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ESTHER: Egocentric Stereo Hand Estimation and Reconstruction in the Wild

arXiv:2609.34817v1 Announce Type: new Abstract: Human dexterity is guided by two eyes watching two hands: binocular vision supplies the metric 3D structure that fine-grained manipulation consumes. Ego

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Safety

Estimate, Don't Imitate: Reusing Differentiable State-Based Policies for Visuomotor Control

DGX agent

arXiv:2609.34018v1 Announce Type: cross Abstract: Simulation-trained manipulation policies can exploit privileged state information to learn effective contact-rich behaviours, but deployment requires

safetyarxiv-cs-lg

29 Sept 2026

eval-unlearn: Benchmarking unlearning in Text-to-Image Diffusion Models

arXiv:2609.35269v1 Announce Type: cross Abstract: The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods ar

Evaluating Dynamical Fidelity through Predictive Structure in Physical Representations

arXiv:2609.34627v1 Announce Type: new Abstract: Machine-learning models for physical systems are currently evaluated primarily through errors between predicted and reference states and, increasingly,

Evaluating Hierarchy-Aware Deep Learning for the Recognition of Tironian Notes

arXiv:2609.35277v1 Announce Type: new Abstract: Tironian notes are generally regarded as the first Latin shorthand system and are notable for their large, fine-grained symbol inventory. Their high vis

Evaluating Single and Multi-Omics Based Explainable Artificial Intelligence (MOXAI) for Molecular Subclass Classification of Adult-Type Diffuse Gliomas

arXiv:2609.32190v1 Announce Type: new Abstract: DNA methylation (DNAM) profiling has emerged as a powerful diagnostic tool for classifying brain and solid tumors. However, existing computational model

Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

arXiv:2609.31981v1 Announce Type: cross Abstract: As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such s

EvE: An Alternate Optimizer to Adam

arXiv:2609.35614v1 Announce Type: new Abstract: Adam and its variants dominate neural network training, but a single run only reveals whether a configuration works well after most of its budget is spe

Every state ag and DA w jurisdiction should be launching investigations

Every state ag and DA w jurisdiction should be launching investigations NEW: Employees at OpenAI had raised security alarms months before the Hugging Face incident and related A.I. cyberattacks — thei

safetygary-marcus--x

eVGGT: An Efficient Geometry-Aware Vision Encoder for Visuomotor Policies

arXiv:2509.15880v2 Announce Type: replace Abstract: Geometry-grounded vision models, such as VGGT, have emerged as robust visual encoders, providing essential geometric priors for robotic manipulation

Evidence-Aligned Multimodal On-Policy Self-Distillation for Fine-Grained Visual Understanding

arXiv:2609.34672v1 Announce Type: new Abstract: Fine-grained visual understanding requires models to recognize small details within complex images. Multimodal on-policy self-distillation (OPSD) addres

safetyarxiv-cs-cv

Evidence Before Accuracy: A MRI-PET Fusion Network for Alzheimer Disease Classification with Causal Regional Validation

arXiv:2609.34520v1 Announce Type: new Abstract: Deep learning models for Alzheimer disease (AD) classification routinely report near-perfect discrimination, yet few are shown to rest on AD-relevant ne

EviSplat: Preserving Multi-View Evidence in 3D Gaussian Splatting for Open-Vocabulary Segmentation

arXiv:2609.34853v1 Announce Type: new Abstract: Open-vocabulary 3D scene understanding enables object localization and segmentation from free-form text queries without a fixed category vocabulary. Man

Evolution of fairness in multi-objective reinforcement learning framework

arXiv:2609.34114v1 Announce Type: new Abstract: Fairness, as a fundamental social norm, continues to pose a longstanding puzzle regarding its emergence. Traditional game-theoretic models largely rely

Tutorials

Evolving Dexterous Robots from Scratch

arXiv:2609.33101v1 Announce Type: cross Abstract: Little is known about how to manually design agents capable of dexterous manipulation. Some design principles have been inferred from close examinatio

tutorialsarxiv-cs-lg

EvolvingAvatar: Interactive 3D Head Generation That Adapts as Conversations Unfold

arXiv:2609.35616v1 Announce Type: new Abstract: Interactive 3D head generation requires coordinated speaking and listening motion that responds to an evolving conversation. Existing generators use inc

