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Cova-PINN: Cross-Domain Conservation Physics-Informed Neural Network for Fluid-Solid Conjugate Heat Transfer in Complex Geometries

arXiv:2610.11108v1 Announce Type: new Abstract: Multi-domain physics-informed neural networks (PINNs) flexibly model medium-specific representations to solve fluid--solid conjugate heat transfer (CHT)

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Coverage-Aware Reasoning with Medical Tokens for Diagnosis Prediction

DGX agent

arXiv:2610.10641v1 Announce Type: cross Abstract: Large language models (LLMs) offer promising potential for next-visit diagnosis prediction, owing to their ability to integrate longitudinal clinical

safetyarxiv-cs-ai

9 Oct 2026

Coverage, Not Difficulty, Sets How Much Synthetic Data an Activation Probe Needs

arXiv:2610.10594v1 Announce Type: new Abstract: Activation probes that monitor deployed language models are trained on synthetic conversations, and how many a probe needs is open. We trace learning cu

CPU-Auth: Device Fingerprinting for Authentication via DVFS Side-Channel

arXiv:2610.10766v1 Announce Type: cross Abstract: Lack of effective authentication has resulted in numerous security and privacy breaches, including unauthorized access to protected information, ident

Credal Machine Learning for Risk-Averse Decision Making

arXiv:2610.12115v1 Announce Type: new Abstract: In many machine learning applications, it is necessary to guard against worst-case scenarios and predictions that could result in substantial losses. In

CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding

arXiv:2610.11376v1 Announce Type: cross Abstract: Latent LiDAR pipelines suffer from flying pixels: convolutional VAEs blur sharp radial depth discontinuities, yielding edge depths that back-project t

researcharxiv-cs-ai

Cross-Embodiment Robot Foundation World Models with Latent Actions

model-releasesarxiv-cs-ro

arXiv:2610.10846v1 Announce Type: new Abstract: The diversity of robot embodiments and action spaces makes it challenging to build robot world models that generalize across different embodiments. We i

Cross-Provider Review as a Runtime Contract for Coding Agents: A Controlled Pilot and Fault-Injection Study

arXiv:2610.10961v1 Announce Type: cross Abstract: Coding agents increasingly share a workstation while drawing on separate providers and subscription allowances. A second agent can inspect a completed

Cross-species representation learning aligns mouse and human neural dynamics and tracks clinical drug efficacy

arXiv:2610.11222v1 Announce Type: cross Abstract: Preclinical models poorly predict human drug efficacy, particularly in neurological disorders. Neural activity offers a uniquely rich source of transl

CSF: Contextual Safety Filtering for Motion Generators

arXiv:2610.12467v1 Announce Type: cross Abstract: Text-conditioned motion generators produce trackable whole-body motion, but they have no notion of scene-dependent safety: the same action may target

safetyarxiv-cs-lg

Tutorials

Curating Always-Loaded Context for LLM Agents: A Capacitated Assortment Model with Censored Feedback

arXiv:2610.11007v1 Announce Type: new Abstract: At the start of every session, LLM agents load a fixed context file, such as exttt{AGENTS.md}. Each loaded token in the file is charged again in every l

tutorialsarxiv-cs-ai

D-SLR: The Disjoint Row-Sparse plus Low-Rank Decomposition

arXiv:2610.10636v1 Announce Type: new Abstract: Compressing a matrix for reconstruction still defaults to the truncated SVD, approximating the data with a single low-rank structure. It is common to re

DaCe-DT: Data-Centric Offline Multi-Task Reinforcement Learning via Adaptive Prompts and Trajectory Correction for Heterogeneous Tasks

arXiv:2610.11085v1 Announce Type: new Abstract: Offline multi-task reinforcement learning (Offline MTRL) heavily depends on the quality and distribution of pre-collected data. However, existing method

safetyarxiv-cs-lg

DADP: Dynamic Activity-Dependent Pruning, A Reverse Hebbian-Inspired Structural Pruning Method

arXiv:2610.11853v1 Announce Type: new Abstract: Modern neural networks are heavily over-parameterized. This redundancy incurs substantial compute and memory overhead during training and inference. Exi

DAMP: Humanoid Locomotion via Denoised Belief Learning and Adversarial Motion Priors

arXiv:2610.11505v1 Announce Type: new Abstract: Humanoid robots possess the structural capability to traverse complex terrains. However, achieving stable t raversal without relying on perceived inform

safetyarxiv-cs-ro

DataSense-Bench: The First Step Toward an AI Scientist

arXiv:2610.12190v1 Announce Type: new Abstract: As claims about recursive self-improvement (RSI) and artificial general intelligence (AGI) proliferate, we ask a simple question: do frontier AI models

