Search: “framework”

arXiv:2607.18762v1 Announce Type: new Abstract: We propose a weakly supervised 18FFDG PET representation-learning framework for content based medical image retrieval, using H&E derived information dur

tutorialsarxiv-cs-cv

23 Jul 2026

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Agents

Very cool idea to convert memory to skills. (bookmark it) Most agent memory systems retrieve past traces as passive context. MSCE turns them…

DGX agent

Very cool idea to convert memory to skills. (bookmark it) Most agent memory systems retrieve past traces as passive context. MSCE turns them into executable skills instead. The training-free framework

agentsdair-ai--x

21 Jul 2026

Active Learning for Efficient Annotation of Surgical Videos with Weak Supervision

arXiv:2607.13237v1 Announce Type: new Abstract: Precise spatial-temporal annotation of laparoscopic videos is time-consuming and requires expert knowledge. We propose a human-in-the-loop knowledge acq

Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models

arXiv:2607.13500v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved strong performance in multimodal understanding, yet remain challenging to deploy on resource-constrained edg

applicationsarxiv-cs-cv

CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion

model-releasesarxiv-cs-ai

arXiv:2607.13120v1 Announce Type: cross Abstract: Inferring gene regulatory networks (GRNs) from single-cell transcriptomic data is crucial for biological discovery, yet existing approaches suffer fro

Efficient and Privacy Aware Edge Cloud Collaborative Inference for Large Language Models

arXiv:2607.13093v1 Announce Type: cross Abstract: On-device LLM inference faces a trilemma of response latency, limited hardware resources and user privacy. Full cloud inference delivers strong comput

local-aiarxiv-cs-ai

Efficient Computing for Medical Image Acquisition and Reconstruction

arXiv:2607.13204v1 Announce Type: cross Abstract: Medical imaging systems such as CT, MRI, PET, and SPECT do not directly acquire images. Instead, they measure physical signals that encode anatomical

Exploratory, Communicative, and Deployable: Vision-Driven Embodied Agents for Open-World Mobile Manipulation

model-releasesarxiv-cs-cv

arXiv:2607.13653v1 Announce Type: new Abstract: Real-world deployment of embodied agents requires active exploration, visual grounding, and interactive intent disambiguation. However, existing framewo

From Language to Navigation Goals: A Vision-Language Approach for Semantic Navigation of Mobile Robots Using RGB-D Perception

model-releasesarxiv-cs-ai

arXiv:2607.13624v1 Announce Type: cross Abstract: Natural language interaction provides an intuitive way for non-expert users to communicate with robotic platforms. However, transforming user requests

Industrial Dexterity Benchmark: A Hardware-Software Benchmarking Platform for Industrial Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly

Learning Safe Agent Behaviour from Human Preferences and Justifications via World Models

arXiv:2607.13172v1 Announce Type: new Abstract: We address the problem of safely training an agent policy and deploying a good and safe policy, in settings where the environment dynamics are unknown a

safetyarxiv-cs-ai

LPM: Industrial-Scale Generative Video Restoration

arXiv:2607.13460v1 Announce Type: new Abstract: We present the Large Processing Model (LPM), a diffusion-based generative framework for photorealistic video restoration under complex, in-the-wild degr

applicationsarxiv-cs-cv

Quantum Topological Data Encoding

arXiv:2607.13847v1 Announce Type: cross Abstract: Many datasets encountered across a wide range of domains possess rich geometric and topological structure that is difficult to capture using conventio

Relevance-Aware Rule: Structural Deletion of Irrelevant Conditions in Decision Trees

arXiv:2607.13874v1 Announce Type: new Abstract: Decision trees generate interpretable if--then rules, yet they contain irrelevant conditions (IRCs). These IRCs arise from the structural mechanism of t

Screening Is Effective for Visual Recognition

arXiv:2607.13983v1 Announce Type: new Abstract: Vision Transformer (ViT) has been widely used as a powerful framework for modeling global dependencies among image patches. However, its core component,

