Search: “models”

Layered Risk Mapping for Autonomous Patient Transport in Expeditionary Medical Facilities

arXiv:2607.13497v1 Announce Type: new Abstract: In expeditionary medical facilities, routine patient transport imposes a compounding burden of personal protective equipment consumption, staff diversio

safetyarxiv-cs-ro

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Agents

Learning Engagement Assistant (LEA): Cross-Course Scalability and Classroom Evaluation of an Agentic AI Tutoring System

DGX agent

arXiv:2607.13370v1 Announce Type: cross Abstract: This paper is an extension of a paper presented at the ICAART 2026 conference, which introduced LEA (Learning Engagement Assistant), an adaptive AI tu

agentsarxiv-cs-ai

16 Jul 2026

Learning Physics-Guided Residual Dynamics for Deformable Object Simulation

arXiv:2607.13451v1 Announce Type: cross Abstract: Simulating deformable objects is essential for a wide range of robotic manipulation applications, yet accurately predicting their dynamics remains cha

Local Redundancy: An Information-Theoretic Measure of Plasticity from Synthetic Memorization

arXiv:2607.13432v1 Announce Type: new Abstract: Plasticity -- a neural network's ability to adapt to new tasks -- is critical for continual and transfer learning. Existing measures, such as effective

local-aiarxiv-cs-lg

Low-latency Event-based Object Detection with Spatially-Sparse Linear Attention

arXiv:2603.06228v2 Announce Type: replace Abstract: Event cameras provide sequential visual data with spatial sparsity and high temporal resolution, making them attractive for low-latency object detec

local-aiarxiv-cs-cv

Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling

arXiv:2607.13558v1 Announce Type: new Abstract: Urban region profiling constitutes a core problem in urban computing, supporting applications such as population estimation, economic assessment, and en

Multi-Dictionary Learning for Low Rank Sparse Coding

arXiv:2509.10033v2 Announce Type: replace Abstract: Sparse dictionary coding represents signals as linear combinations of a few dictionary atoms. It has been applied to images, time series, graph sign

tutorialsarxiv-cs-lg

Multimodal Assessment of Pancreatic Cancer Resectability Using Deep Learning

arXiv:2607.13826v1 Announce Type: cross Abstract: Accurate determination of pancreatic ductal adenocarcinoma (PDAC) resectability relies on evaluating how the tumor interacts with major peripancreatic

local-aiarxiv-cs-ai

Hardware

NanoGS: Training-Free Gaussian Splat Simplification

arXiv:2603.16103v2 Announce Type: replace Abstract: 3D Gaussian Splat (3DGS) enables high-fidelity, real-time novel view synthesis by representing scenes with large sets of anisotropic primitives, but

hardwarearxiv-cs-cv

Non-Expansive Two-Time-Scale Stochastic Approximation: A Fixed-Schedule One-Quarter Barrier and Bias-Corrected Acceleration

arXiv:2607.13414v1 Announce Type: cross Abstract: Non-expansive two-time-scale stochastic approximation is governed by a slow stochastic Krasnoselskii--Mann fixed-point iteration rather than by contra

safetyarxiv-cs-lg

Not All Retrievals are Useful: Cross-Attention for Input-Aware RAG in Time Series Forecasting

arXiv:2603.14709v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) enhances zero-shot time series (TS) forecasting by leveraging external knowledge bases, yet existing approaches

researcharxiv-cs-lg

Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows

arXiv:2607.13078v1 Announce Type: cross Abstract: LLMs are now proposed for fraud detection, scam investigation, content moderation, and other trust-and-safety workflows. Much of the public literature

safetyarxiv-cs-ai

Perfect Demo Makes Poor Teacher: Learning Robust Alignment from Critical Motion Segments

arXiv:2606.15587v2 Announce Type: replace Abstract: Expert demonstrations are widely assumed to be the gold standard for robot imitation learning. Yet for fine-grained manipulation such as insertion,

local-aiarxiv-cs-ro

Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

arXiv:2607.13073v1 Announce Type: new Abstract: Neuro-symbolic AI based on IFOL_B is a way to combine neural learning and symbolic reasoning to overcome limitations of purely neural systems (like lack