Agents

ExcavaTwin: Training-Free Geometry-Guided Semantic Elevation Mapping for Autonomous Excavation

arXiv:2609.34719v1 Announce Type: new Abstract: Autonomous excavation requires a spatial representation that jointly captures terrain geometry and task-relevant semantics. Existing excavation mapping

agentsarxiv-cs-ro

ExpertoRhythm: Morphology-Aware Learning for Waveform Reconstruction and Cuffless Blood Pressure Estimation from Single-Channel PPG

arXiv:2609.34146v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring from photoplethysmography (PPG) has strong potential for wearable health and telemonitoring, but accu

Explaining Hyperbolic Neural Networks via Geometry-Aware Relevance Propagation

arXiv:2609.35128v1 Announce Type: new Abstract: Hyperbolic neural networks introduce geometric operations that require explicit treatment in relevance propagation. Equivalent geometric realizations ca

Exterior complex scaling enables physics-informed neural networks for quantum scattering

arXiv:2602.04553v2 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful tool for solving differential equations, yet their application to nuclear scatteri

Extremely Fast and Compact Binary Graph Representations via Randomized Operator Sketching

arXiv:2609.32641v1 Announce Type: new Abstract: Graph neural networks typically rely on dense, floating-point node representations, which can impose substantial memory and computational costs. Binary

Eyes on the Road: A Naturalistic Comparison of MTW Rider Gaze in Urban Indian Traffic

arXiv:2609.33811v1 Announce Type: new Abstract: Motorized two-wheelers (MTW) dominate Indian roads but remain underrepresented in driver behavior research. This study presents the first large-scale an

safetyarxiv-cs-cv

EyeVQA: Benchmarking Ophthalmic Vision-Language Models from Recognition to Spatial Grounding

arXiv:2609.32352v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown increasing potential for medical image understanding, yet their capabilities in ophthalmic imaging remain insuf

f-FUM: Federated Unlearning via min--max and f-divergence

arXiv:2602.06187v2 Announce Type: replace Abstract: Federated learning (FL) enables collaborative training while keeping raw data on clients. Deletion requests and the discovery of poisoned data creat

F4R: Failure-Driven Recognition, Reconstruction, Refinement, and Redeployment for Continual Robot Self-Improvement

arXiv:2609.35575v1 Announce Type: new Abstract: The real-world performance of current vision-language-action models is fundamentally constrained by the limited coverage of expert demonstrations and th

Hardware

Facial classification Using Hybrid Quantum Machine Learning

arXiv:2609.31915v1 Announce Type: new Abstract: Hybrid quantum methods have received limited study for resource-constrained facial biometrics. We present a hybrid quantum-classical facial recognition

hardwarearxiv-cs-cv

Fading Expert Guidance: Bridging Model-Based and Learning-Based Control for Abortable Autonomous Overtaking

arXiv:2308.09456v2 Announce Type: replace Abstract: Overtaking on two-lane roads is a safety-critical decision-making problem for autonomous vehicles, since oncoming traffic may force the ego vehicle

FailPatch: Failure Residual Patching for Vision-Language-Action Models

arXiv:2609.34175v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are typically adapted using successful demonstrations, which provide direct action supervision but rarely cover fa

FARE: Deep Reinforcement Learning For Fair Exposure Constrained Uncertainty Aware Financial Content Personalization

arXiv:2609.31890v1 Announce Type: new Abstract: Content personalization systems in financial services must ensure fair exposure across diverse offerings-a requirement driven by contractual obligations

Fast and Precise Learned Charged-Particle Trajectory Regression at the Large Hadron Collider

arXiv:2609.32479v1 Announce Type: new Abstract: We propose a training recipe that treats charged-particle trajectory parameter regression on high-energy physics detector data as a sequence-modeling ta

FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model

arXiv:2609.34354v1 Announce Type: new Abstract: Modeling resting-state functional magnetic resonance imaging (rs-fMRI) data is crucial for understanding brain-wide neural activity. However, traditiona

Fast Differentiable SVD on GPU via Polar Decomposition

arXiv:2609.32505v1 Announce Type: cross Abstract: We present a fully GPU-oriented SVD pipeline based on polar decomposition, motivated by iterative methods that rely solely on matrix multiplications,

