Search: “framework”

Coarse-to-Fine Hierarchical Alignment for UAV-based Human Detection using Diffusion Models

arXiv:2512.13869v3 Announce Type: replace Abstract: Training object detectors demands extensive, task-specific annotations, yet this requirement becomes impractical in UAV-based human detection due to

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Research

COMPASS: Complete Multimodal Fusion via Proxy Tokens and Shared Spaces for Ubiquitous Sensing

DGX agent

arXiv:2604.02056v2 Announce Type: replace Abstract: Missing modalities in multimodal sensing cause not only information loss but also a fusion-interface mismatch: a fusion head trained on a canonical

researcharxiv-cs-cv

9 Jun 2026

Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding

arXiv:2606.09331v1 Announce Type: cross Abstract: Omni-modal retrieval promises a single embedding space for text, image, video, document, and audio inputs, but building such a unified retriever is di

Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering

arXiv:2602.17911v3 Announce Type: replace-cross Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is

Agents

ConMem: Structured Memory-Guided Adaptation in Training-Free Multi-Agent Systems

arXiv:2606.08702v1 Announce Type: new Abstract: Recent advances have improved the adaptive capabilities of LLM-based multi-agent systems (MAS) through memory-, skill-, and learning-based approaches, y

agentsarxiv-cs-ai

Constrained user-item allocation for e-commerce marketing campaigns

arXiv:2606.09623v1 Announce Type: new Abstract: When running marketing campaigns, retailers must decide which products to promote and which users to target. These decisions are inherently coupled: eff

safetyarxiv-cs-lg

Agents

Continual Quadruped Robots Coordination via Semantic Skill Discovery

arXiv:2606.08102v1 Announce Type: cross Abstract: Multi-quadruped coordination has attracted increasing attention due to its enhanced payload capacity, broader contact coverage, and improved adaptabil

agentsarxiv-cs-ai

Agents

Contract2Tool: Learning Preconditions and Effects for Reliable Tool-Augmented LLM Agents

arXiv:2606.07904v1 Announce Type: new Abstract: Tool-augmented large language model agents increasingly rely on external APIs, but standard tool schemas describe how to call a tool, not when the tool

agentsarxiv-cs-ai

Cosmo3DFlow: Wavelet Flow Matching for Spatial-to-Spectral Compression in Reconstructing the Early Universe

arXiv:2602.10172v2 Announce Type: replace-cross Abstract: Reconstructing the early universe from the evolved present-day universe is a challenging and computationally demanding problem in modern astro

Local Ai

Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA

arXiv:2606.09181v1 Announce Type: new Abstract: Recent advances in video multimodal models have significantly improved VideoQA performance. However, these systems often rely on spurious statistical co

local-aiarxiv-cs-cv

Applications

CP4D: Compositional Physics-aware 4D Scene Generation

arXiv:2606.09187v1 Announce Type: new Abstract: 4D generation (extit{i.e.}, dynamic 3D generation) has recently emerged as a rapidly growing research frontier due to its powerful spatiotemporal modeli

applicationsarxiv-cs-cv

CRANE: Knowledge Editing for Reasoning MLLMs

arXiv:2606.09033v1 Announce Type: new Abstract: The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers,

Cranio-Diff: Diffusion-based Cross-domain Craniofacial Reconstruction with 2D X-ray Skull Guidance and Structural Identity Constraints

arXiv:2606.09699v1 Announce Type: new Abstract: The state-of-the-art generative models, such as CycleGAN, Pix2Pix, and diffusion models have demonstrated remarkable performance in the face generation

Culturally-Adapted Red-Teaming Across East and Southeast Asian Contexts: A Methodological and Comparative Analysis

arXiv:2606.09178v1 Announce Type: cross Abstract: Multilingual safety evaluation of large language models (LLMs) has predominantly relied on direct translation (DT) of English benchmarks into target l

Customer Churn Prediction on Structured Data Using FT-Transformer and Stacking Ensembles

arXiv:2606.07582v1 Announce Type: cross Abstract: Customer churn prediction is essential across data-driven industries such as insurance, digital banking, eCommerce, and subscription platforms, where

Data Agents Under Attack: Vulnerabilities in LLM-Driven Analytical Systems

arXiv:2606.08661v1 Announce Type: cross Abstract: Data agents integrate LLM-driven reasoning with relational data access, executable analytical tools, and multi-step workflow orchestration, making the

