Search: “framework”

GaussPDE: Graph-Based Partial Differential Equation-Driven Rendering for 3D Gaussian Splatting

arXiv:2609.27264v1 Announce Type: new Abstract: We present GaussPDE, a framework that injects physically structured partial differential equation (PDE) dynamics into pretrained 3D Gaussian scenes with

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GLASS: Architecture-Tuned, Composable, Device-Side Linear Algebra for Edge Robotics and Beyond

DGX agent

arXiv:2609.28179v1 Announce Type: new Abstract: GPU robotics lacks the reusable numerical infrastructure of mature CPU stacks, instead relying on compiler frameworks that introduce overhead or repeate

model-releasesarxiv-cs-ro

24 Sept 2026

GLoTouch: Global-to-Local Haptic Perception Using a Parallel Gripper for Object Search, Recognition, and Grasping Without External Vision

arXiv:2609.27695v1 Announce Type: new Abstract: Perceiving objects in the environment is a fundamental capability of autonomous robots. In dark or low-light environments, external cameras often fail t

local-aiarxiv-cs-ro

Image Denoising Using Lower Semi-Frames

arXiv:2609.27893v1 Announce Type: cross Abstract: A blind image denoising framework based on an infinite directional lower semi-frame (DLSF) is proposed for additive white Gaussian noise. The model em

Information Capacity of Generative Video Compression: Quantifying the Rate-Compute Exchange at Identical Quality

arXiv:2609.27493v1 Announce Type: new Abstract: Under the AI Flow framework, communication networks distribute intelligence across devices, edge servers, and clouds, and computation at the receiver be

KATOsuper: Surrogate-accelerated neural topology optimization with sensitivity-consistent Fourier neural operators

model-releasesarxiv-cs-ai

arXiv:2609.27216v1 Announce Type: cross Abstract: Topology optimization (TO) remains computationally intensive due to repeated finite element analysis (FEA) evaluations required at each iteration. Whi

Learning Expressive Humanoid Locomotion from Monocular Runway Videos for Robot Fashion Shows

arXiv:2609.27003v1 Announce Type: new Abstract: Runway walking requires coordinated control of posture, stride, foot placement, and whole-body motion to effectively present clothing and convey a disti

safetyarxiv-cs-ro

NeuralSRNF: Neural Square Root Normal Fields for the Statistical Shape Analysis and Generation of Nonrigid 3D and 4D Objects

arXiv:2609.27728v1 Announce Type: new Abstract: We introduce NeuralSRNF, a novel framework for the statistical shape analysis and generation of genus-zero 3D and 4D objects that undergo nonrigid defor

Resource-Efficient Distributed Recursive Gaussian Processes

model-releasesarxiv-cs-lg

arXiv:2609.26979v1 Announce Type: new Abstract: Gaussian processes (GPs) provide a flexible framework for learning unknown functions from noisy measurements while quantifying predictive uncertainty, m

Sparse-Observation Atmospheric Thermal Forecasting with Physics-Informed Neural Networks for Climate-Aware Digital Twins

arXiv:2609.27290v1 Announce Type: new Abstract: Short-horizon forecasts of atmospheric temperature are needed to support climate-aware digital-twin systems, but such forecasts must be produced where t

researcharxiv-cs-ai

The Capability Manifold and ML Scaling Laws

arXiv:2609.27588v1 Announce Type: cross Abstract: Existing machine learning (ML) scaling laws relate predictive loss to compute, model parameters, and data. However, as models are increasingly deploye

agentsarxiv-cs-ai

A Decentralized Partially Observable Team Decision Methodology with Delayed Information Sharing

arXiv:2609.26783v1 Announce Type: cross Abstract: We study decentralized partially observable team decision problems with low-rank latent dynamics and unknown system models. The proposed framework com

safetyarxiv-cs-lg

Agensh: Scaling Organizational Intelligence to 1,024 Agents

model-releasesarxiv-cs-cl

arXiv:2609.26781v1 Announce Type: new Abstract: A multi-agent system can reduce latency on complex tasks by executing work concurrently. Several pioneering harness frameworks support multi-agent syste

Benchmarking Robots for Everyday Environments: From Lab Experiments to Real-World Operations

arXiv:2609.26490v1 Announce Type: new Abstract: This study introduces an interdisciplinary framework for benchmarking robots deployed in public environments, addressing the gap between traditional lab

safetyarxiv-cs-ro

Combining Hierarchical Cognitive Process with Process Supervision for Interpretable Scene Safety Understanding

model-releasesarxiv-cs-cl

arXiv:2609.26399v1 Announce Type: new Abstract: Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning di

DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes

arXiv:2609.26426v1 Announce Type: new Abstract: Finite Element Analysis (FEA) is widely used for transient mechanical simulations, but its high computational cost limits real-time and high-resolution

researcharxiv-cs-lg

Explanation-Guided Medical Named Entity Recognition with Stability and Boundary Awareness for Atopic Dermatitis

arXiv:2606.22886v2 Announce Type: replace Abstract: Objective: This study aims to improve the reliability and robustness of medical named entity recognition (NER) in Chinese atopic dermatitis (AD) cli

local-aiarxiv-cs-cl

From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale

model-releasesarxiv-cs-ai

arXiv:2609.22719v1 Announce Type: cross Abstract: Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration

GameDirector: Decoupling Gameplay Logic from Rendering for Player-Configurable Game World Models

arXiv:2609.25652v1 Announce Type: new Abstract: Recent game world models support realistic visual simulation and interactive gameplay based on player inputs. However, they typically learn environment

agentsarxiv-cs-cv

GRIP: Gaussian Rendering as a Cross-Modal Bridge for Image-to-Point Cloud Registration

arXiv:2609.25966v1 Announce Type: new Abstract: This paper introduces GRIP, a pose-conditioned refinement framework for pixel-to-point matching and 2D to 3D registration. Given an initial coarse pose

Tutorials

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

tutorialsarxiv-cs-lg

Interpretable AI plus Handheld, Portable Retinal Photographs: A Low-Cost Glaucoma Screening Solution for West Africa

arXiv:2609.25697v1 Announce Type: new Abstract: Purpose: To develop and evaluate an interpretable artificial intelligence (AI) framework for glaucoma screening from low-cost portable, handheld retinal

IntLawNER: A Named Entity Recognition Dataset and Benchmark in International Law

model-releasesarxiv-cs-ai

arXiv:2609.22529v1 Announce Type: new Abstract: International law provides the normative framework through which states coordinate action, regulate armed conflict, and protect human rights, yet its te

Knowledge Pull Requests for Continual Document Authoring

arXiv:2609.26634v1 Announce Type: new Abstract: We introduce Knowledge Pull Requests (KPRs), a framework for continual document authoring that makes each change interpretable. Documents require ongoin

researcharxiv-cs-cl

LazyAgent: Demand-Driven Materialization and Physical Optimization of Agentic Programs

arXiv:2609.23058v1 Announce Type: new Abstract: Current agent runtimes that plan before acting generally execute a step once it becomes ready. We present LazyAgent, a unified execution framework for a

agentsarxiv-cs-ai

Real-time autonomous magnetic microrobot navigation across dynamic and biologically relevant environments

arXiv:2509.05500v2 Announce Type: replace Abstract: Autonomous microrobots could enable minimally invasive interventions in confined biological environments, but their operation requires real-time nav

agentsarxiv-cs-ro

Recidivism Prediction, Peer Effect Estimation, and Prediction-Powered Inference with LLM Text Measures

arXiv:2509.20634v3 Announce Type: replace-cross Abstract: We provide a new framework for estimating peer effects when outcomes are multivariate behavioral measures derived from written text using an L

researcharxiv-cs-ai

Robust Photoplethysmography Signal Denoising via Mamba Networks

arXiv:2510.11058v2 Announce Type: replace Abstract: Photoplethysmography (PPG) is widely used in wearable health monitoring, but its reliability is often degraded by noise and motion artifacts, limiti

Sampling at intermediate temperatures is optimal for training large language models in protein structure prediction

model-releasesarxiv-cs-lg

arXiv:2603.29529v2 Announce Type: replace-cross Abstract: Using a statistical mechanics framework, we investigate the parameter space of transformer models trained on protein sequence data. We sample

Vision-based Underwater Formation Control With Input Saturations via Barrier Lyapunov Functions

arXiv:2609.25917v1 Announce Type: new Abstract: In this work, we propose a communication-free framework for vision-based formation control of fully actuated underwater robots subject to sensing constr

researcharxiv-cs-ro

Adversarially Robust PAC Learning with Optimal VC Rates

arXiv:2609.24260v1 Announce Type: cross Abstract: We study the problem of adversarially robust PAC learning. In this framework, the learner observes independent samples from an unknown distribution ov

researcharxiv-cs-lg

Ananke: Contractive Torus Attractor Networks

model-releasesarxiv-cs-cv

arXiv:2609.24737v1 Announce Type: new Abstract: We introduce Ananke, a representation-learning framework that scaffolds latent representations onto a structured product-torus prior, and its flagship v