RADAR: Closed-Loop Robotic Data Generation via Semantic Planning and Autonomous Causal Environment Reset

arXiv:2603.11811v2 Announce Type: replace-cross Abstract: The acquisition of large-scale physical interaction data, a critical prerequisite for modern robot learning, is severely bottlenecked by the p

safetyarxiv-cs-ai

Reflecting Process Expertise in Procedural Material Generation

arXiv:2607.13318v1 Announce Type: new Abstract: Procedural material creation underpins applications in digital content creation, visual effects, and 3D asset design. Achieving high-quality results req

tutorialsarxiv-cs-cv

Self-Improving AI Coding Agents Through Accumulated Behavioral Rules: A Closed-Loop Framework

arXiv:2607.13091v1 Announce Type: cross Abstract: LLM-based coding agents repeat the same classes of mistakes across sessions because they lack a mechanism to retain corrections from human review feed

SemaDiff: Identifying Semantic-Changing Commits with Generated Code and Tests

arXiv:2607.13111v1 Announce Type: cross Abstract: Distinguishing semantic-preserving commits from changing ones remains an open challenge in software repository mining. While existing approaches detec

local-aiarxiv-cs-ai

STKAN: Kolmogorov-Arnold Networks for Spatio-Temporal Forecasting

arXiv:2607.13108v1 Announce Type: cross Abstract: Real-world traffic data exhibit heterogeneous spatial correlations and nonlinear temporal dynamics, posing substantial challenges for accurate spatio-

Stress-Sharing: A Bio-Inspired Approach to Decentralized Fault Repair in Modular Spacecraft

arXiv:2607.13444v1 Announce Type: new Abstract: Structural damage in modular spacecraft can disrupt mechanical and communication connectivity, reducing system capability. Existing approaches rely on r

local-aiarxiv-cs-ro

T3HG-Editor: Text-driven 3D Human Garment Editing with Body Priors Embedded in SMPL-X

arXiv:2607.13654v1 Announce Type: new Abstract: While 3D Gaussian Editing (3DGE) has seen substantial progress, text-driven 3D human garment editing remains largely underexplored. Existing 3DGE works

Task-Oriented Sensing and Covert Transmissions for Collaborative Multi-AUV Systems

arXiv:2607.13880v1 Announce Type: new Abstract: In underwater covert cooperative missions, autonomous underwater vehicles (AUVs) often cannot rely on active sonar to continuously obtain complete infor

local-aiarxiv-cs-lg

Task-Specific Feature Fusion Method for Multi-Task Affective Behavior Analysis

arXiv:2607.13986v1 Announce Type: new Abstract: The 11th Affective Behavior Analysis in-the-wild (ABAW11) Multi-Task Learning Challenge requires a unified system to predict valence-arousal, categorica

Track and Caption Any Motion: Open-Vocabulary Spatiotemporal Captioning via Trajectory-Conditioned Generation

arXiv:2512.10607v2 Announce Type: replace Abstract: We present TCAM (Track and Caption Any Motion), a generative framework that watches a video and with no text query and no region prompt decides what

safetyarxiv-cs-cv

Uniform Approximation of Functions with Asymmetric Growth and Decay by Deep Weighted Polynomials

arXiv:2506.21306v2 Announce Type: replace-cross Abstract: Functions that grow without bound on one side of the real line and decay to zero on the other cannot be approximated uniformly by ordinary pol

Video to All-in-focus Image Reconstruction Algorithm for Automated Microscopic Urinalysis

arXiv:2607.13601v1 Announce Type: cross Abstract: Microscopic urinalysis is a routine diagnostic test at hospitals. Recent studies have demonstrated the effectiveness of deep learning methods to autom

When Audio Separation Hurts Zero-Shot ASR: Evaluating SAM-Audio with Whisper on Bengali and English Speech

arXiv:2603.04710v2 Announce Type: replace-cross Abstract: Recent advances in automatic speech recognition (ASR) and speech enhancement have strengthened the common belief that cleaner audio should lea

When is the combined load identifiable from a stress-intensity profile? A coupled forward-inverse study on SIFBench finite-element data

arXiv:2607.13074v1 Announce Type: cross Abstract: This work studies the inverse problem of recovering the relative magnitudes of the tension, bending, and bearing loads acting on a crack from its stre

WNOJ-LIO: A White-Noise-on-Jerk Motion-Prior EKF for High-Dynamic LiDAR-IMU Fusion

arXiv:2607.13405v1 Announce Type: new Abstract: LiDAR-inertial odometry (LIO) is a key component of autonomous navigation, but high-dynamic driving exposes two coupled challenges: intra-scan motion di

agentsarxiv-cs-ro

A Longitudinal Analysis of Public Discourse on AI Ethics in Education Using Twitter Data

arXiv:2607.12295v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) and generative AI (GenAI) into education presents significant opportunities to enhance teaching