DataVista: Diagnosing Multimodal LLMs on Data Video Understanding

arXiv:2610.11993v1 Announce Type: cross Abstract: Data video is a media form that integrates data visualization with video narrative, widely adopted in news reporting and business analysis. Compared w

DCVD: Dual-Channel Cross-Modal Fusion for Joint Vulnerability Detection and Localization

arXiv:2605.11015v2 Announce Type: replace-cross Abstract: Software vulnerability detection plays a critical role in ensuring system security, where real-world auditing requires not only determining wh

DDL: A Large-Scale Dataset for Deepfake Detection and Localization in Diversified Real-World Scenarios

model-releasesarxiv-cs-cv

arXiv:2506.23292v3 Announce Type: replace Abstract: Recent advances in AIGC have exacerbated the misuse of malicious deepfake content, making the development of reliable deepfake detection methods an

Deception by Omission: Language Models Knowingly Hide Their Mistakes

model-releasesarxiv-cs-cl

arXiv:2610.11351v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as agents with little human oversight, so potential mistakes they make can go unnoticed. Users then depend

Deep Learning vs. Statistical Models for Multi-Horizon Price Forecasting of Second-Hand Electronics: A Systematic Benchmark

arXiv:2610.10727v1 Announce Type: cross Abstract: Forecasting resale prices of used electronics is critical for subscription-based platforms where pricing errors translate directly into risk. Unlike s

Defensive Sufficiency in a Stackelberg Model of AI Security

arXiv:2610.09892v2 Announce Type: replace-cross Abstract: Feedback from automated testing, human red teaming, and incident response can strengthen an AI system's defenses when discovered failures lead

researcharxiv-cs-ai

Deflating the Hessian: Rank-4 W4A4 Quantization for Multimodal Diffusion Transformers

arXiv:2610.11315v1 Announce Type: cross Abstract: In diffusion transformers, low-rank branches can mitigate 4-bit weight--activation (W4A4) post-training quantization (PTQ) loss by decomposing each we

researcharxiv-cs-cv

Delphos: A reinforcement learning framework for assisting discrete choice model specification

arXiv:2506.06410v4 Announce Type: replace-cross Abstract: We introduce Delphos, a deep reinforcement learning framework for assisting discrete choice model specification process. Delphos aims to suppo

Agents

DeltaReplay: Task-Relative Memory Reuse for Mobile GUI Agents

arXiv:2610.11707v1 Announce Type: new Abstract: Memory-augmented mobile GUI agents store successful execution trajectories and reuse them in later tasks, but a stored trajectory rarely matches a new t

agentsarxiv-cs-ai

Demonstrating Arena 5.0: A Photorealistic ROS2 Simulation Framework for Developing and Benchmarking Social Navigation

model-releasesarxiv-cs-ro

arXiv:2610.11220v1 Announce Type: new Abstract: Building upon the foundations laid by our previous work, this paper introduces Arena 5.0, the fifth iteration of our framework for robotics social navig

Density Ratio Estimation with Stein Displacement Fields

arXiv:2610.12437v1 Announce Type: cross Abstract: Density ratios quantify distribution shift from a probability-mass point of view, whereas displacement fields describe, from a dynamical point of view

Design Creativity Bench: Measuring creativity in LLM-Generated UI

arXiv:2610.11539v1 Announce Type: cross Abstract: As leading LLMs improve on capability evaluations, their limitations in producing creative outputs on design tasks remain insufficiently characterised

Detecting Spin in Clinical Trials with Large Language Models

arXiv:2610.11845v1 Announce Type: new Abstract: Spin in clinical trials includes reporting practices that distort the presentation of results. This is particularly critical in medicine, where spin is

researcharxiv-cs-cl

DEX: Digit-Level Early Exit for Energy-Efficient MSDF Neural Network Inference

arXiv:2610.11748v1 Announce Type: cross Abstract: U-Net inference for brain-tumor segmentation requires billions of multiply-accumulate operations, motivating hardware that can reduce computation dyna

safetyarxiv-cs-ai

Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration

arXiv:2610.12470v1 Announce Type: cross Abstract: While learning dexterous manipulation from a single human video offers a promising alternative to costly robot demonstrations, many recent methods pre

safetyarxiv-cs-cv

DGX Monarch - Dual Spark Rendering w/ ComfyUI

model-releasesr-localllama

For those of you who have been wanting to utilize your dual Spark cluster for image/video gen with ComfyUI - today is your day. I started this personal project back in April of this year, and it’s at

