Search: “evaluation”

arXiv:2609.06131v1 Announce Type: cross Abstract: Environmental identification in wireless sensing is essential for 6G integrated sensing and communication (ISAC) systems to achieve reliable situation

applicationsarxiv-cs-lg

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Imaginative World Modeling with Scene Graphs for Embodied Agent Navigation

DGX agent

arXiv:2508.06990v2 Announce Type: replace Abstract: Semantic navigation requires an agent to navigate toward a specified target in an unseen environment. Employing an imaginative navigation strategy t

agentsarxiv-cs-ro

9 Sept 2026

Impact of canny edge detection preprocessing on performance of machine learning models for Parkinson's disease classification

arXiv:2609.07408v1 Announce Type: cross Abstract: This study investigates the classification of individuals as healthy or at risk of Parkinson's disease using machine learning (ML) models, focusing on

Improving Multivariate Time Series Classification with Class-Wise Training and Model Aggregation

arXiv:2609.07493v1 Announce Type: new Abstract: In this paper, we propose a class-wise dimension (channel) selection framework for Multivariate Time Series Classification (MTSC). Rather than applying

Local Ai

Information-Guided Safe Reinforcement Learning for Autonomous Gas Source Localization using sUAS

arXiv:2609.05569v1 Announce Type: new Abstract: The autonomous localization of fugitive gas emissions using small Unmanned Aircraft Systems (sUAS) constitutes a fundamentally ill-posed inverse problem

local-aiarxiv-cs-ro

Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning

arXiv:2609.05946v1 Announce Type: new Abstract: Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have

Introducing HALC: A general pipeline for the systematic and reliable construction of prompts for automated coding with LLMs in the computational social sciences

arXiv:2507.21831v2 Announce Type: replace-cross Abstract: LLMs are seeing widespread use for task automation, including automated coding in the social sciences. However, even though researchers have p

Introductory Notes on Learning^2

arXiv:2609.06546v1 Announce Type: cross Abstract: Although machine learning can be used to predict the evolution of physical systems from data, a formulation that learns only the system state at each

Hardware

Inverse Digital Marbling: Recovering Gesture Programs with a Replay Adjoint

arXiv:2609.08722v1 Announce Type: cross Abstract: Pigment deposition in paper marbling displaces the pattern already present, coupling the appearance of each gesture to later actions. We recover execu

hardwarearxiv-cs-cv

JEDI: JEPA-to-Edge Distillation for Efficient Cropland Segmentation from Satellite Imagery

arXiv:2609.07915v1 Announce Type: new Abstract: Large vision models provide useful representations for remote-sensing segmentation but are often too expensive for deployment at the satellite or field

Joint-Conditioned Stereo Surface Reasoning for Interaction Field Estimation

arXiv:2609.06955v1 Announce Type: new Abstract: Predicting hand--object interaction fields requires locating the nearest object-surface point for each hand joint, often from small and partially occlud

Knowledge-Guided Vision-Language Inference for Image-Based Urban Flood Depth Estimation

arXiv:2509.04772v2 Announce Type: replace Abstract: Timely floodwater depth estimates support road accessibility assessment and emergency response during urban flooding. Supervised vision methods ofte

Latent-to-Latent Flow for Volumetric Stochastic Segmentation

arXiv:2609.07460v1 Announce Type: new Abstract: Uncertainty arising from inter-observer variability in medical image segmentation plays an important role in developing treatment plans. Research in thi

LatentFM: A Latent Flow Matching Approach for Generative Medical Image Segmentation

arXiv:2512.04821v4 Announce Type: replace Abstract: Generative models have achieved remarkable progress with the emergence of flow matching (FM). It has demonstrated strong generative capabilities and

Learning Subgroup Relations Using Siamese Graph Neural Networks

arXiv:2607.11140v2 Announce Type: replace Abstract: Determining whether one finite group is isomorphic to a subgroup of another is a fundamental problem in computational group theory. In this work, we

