Search: “framework”

FuseSampleAgg: One-Pass Neighborhood Estimation for Budgeted Knowledge-Graph Refresh and Validation

arXiv:2511.13645v2 Announce Type: replace Abstract: Operational knowledge-graph (KG) pipelines in networking and cybersecurity increasingly need to refresh embeddings under strict time, memory, and au

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GENA3D: Generative Amodal 3D Modeling by Bridging 2D Priors and 3D Coherence

DGX agent

arXiv:2511.21945v3 Announce Type: replace Abstract: Generating complete 3D objects under partial occlusions (i.e., amodal scenarios) is a practically important yet challenging problem, as large portio

safetyarxiv-cs-cv

24 Jun 2026

Local Ai

GeoIMO: Geometry-Driven Independent Motion Classification for Event Cameras

arXiv:2606.24499v1 Announce Type: new Abstract: Existing automotive event datasets rely on appearance-based annotations from frame pipelines, making them poorly suited for motion-aware event perceptio

local-aiarxiv-cs-cv

Grad Detect: Gradient-Based Hallucination Detection in LLMs

arXiv:2606.24790v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse tasks, yet they remain prone to generating hallucinations. Detec

Ground Then Rank: Revisiting Knowledge-Based VQA with Training-Free Entity Identification

arXiv:2606.23881v1 Announce Type: new Abstract: Knowledge-Based Visual Question Answering (KB-VQA) requires grounding visual queries to external knowledge beyond directly observable content in images.

researcharxiv-cs-cl

Grounded Chess Reasoning in Language Models via Master Distillation

arXiv:2603.20510v2 Announce Type: replace Abstract: Language models often lack grounded reasoning capabilities in specialized domains where training data is scarce but bespoke systems excel. We introd

Grounding Generative Policies in Physics: Optimization-Guided Diffusion for Robot Control

arXiv:2606.24208v1 Announce Type: new Abstract: Diffusion models sample effectively from high-dimensional, multimodal distributions, but their outputs may violate deployment constraints. For task-spac

researcharxiv-cs-ro

HANCLIP: A Family of Hyperbolic Angular Negation Vision Language Models

arXiv:2606.23843v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are typically pre-trained on large-scale image-text datasets to capture semantic correspondences between visual content an

Heterogeneous Knowledge Distillation via Geometry Decoupling and Momentum-Aware Gradient Regulation

arXiv:2606.24557v1 Announce Type: new Abstract: Heterogeneous Knowledge Distillation (HKD) aims to transfer knowledge across varying architectures (e.g., from Transformer to CNN) but inherently suffer

High-Fidelity Synthetic Transmission Electron Microscopy Image Generation Using Diffusion Probabilistic Models for Data-Limited Semiconductor Metrology

arXiv:2606.24817v1 Announce Type: new Abstract: Advanced semiconductor nodes drastically increased demand for Transmission Electron Microscopy (TEM), yet destructive sample preparation, slow imaging a

HiPath: Hierarchical Vision-Language Alignment for Structured Pathology Report Prediction

arXiv:2603.19957v2 Announce Type: replace-cross Abstract: Pathology reports are structured, multi-granular documents encoding diagnostic conclusions, histological grades, and ancillary test results ac

safetyarxiv-cs-ai

Holistic Data Scheduler for LLM Pre-training via Multi-Objective Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2606.24133v1 Announce Type: cross Abstract: The composition of training data, governed by the diversity of sources and their mixing strategy, is a cornerstone of Large Language Model (LLM) pre-t

How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation

model-releasesarxiv-cs-cl

arXiv:2606.16821v2 Announce Type: replace Abstract: Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that

Hybrid Sequence Modeling and Reinforced Verification for Controllable Target-Conditioned Decision Making

arXiv:2508.16420v3 Announce Type: replace Abstract: Target-conditioned sequence models provide a simple interface for controllable offline decision making, but the requested target return can be an un

safetyarxiv-cs-lg

Information-Theoretic Classifier-Free Guidance with Adaptive Schedule Optimization

arXiv:2606.24025v1 Announce Type: new Abstract: Diffusion models have achieved strong performance in image, text-to-image, and video generation, where conditional generation is often controlled by cla

researcharxiv-cs-lg

InSight: Self-Guided Skill Acquisition via Steerable VLAs

arXiv:2606.24884v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can learn manipulation skills from demonstrations, but their capabilities are bounded by the skills in the trainin

agentsarxiv-cs-ai

Integrated Sensing and Communications for Real-time Avatar Control in XR over 5G

arXiv:2606.23771v1 Announce Type: cross Abstract: Extended Reality (XR) presents a challenging use case for 5G and 6G networks, requiring high data-rates and lowlatency communication to deliver a trul

