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Efficient Provably Private Classification with a Tabular Foundation Model

arXiv:2610.10068v1 Announce Type: new Abstract: Tabular data underpin prediction and decision-making in medicine, finance, government and science, but often contain sensitive individual-level informat

tutorialsarxiv-cs-lg

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Eigenvalues of the Hessian in Deep Learning: The Origin of Symmetry and Its Breaking

DGX agent

arXiv:2610.09919v1 Announce Type: new Abstract: Hessian spectra at trained models in deep learning exhibit a persistent pattern: eigenvalues organize into distinct clusters, including a large bulk nea

model-releasesarxiv-cs-lg

8 Oct 2026

Elastic’s AlertZero puts AI agents to work on security alert overload

Enterprise search and security company Elastic N.V. today introduced AlertZero, a team of specialized artificial intelligence agents for security operations. Built into Elastic Security, the agents ta

applicationssiliconangle

ELROND: Exploring and decomposing intrinsic capabilities of diffusion models

arXiv:2602.10216v2 Announce Type: replace Abstract: A single text prompt passed to a diffusion model yields a wide range of visual outputs determined solely by a stochastic process, leaving users with

EM-SNN: Efficiently Modulated Spiking Neural Network for Remote Sensing Image Dehazing

arXiv:2610.09275v1 Announce Type: new Abstract: Although spiking neural networks (SNNs) provide an energy-efficient alternative to artificial neural networks (ANNs), their application to remote sensin

Embedded Evaluation of Task Admission Coalescing in Decentralized Multi-Robot Systems

model-releasesarxiv-cs-ro

arXiv:2610.09187v1 Announce Type: new Abstract: Multi-robot task allocators in dynamic missions commonly admit newly released tasks immediately, potentially invoking allocation for each new arrival. W

emg2face: Expressive Facial Animation with High-Density Surface EMG

arXiv:2610.09304v1 Announce Type: cross Abstract: Facial movements convey subtle and important information that is critical for human social communication. Optical methods for face capture are difficu

Emo-Jev: Probabilistic Reasoning for Emotion Classification with Jev

arXiv:2610.08829v1 Announce Type: new Abstract: Jev offers an alternative interface for language understanding: given an input and predefined questions, it returns probabilistic decisions rather than

researcharxiv-cs-cl

EmphTTS: an emphasis-control TTS with reinforcement learning

arXiv:2609.27599v2 Announce Type: cross Abstract: Generating controllable and human-like emphasis remains an open challenge in text-to-speech, even when explicit emphasis control signals are provided

local-aiarxiv-cs-cl

Empirical Evidence for Simply Connected Decision Regions in Image Classifiers

arXiv:2605.06380v2 Announce Type: replace Abstract: The topology of a classifier's decision regions determines how inputs with the same predicted label can be connected and deformed without changing t

Empowering SMBs to do more with Gemini

model-releasesgoogle-cloud-ai

Today, we announced the new Gemini agent, your single, universal agent for work. For small and midsize businesses, with lean teams and margins, Gemini will be a critical tool for you to operate effici

Agents

End-to-End Autonomous Generation of Human Assembly Plans

arXiv:2610.09781v1 Announce Type: new Abstract: Turning a CAD design into an assembly plan is still largely done by hand, requiring engineers to reason about geometric feasibility, tool access, stabil

agentsarxiv-cs-ro

Energy-Efficient Gait Adaptation via Hierarchical Reinforcement Learning for Quadrupedal Locomotion Across Diverse Terrains

arXiv:2610.10297v1 Announce Type: cross Abstract: While energy efficiency is a critical objective for legged-robot locomotion control, achieving low energy consumption while maintaining robust perform

safetyarxiv-cs-lg

EngramEdit: Decoupled Knowledge Updates in LLMs through Conditional Memory

model-releasesarxiv-cs-cl

arXiv:2610.10533v1 Announce Type: new Abstract: Conditional memory architectures such as DeepSeek Engram use input n-grams to look up learned embeddings, expanding the capacity of large language model

Enhancing Multi-Region Stylization with Interior-Guided Boundary Repair

arXiv:2610.09706v1 Announce Type: new Abstract: Region-based neural style transfer enables fine-grained artistic control by allowing independent stylization of semantic image regions. However, composi

Enhancing Robotic Perception and Adaptability through Sensor Fusion and Origami-Inspired Designs

arXiv:2610.09828v1 Announce Type: new Abstract: Compact mobile robots must recover scene geometry under changing lighting and surface texture while working within tight payload and cost limits. We pre

researcharxiv-cs-ro

EntroPrefill: Renyi-Guided Context Pruning with Conditional Stability Guarantees for Retrieval-Augmented Generation

arXiv:2610.09757v1 Announce Type: new Abstract: Mid-prefill pruning can reduce the sequence processed by deeper transformer layers, but attention concentration alone does not certify that discarded co