Learning to build covering structures with continuous adjustments

arXiv:2609.08669v1 Announce Type: cross Abstract: Robotic construction offers the potential to use materials more efficiently and create complex geometries, but current methods rely on rigid, high-pre

Local Ai

Likelihood-Based Unsupervised Anomaly Detection in CMS Dijet Events

arXiv:2609.06686v1 Announce Type: cross Abstract: We present an unsupervised search for anomalous dijet events in proton--proton collision data using neural spline flow density estimation. A normalizi

local-aiarxiv-cs-lg

LLM-Aided Design for Manufacturing: A Multi-Agent System for Intent-Preserving Redesign of CAD for Improved Manufacturability

arXiv:2609.05559v1 Announce Type: cross Abstract: We introduce autonomous, intent-preserving Design for Manufacturing (DFM) redesign of CAD parts: given an engineer's CAD model, the method returns a v

Local gradient neural operator

arXiv:2609.07752v1 Announce Type: new Abstract: Field temporal prediction and source identification constitute canonical problems in dynamical systems. Conventional approaches to these problems depend

Agents

Memory in Deep Time-Series Models

arXiv:2609.06006v1 Announce Type: new Abstract: Deep learning for time series has progressed through successive architectural paradigms, from recurrent networks and transformers to structured state-sp

agentsarxiv-cs-lg

MetaKV: Adaptive KV Cache Compression for Constrained LLM Inference

arXiv:2609.07966v1 Announce Type: new Abstract: Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (LLM) inference, particularly for long-conte

Mind-to-Face: Neural-Driven Photorealistic Avatar Synthesis via EEG Decoding

arXiv:2512.04313v2 Announce Type: replace Abstract: Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-

Minimizing the Effect of Sleep Deprivation in the Forward-Forward Algorithm

arXiv:2609.06042v1 Announce Type: new Abstract: This paper addresses the challenge posed by sleep deprivation in the Forward-Forward algorithm, where separating the two passes in this algorithm and im

MM-SVGEdit: A Multimodal-Driven SVG Editing for UI Design

arXiv:2609.06116v1 Announce Type: cross Abstract: In the field of UI design, Scalable Vector Graphics (SVG) is widely used as a design medium. However, traditional SVG editing techniques have high ent

MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control

arXiv:2609.06251v1 Announce Type: new Abstract: Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on

safetyarxiv-cs-cv

Modal Logic Neural Networks

arXiv:2512.03491v3 Announce Type: replace Abstract: Neural Networks are indispensable to natural sciences and society. Their impact extends from applications in public health to workforce productivity

ModularPhaseNet: Finite-Cyclic Phase Geometry for Computable Semantic Hierarchy, Direction, and Context Consistency in Standard Transformers

arXiv:2609.06000v1 Announce Type: cross Abstract: We propose ModularPhaseNet, a classical and integer-computable discretization of the continuous complex phase geometry introduced in QuantumPhaseNet.

MOLE: Detecting Insider Threats in AI Agents

arXiv:2609.06966v1 Announce Type: new Abstract: Model misalignment, prompt injection, or operator misuse could lead AI agents operating frontier-lab accounts to exfiltrate model weights, poison traini

Local Ai

Moment-Matching Probabilistic Data Association for Optimization-Based SLAM

arXiv:2609.05941v1 Announce Type: new Abstract: Optimization-based simultaneous localization and mapping (SLAM) makes it possible to reduce accumulated navigation errors of sensing platforms by return

local-aiarxiv-cs-ro

Monocular Visual Odometry without Calibration or Test-time Optimization

arXiv:2510.03348v4 Announce Type: replace Abstract: The most accurate monocular visual odometry systems require known camera intrinsics, refine their estimates with test-time optimization, and recover

safetyarxiv-cs-cv

MorphoOrgaAgent: A Foundation-Model-Based Multi-Agent System for Autonomous Organoid Analysis

arXiv:2609.08696v1 Announce Type: cross Abstract: Organoids are three-dimensional tissue models whose morphology provides important insights into tumor development, disease progression, and drug testi

