Search: “framework”

MedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentatio

arXiv:2606.28419v1 Announce Type: cross Abstract: Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification. Conventional augmen

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Memory-Augmented LSTM Autoencoder for Unsupervised Activity Recognition with IMU Sensor Fusion

DGX agent

arXiv:2606.28377v1 Announce Type: cross Abstract: HAR using Inertial Measurement Unit (IMU) sensors is vital for healthcare monitoring and rehabilitation. Despite deep learning advancements, major cha

applicationsarxiv-cs-ai

30 Jun 2026

MOAR Planner: Multi-Objective and Adaptive Risk-Aware Path Planning for Infrastructure Inspection with a UAV

arXiv:2606.30575v1 Announce Type: new Abstract: The problem of autonomous navigation for UAV inspection remains challenging as it requires effectively navigating in close proximity to obstacles, while

safetyarxiv-cs-ro

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks

arXiv:2606.28339v1 Announce Type: cross Abstract: Industrial 6G networks require ultra-reliable, low-latency, and energy-efficient connectivity in dynamic and blockage-prone environments, where conven

agentsarxiv-cs-ai

Multi-Contact Force Estimation for Continuum Robots via Gaussian-Parameterized Factor Graphs

arXiv:2606.29165v1 Announce Type: new Abstract: Continuum robots offer key advantages in navigating unstructured environments, but their safe operation requires accurate estimation of the external con

researcharxiv-cs-ro

Local Ai

Multimodal and Multiscale Spatial-Temporal Semantic Search and Recommendation with AI Foundation Models

arXiv:2606.28369v1 Announce Type: cross Abstract: Semantic search and recommendation of similar documents, such as news and reports about unusual environmental events (e.g., a dead whale washed ashore

local-aiarxiv-cs-ai

Local Ai

MyGO-Splat: Multi-Objective Closed-Loop Geometric Feedback for RGB-Only Gaussian SLAM

arXiv:2606.29738v1 Announce Type: new Abstract: Real-time monocular Simultaneous Localization and Mapping (SLAM) fundamentally suffers from scale ambiguity and a lack of geometric self-correction. Whi

local-aiarxiv-cs-ro

Neural Stereo Video Compression with Hybrid Disparity Compensation

arXiv:2504.20383v3 Announce Type: replace Abstract: Disparity compensation represents the primary strategy in stereo video compression (SVC) for exploiting cross-view redundancy. These mechanisms can

agentsarxiv-cs-cv

OmniDance: Multimodal Driven Dance Video Generation with Large-scale Internet Data

arXiv:2606.30019v1 Announce Type: new Abstract: Music-driven dance video generation aims to synthesize expressive human motion that is temporally aligned with music while maintaining high visual fidel

Applications

On Surrogate Modeling of Static Response of AM Short-Fiber Thermoplastics Using Graph Neural Networks

arXiv:2606.28996v1 Announce Type: new Abstract: Short-fiber thermoplastic (SFT) composites are increasingly employed in lightweight aerospace and automotive structures owing to their favorable strengt

applicationsarxiv-cs-lg

Local Ai

Online Data Selection for Instruction Tuning via Gaussian Processes

arXiv:2606.30077v1 Announce Type: cross Abstract: With Large Language Model (LLM) pre-training and fine-tuning shifting its focus from data volume to data quality, quality data selection has emerged a

local-aiarxiv-cs-ai

PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs

arXiv:2606.28898v1 Announce Type: new Abstract: Knowledge updating in pre-trained Large Language Models (LLMs) remains an important challenge. While continual training provides a potential avenue for

researcharxiv-cs-cl

PCP-GAN: Property-Constrained Pore-scale image reconstruction via conditional Generative Adversarial Networks

arXiv:2510.19465v2 Announce Type: replace Abstract: Obtaining truly representative pore-scale images that match bulk formation properties remains a fundamental challenge in subsurface characterization

Personalizing MLLMs via Reinforced Multimodal Reference Game

arXiv:2606.28845v1 Announce Type: new Abstract: Personalizing Multimodal Large Language Models (MLLMs) aims to recognize users' unique concepts from visual data and provide personalized responses. Alt

Tutorials

Physics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory

arXiv:2606.28630v1 Announce Type: new Abstract: Forecasting longitudinal brain lesion evolution is critical for disease monitoring and treatment planning. Existing approaches typically learn a direct

tutorialsarxiv-cs-cv

Privacy-Preserving Decentralized Cooperative Localization with Range-Only Measurements: A Convex Optimization Based Approach

arXiv:2606.29673v1 Announce Type: new Abstract: Cooperative localization using range-based measurements is critical for multi-robot systems operating in GPS-denied and unstructured environments. Howev

researcharxiv-cs-ro

Applications

Representation Learning for Equivariant Inference with Guarantees

arXiv:2505.19809v3 Announce Type: replace-cross Abstract: In many real-world applications of regression, conditional probability estimation, and uncertainty quantification, exploiting symmetries roote

applicationsarxiv-cs-ai

Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets

arXiv:2606.29837v1 Announce Type: new Abstract: Dataset distillation (DD) condenses large corpora into compact, information-rich subsets for efficient training and reuse. However, under noisy supervis

safetyarxiv-cs-cv

SA-Homo: Scale Adaptive Homography Estimation for Scale Variation Scenarios

model-releasesarxiv-cs-cv

arXiv:2606.30408v1 Announce Type: new Abstract: Homography estimation, as one of the fundamental problems in computer vision, remains challenged by scale variation scenarios where image pairs potentia