Augmented Hypothesis Testing with Persona-Based LLM Simulations

arXiv:2609.24629v1 Announce Type: new Abstract: A/B testing requires large sample sizes, long timelines, and significant costs. When auxiliary predictions of experimental outcomes are available from m

Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation

arXiv:2609.22162v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generation i

local-aiarxiv-cs-cl

CLOOPD: Closing the Learner Loop in On-Policy Distillation

arXiv:2609.24141v1 Announce Type: new Abstract: On-policy distillation (OPD) pays twice for each fresh batch: the student generates trajectories and a stronger teacher scores them. Existing methods im

safetyarxiv-cs-lg

Contrastive Siamese Representation Learning for Predictive Maintenance of Electrical Submersible Pumps

arXiv:2609.22360v1 Announce Type: new Abstract: Electrical submersible pumps (ESPs) are essential in offshore oil production, where unexpected failures can result in significant operational and financ

Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models

arXiv:2411.05005v2 Announce Type: replace Abstract: Beyond high-fidelity image synthesis, diffusion models have recently exhibited promising results in dense visual perception tasks. However, most exi

Ev-YOLO: Uncertainty-Aware Object Detection via a Unified Evidential Formulation

arXiv:2609.24668v1 Announce Type: new Abstract: Reliable uncertainty estimation is essential for deploying object detectors in autonomous systems operating in uncertain environments. Evidential Deep L

agentsarxiv-cs-cv

Explainable Predictive Condition-based Maintenance of Naval-Propulsion Systems using Fuzzy Logic

arXiv:2609.24250v1 Announce Type: new Abstract: The shipping industry has a significant impact on the global economy, emphasizing the need for operational availability and safety through the use of ef

safetyarxiv-cs-lg

FedMust: Semi-supervised Multi-task Student-Teacher Federated Learning for Multi-organ CT Segmentation

arXiv:2609.24627v1 Announce Type: new Abstract: Multi-organ segmentation using deep learning requires large amounts of annotated patient data; however, institutions often lack sufficiently large and d

local-aiarxiv-cs-cv

Financial Language Models as Applied Artificial Intelligence Systems for News-Based Trading under Market Frictions

arXiv:2609.23703v1 Announce Type: new Abstract: Financial language models can transform unstructured firm-specific news into structured decision signals, but financial AI research lacks an integrated

researcharxiv-cs-cl

FRAMES: Failure Recovery And Monitoring of Embodied Skills for Humanoid Loco-Manipulation

arXiv:2609.22538v1 Announce Type: new Abstract: Large language model (LLM) planners can decompose natural-language instructions and select reusable robot skills, but choosing the correct skill does no

agentsarxiv-cs-ro

Tutorials

From Content Generation to Learning Support: Pedagogy-Guided Generative Video Tutors for STEM Learning

arXiv:2609.24083v1 Announce Type: new Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than su

tutorialsarxiv-cs-cl

Glass-Box Deep Learning for FDIA Detection in Nonlinear Automatic Generation Control: A Kolmogorov-Arnold Network Approach

model-releasesarxiv-cs-lg

arXiv:2509.05259v2 Announce Type: replace Abstract: Automatic Generation Control (AGC) plays a critical role in maintaining power balance across multi-area power systems. However, its complete relianc

Heterogeneous Robot Collaboration in Unstructured Environments with Grounded Generative Intelligence

arXiv:2510.26915v2 Announce Type: replace Abstract: While heterogeneous teams have typically been designed for well-specified missions with known semantics, generative intelligence, i.e., large langua

applicationsarxiv-cs-ro

Hierarchical Aggregation of Semantic Uncertainty in 3D Scene Graphs

arXiv:2609.22351v1 Announce Type: new Abstract: Open-vocabulary 3D Scene Graphs (3DSGs) ground each object node in a vision-language embedding, yet they record every entry as equally certain, so a rob

Inductive Graph Representation Learning with Quantum Graph Neural Networks

arXiv:2503.24111v4 Announce Type: replace-cross Abstract: Graph Neural Networks (QGNNs) offer a promising approach to combining quantum computing with graph-structured data processing. While classical

Learning-Based 3D Reconstruction of Power Networks from Aerial Point Clouds

arXiv:2609.23915v1 Announce Type: cross Abstract: This paper presents an end-to-end framework for reconstructing overhead power utility network topology and extracting span-level physical metadata fro

applicationsarxiv-cs-cv