: cross Abstract: We present DisCo algebra---a compositional framework for joint probability built from a symmetric cooperad (disintegration) and a symmetric operad (co

Discover AI: A Learning Guide - 51 hands-on labs for learning how AI actually works.

model-releasesr-localllama

This is an offline app with 51 hands-on labs for learning how AI actually works, from neurons to agents and more... **A bit of insight** - 51 labs in 6 groups, from the basics (what a neuron is, gradi

Disease-level drug approval forecasting from trial-agnostic public data

arXiv:2610.14013v1 Announce Type: cross Abstract: Drug development is an expensive and lengthy process requiring developers to select drugs for human trials and diseases to target. Computational tools

Disentangling Marginal Capacity from Geometry in Optimal-Transport Label Transfer

arXiv:2610.14853v1 Announce Type: new Abstract: Optimal transport (OT) is widely used to align distributions and transfer labels between unpaired source and target data, but source-target composition

Disentangling Task-Relevant Latent Dynamics for Reward Modeling

arXiv:2610.14159v1 Announce Type: cross Abstract: Reward design remains a major bottleneck for reinforcement learning in robotic manipulation. Handcrafted dense rewards can compensate for the limited

Dissecting the Carbon-SLO Tension in Geo-Distributed LLM Serving

arXiv:2610.14571v1 Announce Type: cross Abstract: Large Language Model (LLM) inference is driving a growing share of datacenter carbon emissions. Although carbon-aware scheduling can reduce these emis

Applications

Dissipative Lagrangian Neural Networks for the Interpretable Modelling of Passive Mechanical Systems

arXiv:2610.15996v1 Announce Type: new Abstract: In this paper, we propose the Dissipative Lagrangian Neural Network (dLNN), a continuous-time system identification technique that separately learns the

applicationsarxiv-cs-lg

Dissociating Answerability from Extraction in LLM Question Answering over Radiology Reports

arXiv:2610.17576v1 Announce Type: cross Abstract: Answering questions from radiology reports involves two decisions: whether the report contains an answer and which span gives it. A false answer prese

Distance Marching for Generative Modeling

arXiv:2602.02928v2 Announce Type: replace Abstract: Modern generative models based on diffusion or flow matching transport noise toward the data manifold, without representing the data manifold explic

Distance Prediction for Quantum Codes

arXiv:2610.18130v1 Announce Type: cross Abstract: The distance of a quantum code is a fundamental metric that dictates its error-correction capability. While quantum low-density parity-check (qLDPC) f

Distill3R: A Pipeline for Democratizing 3D Foundation Models on Commodity Hardware

model-releasesarxiv-cs-cv

arXiv:2602.00865v2 Announce Type: replace Abstract: While multi-view 3D reconstruction has shifted toward large-scale foundation models capable of inferring globally consistent geometry, their relianc

Distributed area coverage path planning subject to the inclusion of a headland path

arXiv:2610.15739v1 Announce Type: new Abstract: A deterministic method for the problem of distributed area coverage path planning subject to the inclusion of a headland path is presented. Given a, in

researcharxiv-cs-ro

Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks

arXiv:2610.16142v1 Announce Type: cross Abstract: This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or E

DiTSG: Context-Aware Air Traffic Scene Generation with Multi-Agent Diffusion Transformers

arXiv:2610.16959v1 Announce Type: cross Abstract: Understanding how many aircraft, and which traffic configurations, can be safely and efficiently managed by air traffic controllers within a given air

agentsarxiv-cs-lg

Diversity You Can Actually Measure: A Fast, Model-Free Diversity Metric for Robotics Datasets

arXiv:2603.11634v2 Announce Type: replace Abstract: Robotics datasets for imitation learning typically consist of long-horizon trajectories of different lengths over states, actions, and high-dimensio

safetyarxiv-cs-ro

dMRI-F: A Foundation Model for Generalizable Diffusion MRI Analysis from Sparse Acquisitions

arXiv:2610.17968v1 Announce Type: new Abstract: Diffusion MRI (dMRI) probes water diffusion within the brain, providing unique information about tissue microstructure and white matter connectivity. Hi

