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arXiv:2610.00097v1 Announce Type: new Abstract: Recent diffusion and autoregressive models have substantially improved text-to-video generation, yet producing coherent long-form story videos with cons

agentsarxiv-cs-cv

Hardware

DRelay: Global Draft Context for Prefix-Aware Parallel Speculative Decoding Repair

Content type

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DGX agent

arXiv:2610.01439v1 Announce Type: new Abstract: Parallel drafting reduces the drafting overhead of speculative decoding for large language models (LLMs), but its gains remain limited by the accepted p

hardwarearxiv-cs-ai

2 Oct 2026

DriftOPD: Sequence-Level Reverse-KL Distillation for One-Step VLA Policies

arXiv:2610.00317v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models increasingly rely on action experts that generate short action chunks under receding-horizon control. While chunk-

DSSR-3D: Decoupled Reasoning for View-Dependent Referring in 3D Gaussians

arXiv:2610.00040v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have enabled open-vocabulary and referring segmentation by distilling semantic knowledge from 2D foundation mod

DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication

arXiv:2610.02161v1 Announce Type: cross Abstract: Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progres

DuplexSpeechBench-Document Grounding: Benchmarking Document Grounding and Hallucinations in Voice Agents

arXiv:2610.00316v1 Announce Type: cross Abstract: Voice agents enable low-latency, natural interaction, yet their ability to faithfully ground responses in external documents remains underexplored. We

Dyna-DINO: Efficient ViT Distillation Via Adaptive Representation Anchoring

arXiv:2606.19483v2 Announce Type: replace Abstract: Vision Foundation Models (VFMs) with Vision Transformer (ViT) backbones, such as DINOv2, have become essential for downstream tasks like object reco

researcharxiv-cs-cv

Dyna3: VLM-Guided Training-Free 4D Reconstruction via Depth Foundation Models

arXiv:2610.01286v1 Announce Type: new Abstract: Recent depth foundation models like Depth Anything 3 (DA3) achieve remarkable multi-view depth estimation but assume static 3D scenes, limiting their ap

applicationsarxiv-cs-cv

DynamicVLA: A Vision-Language-Action Model for Dynamic Object Manipulation

arXiv:2601.22153v2 Announce Type: replace-cross Abstract: Manipulating dynamic objects remains an open challenge for Vision-Language-Action (VLA) models. Although recent VLAs generalize well in static

ECHO: A Participatory Framework for Bias-Anchored AI Harm Anticipation

arXiv:2512.03068v2 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) systems increasingly shape consequential decisions, creating value but also potential harms for individuals, soci

EchoPress: Query-Agnostic KV Cache Pruning via Virtual Context Reconstruction

arXiv:2610.00412v1 Announce Type: new Abstract: KV cache pruning reduces long-context inference memory usage by evicting less important key-value pairs. KVzip estimates importance through context reco

ECoMEM: Explicit Concept Memory for Memory-Dependent Robot Control

arXiv:2610.00801v1 Announce Type: new Abstract: A robot may lose sight of an object it must later retrieve, need to recall what a person demonstrated earlier, or track which steps of a task it has alr

safetyarxiv-cs-ro

Local Ai

Effective Resistance and Graph Neural Network Reliability in Tissue-Specific Interactomes

arXiv:2610.02175v1 Announce Type: new Abstract: Protein function annotation needs to know which predictions to distrust, not only what a model predicts. We ask whether tissue-specific interaction stru

local-aiarxiv-cs-lg

Tutorials

Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrodinger Bridge Matching

arXiv:2602.15396v2 Announce Type: replace Abstract: Diffusion models often yield highly curved trajectories and noisy score targets due to an uninformative, memoryless forward process that induces ind

tutorialsarxiv-cs-cv

EfficientRollout: System-Aware Self-Speculative Decoding for RL Rollouts

arXiv:2606.18967v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a representative post-training paradigm for large language models (LLMs), enabling strong reasoning and agent

safetyarxiv-cs-lg

Ego2Act: Evaluating Goal-Directed Manipulation in Egocentric Video Generation

arXiv:2610.01092v1 Announce Type: new Abstract: Video generation models are increasingly being explored as world simulators for embodied planning and learning. To do so effectively, these models must

