Search: “models”

Mixture of Layers: Dynamic Layer Routing for Visual Reasoning

arXiv:2610.09440v1 Announce Type: new Abstract: Pre-trained vision encoders contain layer-wise visual representations that differ in spatial granularity, semantic abstraction, and sensitivity to local

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MORCA: Offline-to-Online Reinforcement Learning for Adaptive Cache Reuse in Video Diffusion Acceleration

DGX agent

arXiv:2610.10457v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve remarkable performance in video synthesis, but their iterative denoising process suffers from high inference laten

tutorialsarxiv-cs-cv

8 Oct 2026

Node-level Graph Neural Architecture Search Framework

arXiv:2610.09297v1 Announce Type: new Abstract: In recent years, Graph Neural Networks (GNNs) and architecture search frameworks have gained extensive application in non-Euclidean data processing, att

OmniCam: Omni-Camera Trajectory Generation via Geometry-Grounded Pose Token Learning

arXiv:2610.09513v1 Announce Type: new Abstract: Camera trajectories control viewpoint changes in video generation, scene reconstruction, and robotic perception. Generating them from language requires

Optimal Regret for Online Market Making with Limit Order Book

arXiv:2610.09691v1 Announce Type: cross Abstract: We study online learning in market making, where, at each round, a market maker posts bid and ask prices before observing the market price and the pri

PARC-Loc: Text-to-Point-Cloud Localization with Partial Assignment and Relational Consistency

arXiv:2610.09761v1 Announce Type: cross Abstract: Text-to-point-cloud localization estimates a position in a city-scale 3D map from descriptions of surrounding objects. Existing coarse-to-fine methods

tutorialsarxiv-cs-cl

Pareto-optimal quantum kernel selection for unsupervised anomaly detection on real malware beaconing data

arXiv:2610.09717v1 Announce Type: cross Abstract: Quantum kernel methods are leading candidates for a practical quantum advantage in machine learning, but assessing that potential requires two quantit

Physics-Aligned Electronic Ground-State Learning Improves Generalization

arXiv:2610.10298v1 Announce Type: new Abstract: Machine-learned interatomic potentials (MLIPs) excel at in-distribution tasks, accelerating drug and material development, yet they struggle to generali

Policy Learning with Weak Signals

arXiv:2610.10167v1 Announce Type: cross Abstract: Policy learning in digital experimentation faces three challenges: weak signal-to-noise ratios, rich covariate spaces, and massive data volumes. We fo

Progress and Prospect of AI in ARPES Workflow

arXiv:2610.10140v1 Announce Type: cross Abstract: Artificial intelligence (AI) is becoming an increasingly useful tool across the experimental sciences, including angle-resolved photoemission spectros

agentsarxiv-cs-lg

Q-Learning with Scalar Adjoint Matching

arXiv:2610.10437v1 Announce Type: new Abstract: Flow policies capture rich and diverse action distributions, and fine-tuning them with off-policy RL to improve beyond the demonstrations has drawn grow

Applications

Q-PhotoMarket: A Design Space Exploration Framework for Photonic Hybrid Quantum Neural Networks in Financial Market Prediction

arXiv:2610.09641v1 Announce Type: cross Abstract: Photonic quantum computing has recently emerged as a promising platform for hybrid quantum machine learning due to its native realization of linear-op

applicationsarxiv-cs-lg

Local Ai

RobotAPO: Adversarial Physics Preference Optimization for Robotic Manipulation Video Generation

arXiv:2610.09454v1 Announce Type: new Abstract: Robotic manipulation videos are increasingly used as visual plans for embodied agents, but optimizing purely for visual plausibility often fails to capt

local-aiarxiv-cs-ro

RobotWorld: Benchmarking Multimodal Agents for Robot Use Across Diverse Tasks and Embodiments

arXiv:2610.10409v1 Announce Type: cross Abstract: General-purpose agents increasingly write code, use tools, and complete complex digital tasks, raising the question of how far these capabilities carr

Shared Gaussianization: What Gaussian Regularizers Certify About Contrastive Learning, and What They Miss

arXiv:2610.10299v1 Announce Type: new Abstract: What can a distribution-matching regularizer such as SIGReg in LeJEPA certify about contrastive learning? We study shared Gaussianization (SG), a charac

Shared-Roadmap Generation and Evaluator for Multi-Agent Path Planning Using Heterogeneous Graph Neural Network

arXiv:2610.09034v1 Announce Type: cross Abstract: Multi-agent path planning (MAPP) in continuous environments often relies on roadmaps to balance safety and search efficiency. However, traditional roa