Environmental Change Detection for Real-World Change Analysis

model-releasesarxiv-cs-cv

arXiv:2506.11481v2 Announce Type: replace Abstract: Scene Change Detection (SCD) evaluates changes using predefined query-reference (i.e., present-past) image pairs. However, this formulation overlook

Epistemic Policy Divergence in Multi-Turn LLM Contamination: A Protocol-Gradient Investigation

model-releasesarxiv-cs-cl

arXiv:2609.35308v2 Announce Type: replace Abstract: Large language models treat conversation history as unverified context, so false premises injected into prior turns can be adopted as fact, a failur

Estimating Model-Level Membership Inference Vulnerability Without Reference Models

arXiv:2510.19773v2 Announce Type: replace Abstract: Membership inference attacks (MIAs) have emerged as the standard tool for evaluating the privacy risks of AI models. However, state-of-the-art attac

Estimating Uncoded Crash Factors with Tabular Foundation and System One Models: Kumo Tabular and Jev

arXiv:2610.10321v1 Announce Type: cross Abstract: Road safety programs count the coded fields of police crash records, while the officer's narrative, which often records factors the fields omit, is ra

safetyarxiv-cs-lg

Evaluating Sequence Assembly Strategies for Differentially Private Synthetic Time-Series Forecasting

arXiv:2610.10222v1 Announce Type: new Abstract: Differentially private time-series generators commonly produce fixed-length synthetic windows, whereas downstream forecasting models often require long

Evaluating the Transfer of Co-Evolved Communication from 2D to 3D Simulation

arXiv:2610.09280v1 Announce Type: new Abstract: This work examines the transfer of a co-evolved communication mechanism between two robotic agents from a discrete two-dimensional (2D) simulator to a t

tutorialsarxiv-cs-ro

Evaluating Trajectory Features for Routing Final-Layer Attention

model-releasesarxiv-cs-lg

arXiv:2610.09272v1 Announce Type: new Abstract: Attention routing requires a signal that predicts the value of attention on the current prefix. We evaluate whether hidden-state extrapolation error, cu

Event-Aligned Visual Action Reasoning for World Action Models

arXiv:2610.09427v1 Announce Type: new Abstract: World-Action Models (WAMs) utilize future visual prediction as an intermediate reasoning process to guide action generation. However, existing WAMs typi

tutorialsarxiv-cs-cv

Evolutionary Architecture Search for Chlorophyll-a Prediction in Lakes using Sentinel-2

arXiv:2610.10496v1 Announce Type: cross Abstract: Small tabular datasets with expert-designed spectral features are the norm in operational Earth observation, and the networks applied to them are typi

Evolve on the Host, Predict on the Edge: Deploying Online Neuroevolutionary Architecture Search for Cross-sectional Stock Return Prediction

arXiv:2610.10038v1 Announce Type: cross Abstract: Accurate forecasting models are usually large, expensive to update online, and fixed in architecture once trained. We apply ONE-NAS, an online neuroev

EvoSignal: LLM-Guided Evolutionary Design of Modular Traffic Signal Control Programs

arXiv:2610.09563v1 Announce Type: new Abstract: Effective traffic signal control (TSC) requires policies that respond to changing traffic demand and network conditions while meeting different control

local-aiarxiv-cs-lg

Exact Dynamics and Finite-Sample Trajectory Recovery of Linear Recursive Feature Machines

arXiv:2610.09196v1 Announce Type: new Abstract: Recursive feature machines (RFMs) learn representations of data by alternating between fitting a predictor to a dataset and updating features of that pr

tutorialsarxiv-cs-lg

Executing Causal Structure Learning with Linear-Attention Transformers

model-releasesarxiv-cs-lg

arXiv:2610.10395v1 Announce Type: new Abstract: Transformers can execute algorithms on data given in their input. We ask whether they can do the same for causal discovery. We study a standard continuo

Agents

Expected Sample Complexity in Multi-Armed Bandits

arXiv:2610.09929v1 Announce Type: new Abstract: Sample complexity is a widely used metric in sequential decision-making problems, defined as the number of suboptimal decisions during the interaction b

agentsarxiv-cs-lg

Agents

ExperienceIndex: Artifact-Grounded Memory

arXiv:2610.10091v1 Announce Type: new Abstract: Knowledge-intensive tasks require answering many questions by reasoning about a shared corpus of artifacts (e.g., court cases, or scientific literature)

agentsarxiv-cs-cl

Hardware

Expert Coupling in MoE Pretraining: Reducing All-to-All Overhead with Correlated Placement and Token Shuffling

arXiv:2610.09372v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) layers replace the feed-forward block of a Transformer with E expert networks, and each token is routed to k of these experts.