MRI-Guided Reslice-Refined Cross-Slice SDF Reconstruction of the Left Ventricle from Cardiac MRI with Sparse Axial Supervision

arXiv:2609.08148v1 Announce Type: new Abstract: Reconstructing a three-dimensional left-ventricular (LV) endocardial surface from cardiac magnetic resonance (CMR) data is challenging when supervision

safetyarxiv-cs-cv

Multi-bounce Drum Roll with Optimized Active Tricks to Leverage Soft Embodiment

arXiv:2609.08490v1 Announce Type: new Abstract: This paper presents a soft robotic drummer for accurate and efficient drum rolls. High-frequency drum rolls require the 'multi-bounce technique,' where

researcharxiv-cs-ro

Multi-Fidelity Physics-Informed Neural Networks with Bayesian Uncertainty Quantification and Adaptive Residual Learning for Efficient Solution of Parametric Partial Differential Equations

arXiv:2602.01176v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding physical

Multi-History-Step SDE Inversion for Image Editing with Superior Regional Awareness

arXiv:2609.06602v1 Announce Type: new Abstract: In recent years, diffusion stochastic differential equation (SDE) inversion and inversion-free methods have become prevalent for training-free image edi

Multi-label versus multi-class classification of blood cells and their aggregates in microfluidic channels

arXiv:2609.07410v1 Announce Type: new Abstract: Deformability cytometry (DC) is a type of imaging flow cytometry, which uses a camera-equipped device to measure cellular stiffness in addition to other

Applications

Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling

arXiv:2609.09062v1 Announce Type: new Abstract: We present a real-world case study of multi-task learning (MTL) for temporal process modeling from limited data with temporally sparse labels. Specifica

applicationsarxiv-cs-lg

Multiple Myeloma Lesion Segmentation on Whole-Body Diffusion-Weighted Imaging via Efficient Anatomical Anticipation and Multimodal Confirmation

arXiv:2609.06165v1 Announce Type: new Abstract: Whole-body diffusion-weighted imaging (WB-DWI) is widely used for multiple myeloma (MM) assessment, yet automated lesion segmentation remains challengin

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts

arXiv:2609.07009v1 Announce Type: cross Abstract: Multimodal continual learning has recently shown great potential for developing agents with human-like intelligence by continuously learning new tasks

NeuralLVC: Neural Lossless Video Compression via Masked Diffusion with Temporal Conditioning

arXiv:2604.03353v2 Announce Type: replace-cross Abstract: While neural lossless image compression has advanced significantly with learned entropy models, lossless video compression remains largely une

Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Best

arXiv:2609.07627v1 Announce Type: cross Abstract: AI agents sometimes act aligned when they infer they are being tested, and differently when not. We argue this is not an anomaly but what current trai

Applications

Not Just Oversmoothing: Detecting the Echo Chamber Effect in Graph Neural Networks

arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that

applicationsarxiv-cs-lg

Novel hybrid protein scaffold gap filling using weighted machine learning ensemble, beam search, and mass-constrained reranking

arXiv:2609.05436v1 Announce Type: cross Abstract: Protein scaffold gap filling is an important computational task in protein sequence reconstruction, where missing amino acid regions must be inferred

Novel Methods for Catheter and Guidewire Segmentation in X-ray Fluoroscopy under a Federated Learning Setting

arXiv:2609.06876v1 Announce Type: new Abstract: Endovascular procedures rely on real-time manipulation of thin instruments, catheters and guidewires, under X-ray fluoroscopy guidance, where accurate v

Observe Before You Alert: Adaptive Driver Alerting with Vision-Language Models

arXiv:2609.08130v1 Announce Type: new Abstract: Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is ris

Agents

One MLLM, One Call: Efficient Zero-Shot Vision-and-Language Navigation via Spatial-Aware Waypoints

arXiv:2609.06476v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate unseen environments by following natural langu

agentsarxiv-cs-cv

Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling

arXiv:2609.08172v1 Announce Type: cross Abstract: Slice sampling is a Markov chain Monte Carlo algorithm that draws its next state uniformly from a 'slice'---a super-level set of the target density fu