Tutorials

Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts

arXiv:2405.19062v2 Announce Type: replace-cross Abstract: Continuous-Time Dynamic Graphs (CTDGs) enable fine-grained modeling of evolving relational systems. However, most existing CTDG representation

tutorialsarxiv-cs-ai

IPO Finance Agent: Evaluation of LLM Financial Analysts beyond Finance Agent v2, with Automated Rubric Generation -- the Case of the SpaceX (SPCX) IPO

arXiv:2606.23032v2 Announce Type: replace Abstract: Finance Agent v2 (by Vals AI) has emerged as the reference benchmark for evaluating both Anthropic Claude and OpenAI ChatGPT frontier language model

Tutorials

IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation

arXiv:2606.24849v1 Announce Type: cross Abstract: Unified multi-modal large language models (MLLMs) have achieved strong text-to-image generation quality, but still struggle with structure-aware promp

tutorialsarxiv-cs-ai

LaGO: Latent Action Guidance for Online Reinforcement Learning

arXiv:2606.24669v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for planning and sequential decision-making, but prior work often relies on using them as direc

Large-Language-Model Discovery of Quantum LDPC Codes through Structured Concept Evolution

arXiv:2606.24808v1 Announce Type: cross Abstract: Quantum computers could outperform classical machines on important problems, but only if the errors that pervade quantum hardware can be corrected at

Latent Visual States for Efficient Multimodal Reasoning

arXiv:2606.24233v1 Announce Type: new Abstract: The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly relie

safetyarxiv-cs-cv

Light-weight Pronunciation Assessment via Discrete Speech Token Surprisal

arXiv:2606.19910v2 Announce Type: replace Abstract: Training automated pronunciation assessment often relies on labeled learner errors or non-native corpora that are costly to collect. We propose a li

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Applications

Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching

arXiv:2606.24457v1 Announce Type: new Abstract: Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computation, or additional foundation-model

applicationsarxiv-cs-cv

LLM-MINE: Large Language Model based Alzheimer's Disease and Related Dementias Phenotypes Mining from Clinical Notes

arXiv:2603.13673v2 Announce Type: replace Abstract: Accurate extraction of Alzheimer's Disease and Related Dementias (ADRD) phenotypes from electronic health records (EHR) is critical for early-stage

LoT-Pass: Long-term-robust Image Watermarking for Image to Video Generation

arXiv:2509.17773v2 Announce Type: replace Abstract: The rapid progress of image-guided video generation (I2V) has raised concerns about its potential misuse in misinformation and fraud, underscoring t

M^2C-EvDet: Multi-Domain Multi-Order Cross-Modal Knowledge Distillation for Event-based Object Detection

arXiv:2606.24248v1 Announce Type: new Abstract: Event-based object Detection (EvDet), as a biologically inspired visual perception paradigm, demonstrates superior performance in scenarios demanding hi

M4-SAR: A Multi-Resolution, Multi-Polarization, Multi-Scene, Multi-Source Dataset and Benchmark for optical-SAR Object Detection

arXiv:2505.10931v4 Announce Type: replace Abstract: Single-source remote sensing object detection using optical or SAR images struggles in complex environments. Optical images offer rich textural deta

Machine Learning Modeling for Real-Time Melt Pool Monitoring in Laser Powder Bed Fusion Additive Manufacturing: A Hybrid Approach

arXiv:2606.23851v1 Announce Type: cross Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion

Macro Graph of Experts for Billion-Scale Multi-Task Recommendation

arXiv:2506.10520v5 Announce Type: replace-cross Abstract: Graph-based multi-task learning at billion-scale presents a significant challenge, as different tasks correspond to distinct billion-scale gra