Accelerated Mixing Time of Randomized Hamiltonian Monte Carlo

arXiv:2607.12902v1 Announce Type: cross Abstract: We show the Randomized Hamiltonian Monte Carlo (RHMC) algorithm has accelerated mixing time guarantees for sampling from log-concave probability distr

researcharxiv-cs-lg

AgentCheck: A Reproduce-Intervene-Mitigate Workbench for LLM Agents over MCP

arXiv:2607.11098v2 Announce Type: replace-cross Abstract: Tool-using LLM agents are mostly evaluated assuming all tools work. When a tool times out, returns a week-stale value, or has its description

ANGLE: Angular Neural Generative Learning via Engression

arXiv:2607.12833v1 Announce Type: cross Abstract: Circular data, representing angles or directions, are frequently encountered in computer vision, biology, geology, and meteorology. Traditional regres

agentsarxiv-cs-lg

Atomic Units of X: The Compression Layer of Intelligence

arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog

Beyond Parallel Tracking: Interactive Multi-Feature Fusion Drives Semantic Reconstruction from Non-invasive Brain Recordings

arXiv:2607.12071v1 Announce Type: new Abstract: Continuous semantic reconstruction from non-invasive neural recordings remains limited by the representational mismatch between semantic feature spaces

safetyarxiv-cs-cl

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

arXiv:2607.12835v1 Announce Type: new Abstract: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, whe

safetyarxiv-cs-cl

ChartGenEval: Corruption-Tested Multi-Dimensional Feedback for Rhythm-Game Chart Generation

arXiv:2607.12857v1 Announce Type: cross Abstract: A generated rhythm-game chart need not reproduce one official note sequence: many note choices can fit the same song and difficulty. Reference-note ag

Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence

arXiv:2506.08121v2 Announce Type: replace-cross Abstract: We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and

safetyarxiv-cs-lg

Contrastive Joint-Embedding Prediction for Representation Learning in Structural MRI

arXiv:2607.11962v1 Announce Type: new Abstract: Self-supervised learning offers a compelling approach for medical imaging, where labeled data are scarce and acquisition costs are high. We present COJE

local-aiarxiv-cs-cv

CRC-HGD: A Histopathological Image Dataset for Grading Colorectal Cancer

arXiv:2607.12750v1 Announce Type: new Abstract: Colorectal cancer (CRC) is the third most common cancer worldwide and the second leading cause of cancer-related deaths globally, with approximately 1,9

Diversity-Enriched Option-Critic

arXiv:2011.02565v2 Announce Type: replace-cross Abstract: Temporal abstraction allows reinforcement learning agents to represent knowledge and develop strategies over different temporal scales. The op

tutorialsarxiv-cs-ai

Do You Remember? Toward Memory-Centric Multimodal AI

arXiv:2607.11919v1 Announce Type: cross Abstract: Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen v

Evidence-Grounded Verified Agentic Reasoning: A Path Toward Eliminating LLM Hallucination in Empirical Inference via Tool-Attested Kernel Proofs

arXiv:2607.12650v1 Announce Type: cross Abstract: Tool access alone does not make LLM empirical reasoning governable: accepted outputs need not descend from attested evidence, and accepted deductions

Expert Knowledge-driven Reinforcement Learning for Autonomous Racing via Trajectory Guidance and Dynamics Constraints

arXiv:2603.05842v2 Announce Type: replace Abstract: Reinforcement learning has demonstrated significant potential in the field of autonomous driving. However, it suffers from defects such as training

safetyarxiv-cs-ro

ExtraGS: Enhancing Endoscopic View Extrapolation via Diffusion-Guided 3D Gaussian Splatting

arXiv:2607.12785v1 Announce Type: new Abstract: Robot-assisted minimally invasive surgery (MIS) critically depends on reliable endoscopic perception for navigation and safety. However, conventional en

safetyarxiv-cs-cv

Fisher Rank Inflation: A Spectral Signature of Memorization under Label Noise

arXiv:2607.12438v1 Announce Type: new Abstract: Deep networks trained with label noise often learn clean structure before memorizing corrupted labels. We show that this transition leaves a spectral si

tutorialsarxiv-cs-lg

Flatness-Preserving Residual Learning for Real-Time Tight Quadrotor Formation Flight

arXiv:2607.12275v1 Announce Type: new Abstract: Quadrotors flying in tight formations are severely affected by turbulent aerodynamic interactions, such as downwash, that can cause catastrophic collisi

researcharxiv-cs-ro

From Geometric Recovery to Causal Validation: A Reproducible Audit of Sparse Autoencoder Features, from Superposition Geometry to Causal Inertness

arXiv:2607.12166v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are the standard for decomposing superposed neural representations into interpretable features, and evaluation relies predomi

safetyarxiv-cs-lg