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When Low Prediction Error Misleads Planning: Diagnosing Representation, Dynamics, and Decision Failures in Latent World Models

arXiv:2610.05550v1 Announce Type: new Abstract: The component that dominates a latent world model's prediction error need not be the one whose repair most improves action selection. We show this by co

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When the Cross-Silo Federation Goes Offline: Continual Learning for Site Onboarding with Limited Unlabeled Data

DGX agent

arXiv:2610.05598v1 Announce Type: new Abstract: An organization often holds too little labeled data to train a model that generalizes, and the records that would supply the rest sit with organizations

agentsarxiv-cs-lg

6 Oct 2026

When the noncommutative AM-GM inequality holds

arXiv:2610.04874v1 Announce Type: cross Abstract: In this note, we prove that the noncommutative AM-GM inequality holds if nge 2lceil m/2 rceil^2. The motivation comes from counterexamples constructed

When to Switch: Reliable Action-Chunk Extension for Vision-Language-Action Models

arXiv:2610.05719v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models serve as unified policies for robotic manipulation, yet their expensive inference forces robots to pause between pol

safetyarxiv-cs-ro

Where Does Jagged Competence Come From?

arXiv:2610.03831v1 Announce Type: new Abstract: Capable systems often show jagged competence: low average error alongside failures on particular inputs. We ask where it comes from in a task built from

Where Does the Semantic Gain Come From? A Reproduction and Extension of Semantic Knowledge-driven Contrastive Learning for Long-Tailed Recognition

arXiv:2610.04104v1 Announce Type: new Abstract: Semantic Knowledge-driven Contrastive Learning (SKCL) uses a language model to decide which classes are related, and pulls each image towards the protot

researcharxiv-cs-cv

Which Preferences to Train On? End-to-End Multi-Objective Alignment with an Adversarial Preference Distribution

arXiv:2610.04845v1 Announce Type: new Abstract: Aligning large language models (LLMs) with human values is important for safe, efficient, and beneficial AI deployment. However, human values are multif

safetyarxiv-cs-lg

Why Convolution Still Matters: Evaluating Inductive Biases in Cryospheric Image Classification

arXiv:2610.04073v1 Announce Type: new Abstract: Recent advances in attention-based deep learning have motivated their adoption for remote sensing image classification; however, their benefits for cryo

Why Subliminal Learning Needs So Much Data: A Noisy Inverse View through Steering Vector Recovery

arXiv:2610.04907v1 Announce Type: new Abstract: Subliminal learning lets a student inherit a teacher's behavioral trait from semantically unrelated data, yet published demonstrations typically require

WILLIE: A Unified Framework and Benchmark for Wound Classification, Segmentation, and Localization

arXiv:2610.05341v1 Announce Type: new Abstract: Chronic wound management affects over 8.2 million patients in the United States and imposes substantial clinical and economic burden. Clinical wound ass

Wiring Matters: Injection Topology and Initialization of Affordance Heads in Vision-Language-Action Policies

arXiv:2610.06318v1 Announce Type: new Abstract: Dense affordance supervision is an appealing auxiliary signal for vision-language-action (VLA) policies, yet naively co-training an affordance head can

Xaurora: Generative Weather Forecasting with Denoising Stochastic Interpolants from a Foundation Model Prior

arXiv:2610.06509v1 Announce Type: new Abstract: Deep learning has revolutionised weather forecasting in recent years, especially through atmospheric foundation models, which offer competitive skill fo

XS-VID: A Large-Scale Benchmark for Small Object Detection and Tracking in Videos

arXiv:2407.18137v2 Announce Type: replace Abstract: Small object detection and tracking in videos remain critical yet underexplored challenges in computer vision, particularly for applications such as

You May Be Running the Wrong Inception Crop

arXiv:2610.04147v1 Announce Type: new Abstract: A decade after its inception, Inception crop has become the standard crop-based data augmentation method for training deep vision models. Not only is it

Your Temporal Link Predictor Is Blind to Who Is Active: A Missing Factor That Transfers Across Models

arXiv:2610.04869v1 Announce Type: new Abstract: An interaction has two parts: someone decides to act, and then chooses whom to act on. Temporal link prediction has concentrated on the second, and we s

Your Unlearning Gives You Away: Identifying Erased Concepts in Diffusion Models

arXiv:2610.05601v1 Announce Type: new Abstract: Existing attacks on unlearned diffusion models assume that the erased concepts are known in advance and focus on recovering them. In practice, however,