hardwarearxiv-cs-cl

Explicit Geometric Chain-of-Thought for Vision-Language-Action in Autonomous Driving

arXiv:2610.10390v1 Announce Type: new Abstract: Vision-language-action~(VLA) models have emerged as a promising paradigm for autonomous driving. However, existing VLA models still suffer from a fundam

local-aiarxiv-cs-cv

Extreme Binary Classification: Extreme Value Theory for Extreme Constraint on False Negative

arXiv:2610.09984v1 Announce Type: cross Abstract: While binary classification is one of the most extensively studied problems in machine learning, the regime in which the goal is to learn a classifier

tutorialsarxiv-cs-lg

FaceKit: a Toolkit for Interpretable Facial Phenotyping, Synthetic Image Generation and Privacy Analysis in Rare Diseases

arXiv:2610.09288v1 Announce Type: cross Abstract: Many rare genetic diseases are associated with recognizable craniofacial features. However, traditional approaches for describing facial morphology re

Factorized Tactile Representation and Control for Sim-to-Real Manipulation

arXiv:2610.10510v1 Announce Type: new Abstract: Tactile sim-to-real learning must bridge simulated contact and device-specific sensor responses while preserving information needed for control. We prop

safetyarxiv-cs-ro

Fast and Robust Teach-and-Repeat Navigation Using MixVPR Visual Place Recognition*

arXiv:2610.09631v1 Announce Type: new Abstract: Teach-and-repeat navigation systems employing advanced visual place recognition techniques for localization exhibit key attributes for long-term mobile

applicationsarxiv-cs-ro

Fast Planning for Multi-object Multi-target Throwing

arXiv:2610.09224v1 Announce Type: new Abstract: Robot throwing has emerged as a promising technique for improving efficiency in logistics and warehouse automation, by enlarging the workspace and speed

applicationsarxiv-cs-ro

Hardware

Fault-tolerant foundation models

arXiv:2610.10311v1 Announce Type: new Abstract: Emerging computer hardware often trades reliability for energy efficiency; here we show that large-language models (LLMs) can be trained to tolerate thi

hardwarearxiv-cs-lg

FedRSPO+: A Heterogeneity-aware Algorithm for Decision-focused Federated Learning

arXiv:2610.09091v1 Announce Type: new Abstract: Decision-focused learning (DFL) trains predictive models for downstream optimization, but existing methods largely assume centralized data. In cross-sil

applicationsarxiv-cs-lg

FedSSMCoOp: SSM Encoders for light-weight Federated Prompt Learning for Few-shot Classification

arXiv:2610.09907v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown strong performance across a wide range of downstream vision tasks, thanks to the complementary information cont

safetyarxiv-cs-cv

Few Bits, One Law: Toward W2A4KV2

arXiv:2610.09202v1 Announce Type: cross Abstract: Extreme low-bit LLM compression is most challenging when weights, activations, and KV caches are quantized together: their distributions differ, and q

local-aiarxiv-cs-cl

Few-Shot Learning for Personalised Automated Pain Assessment

model-releasesarxiv-cs-lg

arXiv:2610.09692v1 Announce Type: new Abstract: Pain perception varies substantially across individuals, making it difficult for population-based classifiers to generalise across all subjects in a dat

Finding the Right Balance: Relevance and Diversity in LLM Retrieval

arXiv:2610.09412v1 Announce Type: cross Abstract: Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves re

applicationsarxiv-cs-cl

Finite-Sample Approximation of Hessian-Guided Perturbed Wasserstein Gradient Flows

arXiv:2610.10218v1 Announce Type: new Abstract: Wasserstein gradient flow extends gradient descent to probability measures. Its Hessian-guided perturbed variant (PWGF) adds Gaussian perturbations to e

local-aiarxiv-cs-lg

FinVector-Market-4B: A Controlled Study of LoRA Adaptation for Structured Financial Tasks

model-releasesarxiv-cs-cl

arXiv:2610.08882v1 Announce Type: cross Abstract: FinVector-Market-4B adapts Qwen/Qwen3.5-4B with rank-16 LoRA on a 22,000-example corpus for structured financial tasks. We evaluate the base and adapt

FlashNeRD: Performance-First Contact-Rich Neural Robot Dynamics

arXiv:2610.09130v1 Announce Type: new Abstract: Compared with analytical physics, learned dynamics models promise robot simulation that is faster, inherently differentiable, and easily adaptable to re

safetyarxiv-cs-ro