Do Artificial Neural Networks Need Dendritic Nanotubes? Two Reasons for Shrinking Importance Estimates in Continual Learning

arXiv:2610.14258v1 Announce Type: new Abstract: Regularization-based continual learning protects each parameter in proportion to an estimate of its importance, yet these estimates come from finite sam

Do My Samples Help? Compute Budget Allocation for Real-World Sampling-Based MPC in Contact-Rich Manipulation

arXiv:2610.14064v1 Announce Type: new Abstract: Sampling-based model predictive control (SMPC) is increasingly practical for contact-rich manipulation because GPU-based physics simulators enable real-

safetyarxiv-cs-ro

Tutorials

Does Pretraining Teach Chemical Language Models Chemistry?

arXiv:2610.18651v1 Announce Type: new Abstract: Chemical language models (CLMs) are pretrained on large corpora of molecules with the aim of learning representations that transfer to diverse downstrea

tutorialsarxiv-cs-lg

Does Seeing More Mean Knowing More? Mono-Anchored Advantage Normalization for Multi-Source Visual Reasoning

arXiv:2605.25437v2 Announce Type: replace Abstract: Visual reasoning through reinforcement learning with verifiable rewards (RLVR) has achieved remarkable progress. However, when dealing with multi-so

Does self-distillation improve reasoning?

arXiv:2610.18613v1 Announce Type: new Abstract: Self-distillation is an emerging approach that trains a model to imitate its own predictions when conditioned on privileged information, such as correct

Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional Languages

arXiv:2610.14112v1 Announce Type: cross Abstract: Calibrated typed-decision ('System One') models return a label and a probability in a single forward pass at a small fraction of the cost of large lan

Dog-Breed Text-to-image Flow Matching from Pretraining to Fine-Tuning on 4 Consumer GPUs

model-releasesarxiv-cs-cv

arXiv:2610.18870v1 Announce Type: new Abstract: We generally perceive that training text-to-image diffusion models requires heavy compute: it is true if we aim at a comprehensive frontier model. This

DoSA: Dots Sparse Attention

arXiv:2610.13990v1 Announce Type: new Abstract: Sparse attention visits few keys, yet finding them can still require scoring every key with every indexer head. We introduce DoSA (Dots Sparse Attention

DoubtLess: Training-Free Contrastive Decoding for Efficient Reasoning

arXiv:2610.18862v1 Announce Type: cross Abstract: Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existing

agentsarxiv-cs-lg

DPAL: A Test-Time Adaptation Loss for Financial Time Series Forecasting

arXiv:2610.14376v1 Announce Type: new Abstract: Test-time adaptation (TTA) enables time series forecasters to update after deployment as new observations become available. However, adaptation objectiv

DPOison-VL: Clean Preference Poisoning in Vision-Language Direct Preference Optimization

arXiv:2610.18609v1 Announce Type: cross Abstract: Direct Preference Optimization (DPO) has become a widely adopted approach for aligning vision-language models (VLMs), yet the security of multimodal p

DR-APO: Decoupled-Representation Advantage-Guided Policy Optimization from Continuous Control to Embodied Navigation

arXiv:2610.16618v1 Announce Type: new Abstract: Policy representations in reinforcement learning have expanded beyond Gaussian policies to diffusion and flow-matching based generative policies. Howeve

DR-VLA: Learning Human-Like Quadruped Navigation from Egocentric Web Videos via Domain-Invariant Scene Representations

arXiv:2610.18373v1 Announce Type: new Abstract: Quadruped robots performing outdoor deliveries must interpret complex scenes, anticipate changes, and navigate in socially compliant ways. Robot demonst

safetyarxiv-cs-ro

Drafting Agents, Not Just Tokens: Speculative Recursive Self-Improvement for Agentic Systems

arXiv:2610.16491v1 Announce Type: new Abstract: Improving an agent through successive revisions requires balancing exploration and evaluation under a limited budget. A narrow search can miss useful se

agentsarxiv-cs-lg