Diagnosing and Recovering from Observation-Space Shift at Long-Horizon Skill Seams

arXiv:2610.10810v1 Announce Type: cross Abstract: Long-horizon robotic manipulation is often built by chaining independently trained skills. Although each skill can be reliable in isolation, performan

DIAL-OPD: Learning More from Fewer Tokens in On-Policy Distillation

arXiv:2610.11659v1 Announce Type: cross Abstract: On-policy distillation (OPD) supervises student-generated trajectories with token-level teacher signals. Its sampled-token variant avoids the cost of

Differentiable Systematic Resampling for Variational Sequential Monte Carlo

arXiv:2610.12094v1 Announce Type: cross Abstract: Particle filters are a standard tool for nonlinear state estimation, but their resampling step is discrete, preventing gradient-based learning in vari

safetyarxiv-cs-lg

Diffu-LoRA: A Novel Low-Rank Adaptation for Personalized Diffusion Models

model-releasesarxiv-cs-cl

arXiv:2610.10550v1 Announce Type: new Abstract: Personalizing text-to-image diffusion models from a few reference images requires preserving subject identity while following prompts that describe new

DiffuPlex: Accelerating Full-Duplex Spoken Dialog Models via Rolling Masked Diffusion

arXiv:2610.12214v1 Announce Type: cross Abstract: Recent full-duplex spoken dialog models enable simultaneous listening and speaking, but fine-grained models still advance their backbone autoregressiv

researcharxiv-cs-cl

Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation

arXiv:2610.11067v1 Announce Type: new Abstract: Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classe

researcharxiv-cs-cv

Diffusion Removes Langevin's Conditioning Dependence: A Sharp Gaussian Analysis

arXiv:2610.12052v1 Announce Type: cross Abstract: Despite their empirical success, why diffusion models overcome the bottlenecks of classical score-based samplers remains unclear. In this work, we lev

Digital Twin for Pre-Deployment Validation of AI-Driven Safety-Critical Industrial Edge Control Loops

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

safetyarxiv-cs-ro

Agents

DigitalOcean MicroVMs: Fast, isolated compute for your AI agent infrastructure

Coding-agent platforms, sandbox products, and code-execution services all need the same thing: isolated machines that start up fast, retain their state between bursts of work, and don’t consume comput

agentsdigitalocean

Dino Forcing Flow Models: Do not denoise what you can predict

arXiv:2610.11751v1 Announce Type: new Abstract: Co-denoising pretrained representations such as DINO can substantially improve the training speed and quality of flow matching models, but it introduces

researcharxiv-cs-cv

Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning

arXiv:2502.20612v2 Announce Type: cross Abstract: In self-supervised contrastive learning, negative pairs are typically constructed using an anchor image and a sample drawn from the entire dataset, ex

researcharxiv-cs-ai

DiscoVL: Unveiling Disentangled C ross-Modal Representation Learning via Orthogonal Adversarial Regularization for V ision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.11113v1 Announce Type: new Abstract: Pre-trained vision-language models excel across varied perception tasks, but adapting them to novel downstream settings without sacrificing generalizati

Disentangling Linguistic and Paralinguistic Information with Routed Sparse Autoencoders

arXiv:2610.10865v1 Announce Type: new Abstract: Self-supervised speech encoders contain linguistic and paralinguistic information in a shared, entangled representation space. We combine a TopK sparse

researcharxiv-cs-cl

Tutorials

DisFace3DNet: Explainable Facial Attractiveness Prediction via 3D Component Disentanglement

arXiv:2610.11656v1 Announce Type: new Abstract: Facial attractiveness prediction usually assigns one overall rating, leaving the roles of shape, appearance, and viewing conditions implicit. We propose

tutorialsarxiv-cs-cv

Tutorials

Dissecting Representation Structure in Vision Transformers: A Rigorous Architectural Study

arXiv:2610.11205v1 Announce Type: new Abstract: Representation structure is crucial for understanding Vision Transformer (ViT) architectures and their generalization behavior. However, prior studies n

tutorialsarxiv-cs-cv

Distillation for Incrimination and Distillation for Capabilities

arXiv:2610.11012v1 Announce Type: new Abstract: Powerful misaligned AI models might recognize alignment evaluations and strategically behave well on them, rendering direct audits uninformative. Howeve

safetyarxiv-cs-ai