ZeST: an VLM-based Zero-Shot Traversability Navigation for Unknown Environments

arXiv:2508.19131v3 Announce Type: replace-cross Abstract: The advancement of robotics and autonomous navigation systems hinges on the ability to accurately predict terrain traversability. Traditional

safetyarxiv-cs-cv

Applications

16-bit Precision of Convolutional Neural Networks on Microcontroller Units for 8-bit Costs

arXiv:2610.03402v1 Announce Type: new Abstract: To deploy deep neural networks on edge hardware, highly efficient inference schemes are necessary that retain high accuracy. This work presents W16A16,

applicationsarxiv-cs-lg

4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes

model-releasesarxiv-cs-ai

arXiv:2610.03715v1 Announce Type: cross Abstract: We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as execut

A Benchmark for Spatially Grounded Gesture Generation

arXiv:2610.03105v1 Announce Type: new Abstract: Communication in shared space interweaves verbal and non-verbal signals, and pointing gestures anchor language to the environment: 'put the cup on that

A Composable AI-Accelerated Iterative Solver for 3D-IC Thermal Modeling

arXiv:2610.02461v1 Announce Type: new Abstract: Accurate thermal analysis of heterogeneous 2.5D/3D-IC packages is essential yet computationally prohibitive. A single full-package FEM simulation can ta

A Controlled Audit of Personal AI Memory for Rating Prediction

arXiv:2610.02764v1 Announce Type: new Abstract: In structured rating prediction, does a personal AI use historical item-rating associations, or mainly the user's rating tendencies? We audit this disti

A Fully Automatic Pipeline for 3D Dendrite Instance Segmentation in SBF-SEM

arXiv:2610.03332v1 Announce Type: new Abstract: Accurate three-dimensional (3D) reconstruction of individual dendrites in serial block-face scanning electron microscopy (SBF-SEM) is essential for quan

researcharxiv-cs-cv

A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs

arXiv:2610.02529v1 Announce Type: new Abstract: Syntactic ambiguity poses a persistent challenge for Arabic NLP, particularly in morphologically rich nominal constructions where multiple structu6ral i

researcharxiv-cs-cl

A Generative Model of Complex Networks Using Graphons and Neural Inverse Operators

arXiv:2610.02439v1 Announce Type: new Abstract: Generative graph models are central to understanding and simulating complex networks. However, existing approaches have complementary strengths and limi

A GHOST in Long-Horizon Agents: Governance Hazard from Overlooked Safety Constraints across Turns

model-releasesarxiv-cs-ai

arXiv:2610.02664v1 Announce Type: new Abstract: Long-horizon agents are now playing an increasingly significant role in assisting humans with complex problem-solving. However, it is exactly their exte

A Guideline-Augmented Multi-Agent Framework for Schema-as-Code Biomedical Named Entity Recognition

model-releasesarxiv-cs-cl

arXiv:2610.02970v1 Announce Type: new Abstract: Large language models (LLMs) have shown promising potential for biomedical named entity recognition (BioNER) through instruction following and in-contex

A hybrid CNN-adjoint optimization framework for reconstruction of viscoelastic tissue properties in magnetic resonance elastography

arXiv:2610.02634v1 Announce Type: cross Abstract: Magnetic resonance elastography (MRE) is a noninvasive imaging modality for quantifying the viscoelastic properties of soft tissues from shear wave pr

A Locally Penalized Cross-Estimate Federated Method with Guarantees for Constrained Personalized Learning

arXiv:2603.19617v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient framework for solving distributed optimization problems. Standard FL methods aggregate local up

local-aiarxiv-cs-lg

A Missing Latent, Not a Missing Simulator: Radius-Augmented Inference for Real JWST Retrieval

arXiv:2610.02245v1 Announce Type: cross Abstract: Amortized simulation-based inference (SBI), which is trained on radiative-transfer simulators, recovers exoplanet atmospheres accurately on synthetic

A Multi Method Importance and Performance Efficiency Analysis of Topological Metrics for Natural Visibility Graph Based Cyber Attack Detection

arXiv:2610.02342v1 Announce Type: new Abstract: Natural Visibility Graph (NVG) based analysis characterizes network traffic through topological descriptors reflecting different structural properties.