SingGuard-NSFA: Extensible Guardrails for Agentic AI via Generative Reasoning and Real-Time Classification

model-releasesarxiv-cs-ai

arXiv:2607.13081v1 Announce Type: cross Abstract: We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive informati

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

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

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

arXiv:2409.10094v3 Announce Type: replace Abstract: Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e

Calibratable Disambiguation Loss for Multi-Instance Partial-Label Learning

model-releasesarxiv-cs-lg

arXiv:2512.17788v2 Announce Type: replace Abstract: Multi-instance partial-label learning (MIPL) is a weakly supervised framework that extends the principles of multi-instance learning (MIL) and parti

DiffRadar: Differentiable Physics-Aware Radar SLAM with Gaussian Fields

model-releasesarxiv-cs-ro

arXiv:2607.12265v1 Announce Type: new Abstract: Radar sensing is increasingly used in mobile systems because it operates reliably under poor lighting, adverse weather, and privacy-sensitive settings w

Tutorials

DM-KG: A Novel Method for Boosting Spatial Cognition of Vision-Language Models in Street View Imagery

arXiv:2607.12319v1 Announce Type: new Abstract: As vision-language models (VLMs) are increasingly deployed in geospatial question answering and visual scene understanding, improving their spatial cogn

tutorialsarxiv-cs-cv

Domain-Incremental Remote Sensing Change Detection via Difference-Guided Adaptation and Frequency-Decoupled Distillation

arXiv:2607.12934v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incrementa

Evaluating Large Language Models on Misconceptions in Multi-Turn Medical Conversations

model-releasesarxiv-cs-cl

arXiv:2607.12884v1 Announce Type: new Abstract: Patients seeking medical information often ask questions that embed incorrect assumptions or misconceptions. In such cases, safe medical communication r

FoundationGeo: Learning Spatial Pixel-Wise Fields for Monocular Metric Geometry

arXiv:2607.11588v2 Announce Type: replace Abstract: We present FoundationGeo, a two-stage framework that explicitly bridges relative and metric prediction via spatial calibration and principled data d

Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite

arXiv:2607.11947v1 Announce Type: cross Abstract: Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated. While PNU l

Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization

model-releasesarxiv-cs-lg

arXiv:2607.12349v1 Announce Type: new Abstract: Drug discovery and development is time-consuming and resource-intensive, motivating computational approaches such as diffusion models for de novo drug d

Inclusive Federated Learning Through Compliance-Weighted Noise Allocation in Healthcare AI

arXiv:2505.22108v4 Announce Type: replace-cross Abstract: Background: Federated learning (FL) enables collaborative training of clinical AI models without centralizing patient data, but adoption is li

applicationsarxiv-cs-ai

IQA-T1: Tool-based Visual Evidence Reasoning for Image Quality Assessment

arXiv:2607.12375v1 Announce Type: cross Abstract: Image Quality Assessment (IQA) in open-world environments remains challenging due to limited generalization and interpretability. Recent approaches ba

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation

arXiv:2505.15284v2 Announce Type: replace-cross Abstract: Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing

applicationsarxiv-cs-cv

Learning from Complementary Ultrasound Representations for Liver Disease Classification

arXiv:2607.12062v1 Announce Type: new Abstract: Differentiating non-alcoholic steatohepatitis (NASH) from non-alcoholic fatty liver disease (NAFLD) using ultrasound remains challenging due to subtle t

LIDAR-AD: A Decoder-Free Latent-Interaction Dreamer with Action-Residual Chains for Autonomous Driving

arXiv:2607.11964v1 Announce Type: new Abstract: Autonomous driving requires long-horizon closedloop decision making in dynamic traffic environments. Latent world models offer an effective framework fo

local-aiarxiv-cs-lg

Mitigating The Effect of Class Imbalance in Data with Hierarchical and Dependable Structure

arXiv:2607.11994v1 Announce Type: cross Abstract: Classifying cybersecurity vulnerabilities using the Common Weakness Enumeration (CWE) taxonomy is challenging due to extreme class imbalance and stron