EgoForge: Goal-Directed Egocentric World Simulator

arXiv:2603.20169v2 Announce Type: replace Abstract: Generative world models have shown promise for simulating dynamic environments, yet egocentric video remains challenging due to rapid viewpoint chan

safetyarxiv-cs-cv

EgoFound3R: End-to-End Egocentric Hand Reconstruction in World Space with Point-Wise Interaction Attributes

arXiv:2610.01210v1 Announce Type: new Abstract: Egocentric video has become a primary source of supervision for embodied models, and its value rests on recovering hand motion in world coordinates, whi

EgoRefine: Ego-Referenced Predictive Alignment and Trajectory-Conditioned Reliability-Aware Fusion for Asynchronous Collaborative Perception

arXiv:2610.00319v1 Announce Type: new Abstract: Collaborative perception enables connected agents to share complementary observations for 3D object detection, extending sensing range and mitigating oc

safetyarxiv-cs-cv

EIDA: Execution-Interface Dynamics Adaptation for Real-to-Sim-to-Real Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2610.01219v1 Announce Type: new Abstract: Simulation-to-robot transfer can fail when velocity commands produce motion and feedback that differ from those modeled during policy training. We prese

Embedding Prediction Helps Image Generation

arXiv:2610.02203v1 Announce Type: new Abstract: In diffusion transformers, a class label or a text prompt is embedded once, and the same condition is reused at every denoising step. We ask whether pre

researcharxiv-cs-cv

Emergent Object Binding Has a Finite Spatial Horizon

arXiv:2610.00006v1 Announce Type: new Abstract: Pretrained Vision Transformers encode whether two image patches belong to the same object. This IsSameObject signal is decodable from frozen patch embed

researcharxiv-cs-cv

Emergent Unfaithfulness: How Alignment Training Causes Language Models to Silently Override Task Faithfulness

arXiv:2610.00568v1 Announce Type: cross Abstract: Large language models are characterized by three key properties: capability, alignment, and faithfulness. Prior work studies the tradeoffs between cap

Agents

Empty Commitments: When Agents Promise What Their Runtime Cannot Deliver

arXiv:2610.01045v1 Announce Type: new Abstract: A chatbot that says 'I will remind you tomorrow' will not run again until the user writes. We call such a promise an empty commitment: a promise of an a

agentsarxiv-cs-ai

Encoded but Disconnected: Decomposing Vision-Language Model Failures under a Patching Null

arXiv:2610.00024v1 Announce Type: new Abstract: Across three vision-language model architectures (LLaVA-1.5-7B, Qwen2.5-VL-7B, InternVL3-8B), we report a universal negative finding for mid-layer inter

End-to-End Historical Music Restoration in Latent Space

arXiv:2610.00607v1 Announce Type: cross Abstract: Historical music restoration (HMR) has almost exclusively focused on constrained problems such as Super-Resolution or the restoration of solo pieces,

End-to-End Learning vs. Modular Architectures: Comparative Insights into Autonomous Driving Systems

arXiv:2610.01746v1 Announce Type: cross Abstract: Autonomous driving systems have become a central focus of intelligent transportation research, with End-to-End Learning and Modular Architectures offe

safetyarxiv-cs-cv

Tutorials

EndoLive: Real-Time Style Transfer for Endoscopic Endonasal Skull Base Surgical Video

arXiv:2610.01956v1 Announce Type: new Abstract: Complex surgical procedures around critical anatomy, such as the endoscopic endonasal skull base surgery, requires significant practice and training on

tutorialsarxiv-cs-cv

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

applicationsarxiv-cs-lg

Local Ai

Enterprise Representation Simplification (ERS): Reducing Representational Complexity for Enterprise AI

arXiv:2610.00791v1 Announce Type: new Abstract: Enterprise information is represented through artifacts shaped by applications, projects, technologies, organizational boundaries, and local requirement

local-aiarxiv-cs-ai

Enterprise storage becomes AI memory as privately run models close in on the frontier