Managing Task Execution for Unknown Workloads in Batteryless IoT: A Hardware-Agnostic Evaluation

arXiv:2606.24340v1 Announce Type: new Abstract: In recent years, the Internet of Things (IoT) paradigm has been shifting toward batteryless, energy-harvesting architectures. Sustaining reliable operat

agentsarxiv-cs-lg

Measuring User's Mental Models of Speech Translation in Human-AI Collaboration

arXiv:2606.24644v1 Announce Type: new Abstract: Millions of people use machine translation (MT) tools daily, yet little is known about their perception of what systems can and cannot do. This paper st

researcharxiv-cs-cl

MedBench v5: A Dynamic, Process-Oriented, and Hallucination-Aware Benchmark for Clinical Multimodal Models

model-releasesarxiv-cs-cl

arXiv:2606.24155v1 Announce Type: new Abstract: Existing medical AI benchmarks lack process visibility, atomic skill evaluation, and integrated hallucination detection. We introduce MedBench v5, a red

Mixtures Closest to a Given Measure: A Semidefinite Programming Approach

arXiv:2509.22879v2 Announce Type: replace-cross Abstract: Mixture models, such as Gaussian mixture models, are widely used in machine learning to represent complex data distributions. A key challenge,

Local Ai

MOCHA: Multi-modal Objects-aware Cross-arcHitecture Alignment

arXiv:2509.14001v5 Announce Type: replace-cross Abstract: Personalized object detection aims to adapt a general-purpose detector to recognize user-specific instances from only a few examples. Lightwei

local-aiarxiv-cs-ai

MortarBench: Evaluating Mortgage Loan Origination Agents

arXiv:2606.19416v2 Announce Type: replace Abstract: Loan origination is the process by which a lender creates a new loan, from application and underwriting through approval and funding. This process s

MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network

arXiv:2606.24214v1 Announce Type: new Abstract: Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branc

MSPL: Multi-Step Pseudo-Labeling for Open-Vocabulary Object Detection

arXiv:2510.14792v4 Announce Type: replace Abstract: Open-vocabulary object detection (OVD) aims to recognize and localize object categories beyond the training set. Recent approaches leverage vision-l

safetyarxiv-cs-cv

Multimedia and Visual Analytics in the Agentic Era

arXiv:2504.06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections. Foundation models and AI agents have ra

NavWM: A Unified Navigation World Model for Foresight-Driven Planning

arXiv:2606.24101v1 Announce Type: cross Abstract: Conventional visual navigation policies often struggle with myopic decision-making and mode collapse in complex environments. While world models offer

agentsarxiv-cs-cv

Neural Network-Based Parametric Model Reduction for Predicting Turbulent Flow for Different Vehicle Geometries

arXiv:2606.24265v1 Announce Type: cross Abstract: Numerical simulations in industrial applications often require performing numerous high-precision computations parameterized by specific experimental

Neuro-Symbolic Drive: Rule-Grounded Faithful Reasoning for Driving VLAs

arXiv:2606.23938v1 Announce Type: new Abstract: Driving VLA models incorporating Chain-of-Thought (CoT) reasoning are attractive because they leverage pretrained VLM representations and expose interme

NeuroSonic: Conditional Flow Matching for EEG-to-Speech Reconstruction

arXiv:2606.24087v1 Announce Type: new Abstract: Reconstructing continuous speech from scalp electroencephalography (EEG) remains fundamentally challenging. EEG provides a weak, spatially diffuse, and

researcharxiv-cs-lg

Tutorials

NoContactNoWorries: Estimating Contact through Vision and Proprioception for In-Hand Dexterous Manipulation

arXiv:2606.24450v1 Announce Type: cross Abstract: Perceiving physical contact is fundamental to dexterous manipulation. While robots often rely on dedicated hardware tactile sensors, humans exhibit a

tutorialsarxiv-cs-ai

One Year Later...The Harms Persist, But So Do We!

arXiv:2606.23884v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used for mental health-related conversations, yet safety safeguards remain inadequate an

safetyarxiv-cs-ai

Open-Vocabulary BEV Segmentation with 3D-Aware Geometric Constraints

arXiv:2606.24353v1 Announce Type: new Abstract: Bird's-eye view (BEV) perception fuses multi-camera images into a unified top-down representation for autonomous driving. Despite recent progress, state

agentsarxiv-cs-cv

P-MTP: Efficient Document Parsing via Multi-Token Prediction with Progressive Depth Scaling

arXiv:2606.24447v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have revolutionized document parsing by enabling end-to-end mapping from images to structured text, imposing a significant