Fast Learning Rate Transfer in Shallow Linear Networks at Growing Training Horizons

arXiv:2609.35029v1 Announce Type: new Abstract: Hyperparameter transfer across model width can substantially reduce the cost of tuning large neural networks, but its behavior when the training horizon

Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models

arXiv:2603.20212v2 Announce Type: replace-cross Abstract: Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Re

Faster Block-Diffusion Serving with Distribution-Free Risk Guarantees

arXiv:2609.33887v1 Announce Type: cross Abstract: Block-diffusion language models are served at hand-picked operating points, such as acceptance thresholds, buffer depth, schedule, checkpoint and prec

Tutorials

Feasible Flow Matching for Graph Reconstruction via Within-Sampling Primal-Dual Guidance

arXiv:2609.32980v1 Announce Type: new Abstract: Graph reconstruction from partial observations often comes with structural side information, such as degree bounds, triangle counts, or an edge-density

tutorialsarxiv-cs-lg

FEAT: Free energy Estimators with Adaptive Transport

arXiv:2504.11516v4 Announce Type: replace-cross Abstract: We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across

Feature Space Guidance for Breast Cancer Classification in DCE-MRI

arXiv:2609.32555v1 Announce Type: new Abstract: Dynamic contrast enhanced breast MRI (DCE-MRI) is a powerful clinical tool for breast cancer detection, providing high resolution anatomical detail toge

FeCoSplat: Feedback-Guided Compression for Feed-Forward 3D Gaussian Splatting

arXiv:2609.33330v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) enables efficient novel-view synthesis from sparse multi-view images, yet its representations remain costly to

Local Ai

Federated 3D Gaussian Splatting for Large-Scale Scene Reconstruction at Wireless Edge

arXiv:2609.32177v1 Announce Type: new Abstract: Three-dimensional (3D) Gaussian splatting (3D-GS) has emerged as a promising technique for large-scale scene reconstruction due to its high rendering ef

local-aiarxiv-cs-cv

Applications

Federated Computation of ROC and PR Curves

arXiv:2510.04979v2 Announce Type: replace Abstract: Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are fundamental analytical tools for evaluating classification models, prov

applicationsarxiv-cs-lg

Federated Subspace Guided Vision-Language-Action Policy Distillation for Non-IID Multi-Robot Manipulation

arXiv:2609.32239v1 Announce Type: cross Abstract: Federated learning offers a natural way for multiple robots to jointly improve manipulation policies without requiring centralized access to training

FedHV: Low-Overhead Hypervolume Weighting for Federated Multi-Objective Optimization

arXiv:2609.32790v1 Announce Type: new Abstract: Task-wise federated multi-objective optimization (FedMOO) trains a shared model for competing prediction objectives under heterogeneous data, partial pa

Agents

FedSysID: A Federated Approach to Sample-Efficient System Identification

arXiv:2211.14393v2 Announce Type: replace Abstract: We study the problem of learning a linear system model from the observations of M clients. The catch: Each client is observing data from a different

agentsarxiv-cs-lg

Feedback Makes Perfect: A Closed-Loop Framework for NL-to-STL Translation

arXiv:2609.33287v1 Announce Type: cross Abstract: Signal Temporal Logic (STL) enables rigorous verification and control of cyber-physical systems, but writing correct specifications requires expertise

researcharxiv-cs-ro

Feedback-Robust AI for Patient Knowledge Graphs

arXiv:2609.33248v1 Announce Type: new Abstract: Patient knowledge graphs from bedside monitoring should type their relations and state whether the data support their signs. In anesthesia and intensive

FestDPO: Few-step Generator Alignment with Direct Preference Optimization

arXiv:2609.34673v1 Announce Type: new Abstract: Few-step generative models can generate high-fidelity samples within a few function evaluations. Despite this efficiency, generated samples may not exhi

Fewer Tokens, More Self-Teaching: On-Policy Self-Distillation for Extreme Visual Token Reduction

arXiv:2609.32353v1 Announce Type: new Abstract: Visual token reduction is an effective way to accelerate multimodal large language models (MLLMs), but performance deteriorates rapidly under extremely

safetyarxiv-cs-cv