More than a Manipulator: Planning Propellant-Free Attitude Maneuvers for Free-Floating Spacecraft

arXiv:2607.12130v1 Announce Type: new Abstract: Spacecraft attitude control is traditionally achieved using momentum exchange devices or propellant-consuming thrusters. Meanwhile, a growing number of

applicationsarxiv-cs-ro

More Than Where You Are: Learning Semantics, Structure, and Geometry from Cross-View Localization

arXiv:2607.12429v1 Announce Type: new Abstract: Consistent cross-view understanding under extreme viewpoint changes is essential for spatial intelligence, as it enables models to recognize the same sc

Physically Aware Radiomics Without Interpolation: Disentangling Voxel Geometry and Signal Modification in CT and MRI

arXiv:2607.12399v1 Announce Type: new Abstract: Objective: Radiomic texture features are usually computed in voxel-index neighborhoods, implicitly assuming isotropic spatial relationships. In anisotro

Quantum Port-Hamiltonian Neural Networks: Learning Conservative and Dissipative Dynamics via Measurement-Induced Nonlinearity

model-releasesarxiv-cs-lg

arXiv:2607.12269v1 Announce Type: new Abstract: We introduce Quantum Port-Hamiltonian Neural Networks (Q-pHNNs), a family of parameterised quantum circuits that learn classical dynamics in a structure

Qubit-Efficient Quantum Search for Hyperdimensional Decomposition via Logarithmic Encoding

arXiv:2607.11936v1 Announce Type: new Abstract: Hyperdimensional Computing (HDC) represents symbols using high-dimensional hypervectors of dimension D. In hypervector decomposition, the objective is t

RegHead: Non-Humanoid Head Blendshapes via Feed-Forward Registration

arXiv:2607.12206v1 Announce Type: new Abstract: We present RegHead, a framework for constructing semantic blendshape sets for animatable non-humanoid head avatars. With a fixed expression vocabulary,

Robust Design of Integrated Sensing and Communication in LEO Satellite Systems

arXiv:2607.12337v1 Announce Type: cross Abstract: With the growing demand for satellite sensing and communication, the limited wireless resources are difficult to support multiple satellite systems. T

Seeing Globally, Refining Locally: Global Visual Guidance and Local Ultrasound Cues for Robust Freehand 3-D Ultrasound Reconstruction

arXiv:2607.12398v1 Announce Type: new Abstract: Freehand 3-D ultrasound (US) imaging has attracted increasing attention owing to its intuitive volumetric visualization, ease of use, and low cost. Howe

Spectral Diffusion Processes

arXiv:2209.14125v3 Announce Type: replace-cross Abstract: Diffusion models have proven to be a flexible and effective framework for modelling probability distributions on finite-dimensional spaces. Ho

Streamlining stereo differentiable rendering for marker-free real-time tracking of surgical robots

arXiv:2607.12604v1 Announce Type: new Abstract: Purpose: Marker-based tracking of surgical robots is occlusion-prone in cluttered operating rooms. We evaluate stereo differentiable rendering for marke

safetyarxiv-cs-ro

TAKE: Trajectory-Aware Knowledge Estimation for Text Dataset Distillation

arXiv:2607.11898v1 Announce Type: new Abstract: Large-scale text corpora have become a quiet bottleneck in modern NLP, not just in storage, but in the accumulated cost of training, fine-tuning, and co

researcharxiv-cs-cl

The Computational Basis of Confidence in Large Language Models

arXiv:2607.12447v1 Announce Type: cross Abstract: Reliable confidence -- the probability that a model's own answer is correct -- is essential for the trustworthy deployment of language models. Existin

Agents

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

agentsarxiv-cs-ai

VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression

model-releasesarxiv-cs-cv

arXiv:2607.12756v1 Announce Type: new Abstract: Vision-language models (VLMs) process large numbers of visual tokens, resulting in substantial inference latency and memory overhead. This has motivated

Building the AI-defined vehicle with Android, Google Cloud, and Nexus SDV