Search: “framework”

Population Fidelity: Evaluating Population Representativeness in LLMs

arXiv:2609.36253v1 Announce Type: cross Abstract: Large language models (LLMs) show considerable potential in simulating human attitudes and preferences. Prior work finds that LLM-generated responses

safetyarxiv-cs-ai

30 Sept 2026

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Applications

ProAct-VLM: Pre-Failure Vision-Language Task Replanning with Continuous Perception Feedback

DGX agent

arXiv:2609.37681v1 Announce Type: new Abstract: Long-horizon robotic tasks are vulnerable to unexpected environmental changes that can render planned actions ineffective or unsafe. To address this, ro

applicationsarxiv-cs-ro

30 Sept 2026

Admissible Diffusion for Multimodal Interventional Trajectories

arXiv:2609.34433v1 Announce Type: new Abstract: Generating a plausible clinical trajectory does not establish what would happen under a different treatment. We present ADMIT, a framework combining irr

Back-Tracking from Clarity: Self-Learning to See Text from Afar

arXiv:2609.32477v1 Announce Type: new Abstract: We propose a self-supervised framework designed to enhance the capability of scene text detectors in identifying and recognizing text in scenarios where

Deep kernel hedging

arXiv:2609.34474v1 Announce Type: new Abstract: We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods. The he

safetyarxiv-cs-lg

End-to-end QP-based policies: A unified perspective on robust control and robot learning

arXiv:2609.31905v1 Announce Type: new Abstract: We present an end-to-end QP-based policy framework that enables systematic policy construction with minimal domain-specific design, while preserving the

Energy-aware frugal Bayesian optimization

model-releasesarxiv-cs-lg

arXiv:2609.31638v1 Announce Type: new Abstract: Modern design optimization frameworks aim first and foremost for models with the most accurate predictions without balancing computational overhead. It

FEAT: Free energy Estimators with Adaptive Transport

arXiv:2504.11516v4 Announce Type: replace-cross Abstract: We present Free energy Estimators with Adaptive Transport (FEAT), a novel framework for free energy estimation -- a critical challenge across

Applications

In-Token Learning for High-Fidelity Image Restoration via Diffusion Transformers

arXiv:2609.33523v1 Announce Type: new Abstract: We present In-Token Learning, an image restoration framework that adapts a pretrained diffusion transformer using conditional rectified flow matching. C

applicationsarxiv-cs-cv

Inspector: Conversational and Lightweight Analyzer of Analog Circuit Layouts Using LLM and CNNs

arXiv:2609.34976v1 Announce Type: cross Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs)

Look Before You Judge: Training-Free Region Mining for Grounded and Explainable Deepfake Detection

arXiv:2609.35536v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) can explain deepfake verdicts in natural language, but such explanations are not necessarily visually grounded

MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis

arXiv:2609.31789v1 Announce Type: cross Abstract: In this work, we explore MammoClaw, a training-free agent framework that leverages frozen MLLMs for mammography analysis. To support agentic investiga

agentsarxiv-cs-cv

PINNMorph: Evolving Online Adaptation Policies for Physics-Informed Neural Networks

arXiv:2609.32685v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a learning-based framework for solving partial differential equations (PDEs), yet their training beha

safetyarxiv-cs-lg

Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios

arXiv:2609.35086v1 Announce Type: new Abstract: In this work, we study portfolio optimization under the stochastic discount factor (SDF) framework by learning market state representations that capture

Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression

arXiv:2609.34834v1 Announce Type: new Abstract: Transform-based methods provide an effective framework for point cloud attribute compression by representing attributes as transform coefficients. Intro

ZeroBot: Learning from Scratch in Minutes with Generative Real2Sim

arXiv:2609.34010v1 Announce Type: cross Abstract: We present ZeroBot, a real2sim framework for learning a robot manipulation task from scratch in minutes under challenging conditions: zero human demon

safetyarxiv-cs-cv

Bayesian Uncertainty Quantification for fMRI Functional Connectivity via Simulation-Based Inference

arXiv:2609.30445v1 Announce Type: cross Abstract: Optimizing fMRI scan duration and spatial resolution is critical for experimental design, yet traditional correlation-based approaches cannot quantify

Learning Vision-Based Agile Gap Traversal: Differentiable Simulation with a Warm-Started Critic

arXiv:2609.30696v1 Announce Type: new Abstract: Traversing narrow gaps is challenging for autonomous quadrotors, especially when control commands come directly from high-dimensional visual observation