Sharp Asymptotic Theory of Maximum Likelihood Estimation for Gaussian Processes with an RBF Kernel

arXiv:2610.10080v1 Announce Type: cross Abstract: Gaussian processes (GPs) are widely used across machine learning, spatial statistics, time-series analysis, optimization, Bayesian statistics, and sci

SkillSandbox: Skill Verification via Dynamic Scenario Synthesis

arXiv:2610.10088v1 Announce Type: cross Abstract: Self-evolving agents distill task-solving experience into skills for future reuse, but these skills can encode incorrect procedures or non-transferabl

researcharxiv-cs-cl

Applications

Speech Emotion Recognition Using CNN and Its Use Case in Digital Healthcare

arXiv:2406.10741v2 Announce Type: replace-cross Abstract: The process of identifying human emotion and affective states from speech is known as speech emotion recognition (SER). This is based on the o

applicationsarxiv-cs-lg

SPLATIFY: Reproduce, Discover, Innovate! From Papers and Ideas to Trainable 3DGS Code

arXiv:2610.09116v1 Announce Type: new Abstract: The rapid growth of 3D Gaussian Splatting (3DGS) research demands significant effort to reimplement papers before building on them. We introduce SPLATIF

agentsarxiv-cs-cv

STRIDE: Spatial-Temporal Representation for Interval-conditioned Disease Evolution in Longitudinal Glioblastoma MRI

arXiv:2610.08848v1 Announce Type: cross Abstract: Glioblastoma (GBM), an aggressive primary brain tumor, is routinely monitored with longitudinal MRI after treatment. Distinguishing stable disease (SD

Symmetry-Informed Causal Partial Identification

arXiv:2610.09230v1 Announce Type: new Abstract: Partial identification (PI) entails estimating bounds on causal effects by encoding different assumptions on data generation as a constrained optimizati

The Silhouette Operator: Identifiability of Low-Rank Measures from One-Dimensional Projections

arXiv:2610.09687v1 Announce Type: cross Abstract: Structured recovery phenomena, such as restricted isometry properties in compressed sensing, have shown that high-dimensional objects can often be rec

TMT: Runtime Backdoor Detection for Vision-Language-Action Policies on Unseen Tasks

arXiv:2610.09462v1 Announce Type: new Abstract: Backdoored vision-language-action (VLA) policies can preserve benign task performance while producing malicious actions when a trigger appears. Detectin

safetyarxiv-cs-ro

TouchScale: 500 Hours of Human Vision and Touch for Visual-Tactile Learning

arXiv:2610.10288v1 Announce Type: new Abstract: Large-scale egocentric human interaction data is becoming an important source of physical supervision for embodied learning, yet video alone leaves the

safetyarxiv-cs-cv

Tracing Inputs, Verifying Outputs: Validating Attribution in Music Generation

arXiv:2610.09637v1 Announce Type: cross Abstract: How can we verify whose music contributed to an AI-generated output? This paper demonstrates how input-based attribution can provide verifiable eviden

Transition Path Sampling Using Koopman Operators and Exit-Time Optimal Control

arXiv:2610.10054v1 Announce Type: cross Abstract: Sampling transitions between metastable states is a central problem in dynamical systems theory and molecular dynamics in particular. A key challenge

Local Ai

Trust-Region Optimization for Smooth Potential-Interaction Energies in Wasserstein Space

arXiv:2610.08883v1 Announce Type: cross Abstract: Finding low-energy configurations of interacting particles and approximating probability distributions lead to the minimization of potential-interacti

local-aiarxiv-cs-lg

UniCSI Towards a Universal Wi-Fi CSI Encoder for Ubiquitous Human Sensing

arXiv:2610.09559v1 Announce Type: new Abstract: Wi-Fi sensing promises to turn the everyday wireless signals that already surround us into ubiquitous sensors for human sensing. However, a fundamental

Local Ai

Universal Local Error and Realized Amplification for the First-Order EDM Predictor

arXiv:2610.10190v1 Announce Type: cross Abstract: We analyze the first-order deterministic diffusion sampler of Karras et al. (2022), termed EDM, in 2-Wasserstein distance by separating two sources of

local-aiarxiv-cs-lg

VIA: Visual Interface Agent for Robot Control

arXiv:2607.11119v2 Announce Type: replace Abstract: Robot manipulation is a complex task that requires visual perception, physical reasoning, planning, and closed-loop control. General-purpose foundat

agentsarxiv-cs-ro

Video-Conditioned Generative Joint 2D-3D Hand Motion Recovery

arXiv:2610.10512v1 Announce Type: new Abstract: Recovering faithful 3D hand motion from video remains challenging due to frequent occlusions and incomplete visual observations, which make frame-wise p

tutorialsarxiv-cs-cv

VM-ARRAYDPS: Virtual Microphone Augmented Diffusion Posterior Sampling for Unsupervised Blind Speech Separation

arXiv:2610.09334v1 Announce Type: cross Abstract: Blind Source Separation(BSS) is a fundamental problem in signal processing, aiming to separate multiple source signals from their mixtures without pri

tutorialsarxiv-cs-lg

2D Spatial Reasoning with Adaptive Neural Cellular Automata

arXiv:2610.08518v1 Announce Type: new Abstract: Many modern learning approaches are still struggling with spatial reasoning tasks, i.e. they lack the ability to utilize geometric information of percei