Decision-Focused Continual Learning for Seaport Power-Logistics Scheduling: Generalization across Varying Tasks

arXiv:2511.07938v3 Announce Type: replace Abstract: Power-logistics scheduling in modern seaports typically follows a predict-then-optimize pipeline. To enhance the decision quality of predictions, de

Deep Active Re-Labeling: Toward Noise-Resilient Annotation Efficiency

arXiv:2606.08718v1 Announce Type: cross Abstract: While Deep Active Learning (DAL) effectively reduces human annotation costs, its efficacy is constrained by human annotation errors. This is because t

DeepMine-Mamba: Mitigating Information Dilution in Mamba-Based State Space Models for Document Image Binarization

arXiv:2606.08781v1 Announce Type: new Abstract: Document image binarization aims to separate foreground text from degraded backgrounds while preserving thin, broken, and low-contrast strokes. Although

Dense Force Estimation with an Event-based Optical Tactile Sensor

arXiv:2606.09451v1 Announce Type: cross Abstract: Humans rely on spatially dense, geometry and force-aware tactile feedback at high temporal resolution for dexterous manipulation. While vision-based t

Detecting and containing AI-powered threats with Google Security Operations agents

model-releasesgoogle-cloud-ai

To defend against the growing range of AI-accelerated threat actors, organizations need to be able to respond faster to outpace the adversary.Recently, we announced Google AI Threat Defense, an automa

DexPIE: Stable Dexterous Policy Improvement from Real-World Experience

arXiv:2606.09615v1 Announce Type: cross Abstract: Dexterous manipulation presents substantial challenges for imitation learning due to its high-dimensional action space and complex contact-rich dynami

Applications

Differentially Private Synthetic Data via APIs 4: Tabular Data

arXiv:2606.08259v1 Announce Type: new Abstract: This paper investigates the problem of generating synthetic tabular data with differential privacy (DP) guarantees, enabling data sharing in sensitive d

applicationsarxiv-cs-lg

DifferSeg: Towards Diverse Multimodal Binary Segmentation via Differential Perception and Frequency Guidance

arXiv:2606.08906v1 Announce Type: new Abstract: In many binary segmentation tasks, most multimodal methods rely on fixed feature concatenation for cross-modal interaction and straightforward decoder d

DiffSight-Former: Modeling Structural Differences and Temporal Dynamics for Glaucoma Progression Prediction

arXiv:2606.09140v1 Announce Type: new Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, and early detection from fundus images is critical for effective disease management. Wh

Discovering Expert-Level Nash Equilibrium Algorithms with Large Language Models

arXiv:2508.11874v2 Announce Type: replace-cross Abstract: Designing polynomial-time algorithms for approximate Nash equilibria (ANE) with provable worst-case guarantees is a fundamental open problem i

Disentangled Feature Importance

arXiv:2507.00260v3 Announce Type: replace-cross Abstract: When predictors are statistically dependent, the appropriate definition of feature importance depends on the operational goal. Conditional-inc

Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference

arXiv:2606.07677v1 Announce Type: cross Abstract: Electronic health records (EHR) pose large-scale multi-disease modeling problems in which many outcomes are rare and strongly influenced by shared ris

Distilling Safe LLM Systems via Soft Prompts for On Device Settings

model-releasesarxiv-cs-lg

arXiv:2606.09388v1 Announce Type: new Abstract: Deploying safe large language models (LLMs) on resource-constrained edge devices presents a critical challenge: while dual-model systems combining LLMs

DIVERGE: Diversity-Enhanced RAG for Open-Ended Information Seeking

arXiv:2602.00238v2 Announce Type: replace-cross Abstract: Existing retrieval-augmented generation (RAG) systems often assume that each query has a single correct answer. This assumption overlooks open

Diverse Thinking Schemata Elicit Better Reasoning in Large Language Models

arXiv:2606.08974v1 Announce Type: new Abstract: Large reasoning models (LRMs) have attracted increasing attention for their ability to solve complex mathematical problems by generating extended reason

DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home

arXiv:2606.07542v1 Announce Type: cross Abstract: Generative AI is reshaping healthcare, yet most existing advances rely on hospital-grade devices, which limits their accessibility and potential for h

DN-Hypo-Pipeline: An AI-Driven Workflow for Hypothesis Generation via Large Language Models and Scientific Explanations

arXiv:2606.08532v1 Announce Type: new Abstract: A scientific hypothesis is the first step in research and undergoes experimental validation, yet it also reflects a deep understanding of and reasoning

Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View

arXiv:2606.07642v1 Announce Type: new Abstract: Assessing built-environment interaction, such as wheelchair accessibility, is difficult because real-world mobility is shaped by distributed, context-de

DOG-DPO:Dynamic Optimization in Geometry for Safety Alignment

arXiv:2606.07678v1 Announce Type: cross Abstract: Safety alignment for large language models relies on preference data, but current pipelines often train on large, redundant datasets. Existing data se

Domain-Adapted Small Language Models with Hybrid Post-Processing: Achieving Cost-Efficient, Low-Latency Multi-Label Structured Prediction via LoRA Fine-Tuning on Scarce Data

model-releasesarxiv-cs-lg

arXiv:2606.05781v2 Announce Type: replace Abstract: Deploying frontier large language models (LLMs) for domain-specific structured evaluation tasks incurs prohibitive latency, cost, and data-privacy o

Dr. SHAP-AV: Decoding Relative Modality Contributions via Shapley Attribution in Audio-Visual Speech Recognition

arXiv:2603.12046v2 Announce Type: replace-cross Abstract: Audio-Visual Speech Recognition (AVSR) leverages both acoustic and visual information for robust recognition under noise. However, how models

Driving Video Retrieval for Complex Queries with Structured Grounding

arXiv:2606.09109v1 Announce Type: new Abstract: Video retrieval at scale is central to data curation and safety validation in autonomous driving, where users want to find not only scenes but also dyna

Applications

DSFNet: Learning Dual-Domain Spectral Operators for Multi-Modality Spatio-Temporal Forecasting in Urban Transportation Systems

arXiv:2606.07695v1 Announce Type: cross Abstract: Multi-Modality Spatio-Temporal Forecasting (MoSTF) extends traditional spatio-temporal forecasting by incorporating diverse traffic modalities. Despit

applicationsarxiv-cs-ai

Dual Quaternion-Based Unscented Kalman Filter with Visual Inertial Odometry for Navigation in GPS-Denied Environments

model-releasesarxiv-cs-ro

arXiv:2606.09292v1 Announce Type: new Abstract: Reliable navigation in GPS-denied environments remains a fundamental challenge in robotics, aerospace, and autonomous vehicle applications. This paper p

DynaCF: Mitigating Shortcut Learning in Reward Models via Dynamic Counterfactual Sensitivity

arXiv:2606.09043v1 Announce Type: new Abstract: Reward models trained from pairwise preferences often exploit superficial shortcut cues rather than learning true response quality. We propose DynaCF, a

Echo-DM: Ultrasound Marker Removal via Conditional Latent Diffusion and Region-Aware Fusion

arXiv:2606.09378v1 Announce Type: new Abstract: Clinical ultrasound images often contain artificial markers, such as measurement calipers and text, to assist diagnostic interpretation and comparison.

Tutorials

EditSR: Enhancing Neural Symbolic Regression via Edit-based Rectification

arXiv:2606.07915v1 Announce Type: new Abstract: Neural symbolic regression models improve inference efficiency by shifting structural search to pretraining, but their one-pass autoregressive decoding

tutorialsarxiv-cs-ai

Efficient Minimal Solvers for Visual-Inertial Relative Pose Estimation in Multi-Camera Systems

arXiv:2606.09477v1 Announce Type: new Abstract: Estimating the relative poses of multi-camera systems is a fundamental problem in computer vision, with critical applications in autonomous vehicles, mo

Local Ai

Efficient Skill Grounding via Code Refactoring with Small Language Models

arXiv:2606.07999v1 Announce Type: new Abstract: Effective skill grounding is essential for deploying reusable skills in embodied agents, as even minor embodiment or environmental differences can rende

local-aiarxiv-cs-ai

EgoAERO: Learning Dexterous Manipulation from a Single Egocentric Video without Object Assets

arXiv:2606.08057v1 Announce Type: cross Abstract: Egocentric RGB-D videos offer a natural source of human dexterous manipulation demonstrations, but existing data is difficult to use for robot learnin

EgoPriMo: Egocentric Motion Generation for Interactive Humanoid Control

arXiv:2606.08495v1 Announce Type: cross Abstract: Humanoid robots require whole-body motions that adapt to scene context, task requirements, and user intent. Motion tracking reproduces specified traje

EgoTactile: Learning Grasp Pressure for Everyday Objects from Egocentric Video

arXiv:2606.09243v1 Announce Type: cross Abstract: Estimating full-hand grasp pressure from egocentric video is critical for immersive VR and robotic manipulation, yet dense tactile sensing often relie