MDSkin-Net: Multi-Task Skin Lesion Analysis Driven by Pattern Analysis Priors and Spatial Alignment Regularization

arXiv:2609.30855v1 Announce Type: new Abstract: Reliable skin lesion segmentation and classification are central to dermoscopic computer-aided diagnosis. Existing multi-task frameworks couple the two

SatNav: A Scalable Benchmark for Long-Horizon UAV Vision-Language Navigation from Satellite Imagery

arXiv:2609.31507v1 Announce Type: new Abstract: Urban uncrewed aerial vehicle (UAV) vision-language navigation (VLN) requires agents to follow instructions across extended urban spaces, inherently dem

Local Ai

Towards Universal Representation-Based Process Control

arXiv:2609.30790v1 Announce Type: new Abstract: Many temporal process learning and monitoring pipelines operate in local windows, making window-level decisions unavoidable in practice. In such setting

local-aiarxiv-cs-lg

Agentic Detection of Online Conspiracies

arXiv:2609.30250v1 Announce Type: new Abstract: Conspiratorial discourse on social media is not always expressed through explicit claims or stable lexical markers. The same surface content may express

agentsarxiv-cs-cl

Beyond Feature Reliability: Repeat-Informed Multifractal Curve Regression for Brain-Age Prediction

arXiv:2609.29307v1 Announce Type: new Abstract: Brain-age prediction from resting-state fMRI provides a quantitative framework for characterizing age-related changes in spontaneous brain dynamics and

Federated Learning of AnDE Classifiers

arXiv:2609.28695v1 Announce Type: new Abstract: This work presents a federated framework for training Averaged n-Dependence Estimators (AnDE) in distributed environments. The proposed method focuses o

Applications

Learned Cross-Task Relationships in Multi-Task Models

arXiv:2609.28776v1 Announce Type: new Abstract: We propose a framework that learns cross-task relationships in multi-task models by approximating the joint distribution of task labels through targeted

applicationsarxiv-cs-ai

The Gold in Bias: Maturing the AI Design Process through Verification

arXiv:2609.29730v1 Announce Type: new Abstract: Bias in AI systems is typically framed as a flaw to be minimized, yet it also serves as a critical indicator of underlying weaknesses in data, modeling

safetyarxiv-cs-ai

Anatomy-Aware Synthesis of Post-Contrast Breast MRI from Pre-Contrast Images

arXiv:2609.27015v1 Announce Type: new Abstract: We developed an anatomy-aware deep learning framework to synthesize post-contrast breast MRI from pre-contrast images, emphasizing tumor and background

Depth-Guided Contrastive Learning for 2D Representations with 3D Spatial Awareness

arXiv:2609.28159v1 Announce Type: new Abstract: Standard contrastive learning frameworks are mainly designed from a semantic perspective, yet learning 2D visual representations that preserve 3D spatia

HINT-Blimp: Human INTent Inference from Multimodal Cues for Robotic Blimps

arXiv:2609.27154v1 Announce Type: new Abstract: In human-robot interaction, traditional interfaces such as joysticks and handheld tablets introduce latency into navigation tasks and require the operat

researcharxiv-cs-ro

Local Ai

LAYERSCOPE: A Layerwise Characterization of Video and Multimodal Learned Representations

arXiv:2609.28086v1 Announce Type: cross Abstract: We propose LAYERSCOPE, a label-free, layerwise framework that aims to characterize a model's learned representations in video and multimodal settings.

local-aiarxiv-cs-ai

Reflection-Aware Reasoning for Non-Line-of-Sight Pedestrian Localization

arXiv:2609.27346v1 Announce Type: new Abstract: Reliable localization of non-line-of-sight (NLOS) pedestrians is critical for safe urban autonomous driving, yet it remains highly challenging in ego-dy

agentsarxiv-cs-ro

Spatial and Semantic Reasoning for LLM-Driven Robot Navigation via MCP

arXiv:2609.27340v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as natural-language interfaces for robotic systems, yet their integration with Robot Operating System

agentsarxiv-cs-ro

Tutorials

Tail-Aware Geometry Learning for Conformal Ellipsoids

arXiv:2609.27221v1 Announce Type: new Abstract: This paper studies multivariate conformal prediction (CP), a distribution-free uncertainty quantification framework with finite-sample coverage guarante

tutorialsarxiv-cs-lg

Hardware

Conduit: An Experience Data Plane for Distributed Reinforcement Learning

arXiv:2609.24456v1 Announce Type: cross Abstract: Distributed reinforcement learning (RL) scales training by parallelizing actors and learners around an Experience Buffer. As RL workloads grow, howeve

hardwarearxiv-cs-ai

Control Barrier Functions for Safe Free-Flying Robotic Spacecraft Operations in Tumbling Target Capture

arXiv:2609.25905v1 Announce Type: new Abstract: This paper presents a modular control barrier function (CBF) framework for safe free-flying robotic spacecraft operations during tumbling target capture