researcharxiv-cs-ai

A Near-Zero Monitor Readout Is Not Evidence of Behavioral Control

arXiv:2610.03458v1 Announce Type: new Abstract: Post-training with verifiable rewards can induce reward hacking, motivating the use of monitors within the training objective rather than solely for off

safetyarxiv-cs-ai

A Passive AI System for Verifying Physical State on Automated Liquid Handlers

arXiv:2610.02668v1 Announce Type: new Abstract: Automated liquid handlers execute digital protocols, but operators must assemble the deck and confirm that the physical setup matches the intended exper

researcharxiv-cs-ro

A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning

arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only

local-aiarxiv-cs-lg

A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition

arXiv:2504.03432v4 Announce Type: replace-cross Abstract: Solving (Stampacchia) variational inequalities (SVIs) is a foundational problem at the heart of optimization. However, this expressivity comes

Agents

A Simulation-Grounded Agentic VLM Framework for Wildfire Monitoring and Reporting

arXiv:2610.02451v1 Announce Type: new Abstract: Effective wildfire monitoring requires relating visual evidence to physical fire dynamics, yet real videos with synchronized physical annotations are sc

agentsarxiv-cs-cv

A Sobel-Gradient MLP Baseline for Handwritten Character Recognition

arXiv:2508.11902v4 Announce Type: replace Abstract: This study examines how much handwritten-character information is retained by a deliberately simple first-order edge representation. Instead of lear

researcharxiv-cs-cv

A Two-Stage Cascade for Near-Real-Time Forest Anomaly Detection from Sentinel-1 SAR Time Series

arXiv:2610.02763v1 Announce Type: new Abstract: Tropical forest monitoring is essential for global climate stability and biodiversity preservation. To address the urgent need for rapid, reliable detec

A Unified BERT-CNN-BiLSTM Framework for Simultaneous Headline Classification and Sentiment Analysis of Bangla News

arXiv:2511.18618v2 Announce Type: replace-cross Abstract: In our daily lives, newspapers are an essential information source that impacts how the public talks about present-day issues. However, effect

researcharxiv-cs-ai

A Unified Framework for Bayesian Data Assimilation with Generative Models and Observation Interpolants

arXiv:2610.03396v1 Announce Type: new Abstract: Bayesian data assimilation combines model forecasts with noisy observations, but sampling high-dimensional, non-Gaussian posteriors remains challenging.

safetyarxiv-cs-lg

A Unified Framework for Empowerment and Predictive Control

arXiv:2610.03563v1 Announce Type: new Abstract: Sampling-based model predictive control (MPC) is a powerful approach to trajectory optimization, but its performance depends on an informative cost func

safetyarxiv-cs-ro

A Vision-Language Model (VLM)-based Pipeline for End-to-End Procedural Modeling of Field-Grown Maize from Point Clouds

arXiv:2610.03468v1 Announce Type: new Abstract: Editable 3D models of field-grown crops support high-throughput phenotyping and in silico breeding trials, but building them from scanned point clouds r

Accurate Open-Loop Control of a Soft Continuum Robot Using Visually Learned Latent Dynamics

arXiv:2603.19655v2 Announce Type: replace Abstract: This work addresses open-loop control of a soft continuum robot (SCR) from video-learned latent dynamics. Visual Oscillator Networks (VONs) from pre

researcharxiv-cs-ro

Activation Sparsity with Weight Approximation for Faster LLM Decoding on Offloaded Weights

arXiv:2610.02598v1 Announce Type: new Abstract: Deploying LLMs on consumer-grade GPUs with insufficient memory to hold their weights can result in prohibitively slow inference, because decoding repeat

local-aiarxiv-cs-lg

Adaptive Mutual Distillation for Balanced Multi-Task Post-Training of Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.02856v1 Announce Type: new Abstract: Multi-task post-training of large language models (LLMs) aims to improve performance across tasks with unequal amounts of training data. Existing method

Adaptive Second-Order Solvers for Fast Stochastic Diffusion Sampling

arXiv:2610.03034v1 Announce Type: cross Abstract: Diffusion models rely on numerical solvers requiring time-discretization, which has a large influence on the tradeoff between sampling cost and qualit

researcharxiv-cs-cl

Adaptive Spectral-Koopman Dynamics Modeling for Temporal Domain Generalization

model-releasesarxiv-cs-ai

arXiv:2610.02822v1 Announce Type: cross Abstract: Temporal Domain Generalization (TDG) has emerged to address real-world streaming data with distribution shifts over time. However, existing methods ar

AdaStep: Adaptive Step Credit Weighting for Agentic Reinforcement Learning

arXiv:2610.03223v1 Announce Type: cross Abstract: Long-horizon LLM agents are typically trained with sparse outcome rewards, making trajectory-level objectives too coarse to distinguish the contributi

local-aiarxiv-cs-cl