AFA-BANDIT: Provably Near-Optimal Online Multi-Feature Classification Under Budget Constraints

arXiv:2610.07615v1 Announce Type: new Abstract: Active Feature Acquisition (AFA) is a classification problem in which an agent decides which costly features to acquire before predicting each sample's

Agentic Semantic Sensing for Resource-Adaptive AI-RAN

arXiv:2610.07829v1 Announce Type: new Abstract: Semantic sensing (SemS) acquires task-relevant information rather than reconstructing complete physical information. Existing SemS formulations typicall

agentsarxiv-cs-ai

AIMS: Anchor-Integrated Multi-View Synthesis for Scalable Novel View Rendering

arXiv:2610.07566v1 Announce Type: new Abstract: Feed-forward novel view synthesis methods achieve strong generalization from posed multi-view inputs, but scaling them to large input view sets remains

Anchor and Adapt: Asymmetric Prompt Adaptation for Few-Shot Industrial Anomaly Detection

arXiv:2610.07016v1 Announce Type: cross Abstract: In few-shot industrial anomaly detection, the few normal target images provide no direct defect supervision, making anomaly prompts difficult to learn

tutorialsarxiv-cs-ai

Anytime-valid simulation-based hypothesis testing

arXiv:2610.08210v1 Announce Type: cross Abstract: For a given data distribution (X_t)_{t in N} sim Q i.i.d., we investigate the hypothesis testing problem: H_0: Q = P_0 vs. H_1: Q = P_1, for two diffe

ApexQuant: Data-Free Elastic Quantization by Residual Re-Isotropization

arXiv:2610.07904v1 Announce Type: new Abstract: We introduce ApexQuant, a calibration-free quantization method that recursively re-quantizes the residual error, serving as a refinement layer on top of

Auditable Claims about AI Agents

arXiv:2610.07459v1 Announce Type: new Abstract: Organizations make claims about their AI agents: a person approves every external email, every action is logged, an evaluation shows the agent is safe t

safetyarxiv-cs-ai

Applications

Beyond Marginals: A Multi-Dimensional Evaluation Framework for Multi-Table Synthetic Data Generation

arXiv:2610.06854v1 Announce Type: cross Abstract: Synthetic data generation is critical for privacy compliance, machine learning augmentation, and software testing. While single-table evaluation is we

applicationsarxiv-cs-lg

Building Rome from a Single Image

arXiv:2610.08790v1 Announce Type: new Abstract: Single-image scene generation aims to produce a complete 3D scene mesh from a single image, including surfaces the camera did not observe. While pretrai

Calibrated Uncertainty for Informative Path Planning in Aquatic Environmental Monitoring

arXiv:2609.34577v2 Announce Type: replace Abstract: Informative Path Planning for scalar field reconstruction uses predictive uncertainty to direct sensing vehicles toward maximally informative locati

researcharxiv-cs-ai

Calibration Is Not Control: Intervention Value for LLM-Agent Oversight

arXiv:2606.21399v2 Announce Type: replace Abstract: Runtime oversight often intervenes when an LLM agent's calibrated failure score crosses a threshold. Yet states with the same failure risk can diffe

safetyarxiv-cs-ai

Can Semantic Geometry Teach an AI Judgement?

arXiv:2610.07249v1 Announce Type: new Abstract: How can an AI agent determine what rules to follow? One rule permits an action. Another imposes a condition, exception, or conflicting obligation. Deter

safetyarxiv-cs-ai

CANDLE: Cortical Null-Space Decomposition for Noninvasive Brain Source Imaging

arXiv:2610.07824v1 Announce Type: new Abstract: Electrophysiological source imaging (ESI) aims to estimate cortical source activity from noninvasive electrophysiological measurements such as electroen

Catching Developers in the Flow: Low-Latency Agentic Program Repair at Google Scale

arXiv:2610.07289v1 Announce Type: cross Abstract: Manual repair of program failures is time-consuming and disruptive for software developers, particularly during the pre-submit phase where test failur

agentsarxiv-cs-ai