As open-weight models close in on the performance of proprietary frontier systems, enterprises are gaining a credible way to run generative AI on hardware they own. That shift puts the data already si

applicationssiliconangle

EP-Flow: Disordered Crystal Structure Prediction without Site-Level Annotations

arXiv:2610.01315v1 Announce Type: new Abstract: Generative models have made rapid progress in ordered crystal structure prediction, yet many functional materials are intrinsically disordered, with sub

researcharxiv-cs-lg

eRLT: Efficient VLA Reinforcement Learning via Action-Relevant Token Routing

arXiv:2610.00913v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide strong behavioral priors for robotic manipulation, yet efficiently adapting them to downstream tasks remains

researcharxiv-cs-ro

Error-Corrected Inference-Time Scaling for Imperfect Diffusion Models

arXiv:2610.01933v1 Announce Type: cross Abstract: Inference-time scaling adapts pretrained diffusion models to new sampling tasks without additional training. Existing methods rely primarily on Monte

researcharxiv-cs-lg

ESCROW: Guarded and Dual-Objective Continual Maintenance for Agents in Policy-Governed Enterprise Workflows

arXiv:2608.01772v2 Announce Type: replace Abstract: LLM agents increasingly run policy-bound enterprise workflows, where they must apply rules consistently and stay auditable. Deploying such an agent

EurekaBench: Measuring Agentic Ability to Discover New Scientific Insights

arXiv:2610.00492v1 Announce Type: cross Abstract: When Isaac Newton discovered the law of gravitation, he did so through an iterative process of analyzing observed data such as planetary patterns, fin

Evaluating Hybrid Quantum-Classical Models for Reduced-Order Brain Deformation Dynamics

arXiv:2610.00554v1 Announce Type: new Abstract: We evaluate hybrid quantum-classical machine learning for the reduced-order prediction of spatiotemporal brain deformation fields. To mitigate the compu

Evaluating LLM-Generated Preference Distributions

arXiv:2610.01000v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as probabilistic generators for simulation, synthetic data generation, and decision support in settin

applicationsarxiv-cs-ai

Evaluating Physical Consistency and Plausibility in Generative Scenario Models for Autonomous Driving

arXiv:2610.01581v1 Announce Type: new Abstract: Generative AI models are increasingly used for scenario generation in autonomous driving. While they can generate realistic-looking scenarios, they ofte

Evaluating the Robustness of Anti-UAV Detection under Controlled Fog Degradation: Fog-Aware Training and Clear-Sky Tradeoff

arXiv:2610.00141v1 Announce Type: new Abstract: Vision-based anti-UAV systems must function in poor visibility, yet most benchmarks use only clear-sky footage, and previous robustness studies treat ad

Evasion Attacks: How Adversarial Noise Bypasses ML Classifiers

arXiv:2610.00136v1 Announce Type: cross Abstract: This paper presents a reproducible, educational study of evasion attacks in image classification and text classification. A compact convolutional netw

researcharxiv-cs-lg

Even if AIs become conscious, that doesn't imply that humanity should hand over control to them. https://eigenism.org

Even if AIs become conscious, that doesn't imply that humanity should hand over control to them. https://eigenism.org NEW: According to a bombshell report in the New York Times, Anthropic co-founder C

safetydan-hendrycks--x

EvenSplat: Coupled 2D-3D Decomposition for Gaussian Splatting under Exposure and Illumination Variation

arXiv:2610.01876v1 Announce Type: new Abstract: A surface photographed under even light presents nearly the same appearance from every angle; the same surface under uneven light does not. Exposure cha

applicationsarxiv-cs-cv

Every Ablation Is a Dose: Counterweights and the Semblance of Self-Repair

arXiv:2610.02173v1 Announce Type: new Abstract: Ablate a component of a language model, and other components often appear to adjust and compensate. This phenomenon, termed self-repair, has been observ

Every Batch Is Its Own Validation Set: Leave-One-Out Gradient Matching for Online Data Selection in LLM Fine-Tuning

arXiv:2610.00436v1 Announce Type: new Abstract: Online batch selection fine-tunes a language model on the most useful part of each candidate batch. Selectors that match the gradient of the candidate b

Evidence-Gated Research: Statistically Controlled Model Adoption in Adaptive Search

arXiv:2610.01751v1 Announce Type: new Abstract: Adaptive model search is path dependent: once a challenger is adopted, it becomes the reference from which later candidates are generated. A statistical

EviGraph: Proof-Carrying Selective Recommendation over Temporal Public-Service Knowledge Graphs

arXiv:2610.00212v1 Announce Type: new Abstract: Public-service recommendations require evidence that matches the requested service, scope, and date. Yet treating every missing detail as decisive can w

Tutorials

EvoGen-Harness: Learning Where and How to Evolve Image-Generation Harnesses

arXiv:2610.00383v1 Announce Type: new Abstract: Modern text-to-image (T2I) systems can be improved without modifying generator parameters by adapting the external system around frozen generators. Howe

tutorialsarxiv-cs-lg