Geometric Uncertainty for Detecting and Correcting Hallucinations in LLMs

arXiv:2509.13813v3 Announce Type: replace Abstract: Large language models are known to hallucinate, generating linguistically plausible but incorrect answers to questions. Uncertainty quantification h

researcharxiv-cs-cl

Learning Neural Feedback Linearization for Data-driven Systems via Augmented Lagrangian

arXiv:2609.25163v1 Announce Type: new Abstract: The paper proposes a novel data-driven framework for designing and training a feedback linearizing controller by explicitly incorporating relative degre

Tutorials

Relative Contact Velocity-Controlled Hand-Object Mechanism for Dexterous Tool Manipulation

arXiv:2609.25619v1 Announce Type: new Abstract: This work investigates how to enable general multi-finger robotic hands to perform the complete tool manipulation process, which entails picking up a to

tutorialsarxiv-cs-ro

Situation Aware Locomotion for Dual Mobile Cobots in Shared Environments

arXiv:2609.26083v1 Announce Type: new Abstract: This paper presents a situation aware locomotion framework for two mobile collaborative robots operating in shared industrial environments. The proposed

Active Spatial Inspection for Effective and Efficient Embodied Exploration

arXiv:2609.22385v1 Announce Type: cross Abstract: Achieving high task success and efficiency remains a central pursuit in embodied exploration. Existing frameworks typically guide agent behavior throu

agentsarxiv-cs-cv

Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching

model-releasesarxiv-cs-lg

arXiv:2609.23383v1 Announce Type: cross Abstract: Bayesian filtering provides a principled framework for online state estimation under uncertainty, yet its application to systems with high-dimensional

DiagGen: Agentic Generation of Deformable Assets with Sim-based Diagnostics for Robotic Simulation

arXiv:2609.23103v1 Announce Type: new Abstract: While simulation-ready deformable assets are essential for in-silico robotic manipulation tasks, existing generation frameworks typically assess physica

agentsarxiv-cs-ro

Explainable Neuro-Fuzzy Prediction for Trustworthy Decision-Making in Maritime

model-releasesarxiv-cs-lg

arXiv:2609.24358v1 Announce Type: new Abstract: Predicting when maritime systems require maintenance can be critical, avoiding hazards and costly consequences. To address this problem, this paper prop

GenVoid: Uncertainty-Aware Learning of Subsurface Material Defects with an Experimentally Validated Physics-Informed Generative Model

arXiv:2609.23761v1 Announce Type: new Abstract: Internal voids are ubiquitous defects in manufactured structures, yet their characterization remains challenging because their geometry is hidden and ca

MM-ContextFold: Context Folding for Multimodal Agentic Retrieval

arXiv:2609.23121v1 Announce Type: new Abstract: Multimodal Agentic Retrieval (MAR) requires agents to solve complex information-seeking tasks by iteratively invoking external tools. Typical frameworks

agentsarxiv-cs-cv

Sim2Real Diffusion: Leveraging Foundation Vision Language Models for Adaptive Automated Driving

model-releasesarxiv-cs-ro

arXiv:2507.00236v4 Announce Type: replace Abstract: Simulation-based design, optimization, and validation of autonomous vehicles have proven to be crucial for their improvement over the years. Neverth

Universal Observatory Graphs for Distributed Sky Coverage and Artificial Intelligence Based Interplanetary Routing

arXiv:2609.22244v1 Announce Type: new Abstract: This research proposes the Universal Observatory Graph (UOG), an AI-driven framework for distributed astronomical observation across the Solar System. T

agentsarxiv-cs-lg

Video-based Surgical Skill Assessment Using Dynamics-and-Uncertainty-Aware Tree-based Gaussian Process Classifier

arXiv:2609.24619v1 Announce Type: new Abstract: The proposed pipeline integrates a representation-flow convolutional neural network with a dynamics- and uncertainty-aware tree-based Gaussian Process c