SafePyramid: A Hierarchical Benchmark for In-context Policy Guardrailing

model-releasesarxiv-cs-ai

arXiv:2606.29887v1 Announce Type: new Abstract: In real-world applications, guardrails are often expected to identify unsafe user-model interactions according to application-specific safety policies,

Tutorials

See, Think, Learn: A Self-Taught Multimodal Reasoner

arXiv:2512.02456v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved remarkable progress in integrating visual perception with language understanding. However, effecti

tutorialsarxiv-cs-cl

Semantic-Driven Scale and Spatial Selection for Efficient Cross-Modal Alignment in Referring Remote Sensing Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2606.30244v1 Announce Type: new Abstract: Referring Remote Sensing Image Segmentation (RRSIS) seeks to localize and segment the target object or region specified by a natural language expression

SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models

arXiv:2510.12784v2 Announce Type: replace-cross Abstract: Recently, remarkable progress has been made in Unified Multimodal Models (UMMs), which integrate vision-language generation and understanding

safetyarxiv-cs-cl

Stability Boundaries and Motor Performance in Delayed Robot-Mediated Dyadic Interactions

arXiv:2510.14511v3 Announce Type: replace Abstract: This paper establishes analytical stability boundaries for robot-mediated human-human (dyadic) interaction systems, subject to haptic communication

researcharxiv-cs-ro

Stay Unique, Stay Efficient: Preserving Model Personality in Multi-Task Merging

model-releasesarxiv-cs-cv

arXiv:2512.01461v2 Announce Type: replace-cross Abstract: Model merging has emerged as a promising paradigm for enabling multi-task capabilities without additional training. However, traditional basic

Synthetic Interaction Data for Scalable Personalization in Large Language Models

arXiv:2602.12394v2 Announce Type: replace Abstract: Personalized prompting offers large opportunities for deploying large language models (LLMs) to diverse users, yet existing prompt optimization meth

agentsarxiv-cs-lg

t-STEP: An interpretable model for Total Electron Content predictions and irregularities estimations

arXiv:2606.29644v1 Announce Type: new Abstract: Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheri

researcharxiv-cs-lg

The Forgetting-Retention Dilemma: Certified Unlearning Theory in Continual Learning

arXiv:2606.29832v1 Announce Type: new Abstract: Machine unlearning aims to eliminate the influence of specific data from trained models to safeguard privacy. However, this presents a significant chall

researcharxiv-cs-lg

The Interference Gap: Comparing Retrieval Bounds in Human Memory and RAG Systems

model-releasesarxiv-cs-ai

arXiv:2606.28327v1 Announce Type: cross Abstract: How do retrieval bounds compare between human episodic memory and Retrieval-Augmented Generation (RAG) systems under semantic interference? We present

Two-Stage Prompt Optimization for Few-Shot Relation Extraction: From Reasoning-Guided Search to Gradient-Guided Refinement

arXiv:2606.29639v1 Announce Type: cross Abstract: Automatic prompt optimization is still underexplored for episodic few-shot relation extraction with smaller language models. We propose a two-stage fr

Uncertainty Estimation in Pathology Foundation Models via Deep Mutual Learning

arXiv:2606.30020v1 Announce Type: new Abstract: Pathology foundation models (PFMs) offer generalizable representations for whole-slide image (WSI) analysis, yet their clinical adoption remains limited

Unified Enhancement of the Generalization and Robustness of Language Models via Bi-Stage Optimization

model-releasesarxiv-cs-cl

arXiv:2503.16550v2 Announce Type: replace Abstract: Neural network language models (LMs) are confronted with significant challenges in generalization and robustness. Currently, many studies focus on i

UniGP: Taming Diffusion Transformer for Prior-Preserved Unified Generation and Perception

arXiv:2606.30332v1 Announce Type: new Abstract: Recent advances in diffusion models have shown impressive performance in controllable image generation and dense prediction tasks. However, existing app

safetyarxiv-cs-cv

UniVAD v2: Unified Visual Anomaly Detection via Support-Conditioned Boundary Construction

arXiv:2606.29714v1 Announce Type: new Abstract: Unified visual anomaly detection seeks to train a single detector that can be deployed across categories, domains, and application scenarios. In the few

When LLMs Develop Languages: Symbolic Communication for Efficient Multi-Agent Reasoning

arXiv:2606.29354v1 Announce Type: new Abstract: Chain-of-Thought (CoT) improves large language models (LLMs) on difficult reasoning tasks, but it often incurs long natural-language rationales that are

agentsarxiv-cs-ai

Which Tokens Need Context? A Reference-Based Analysis of Translation Responsibility Using Fertility and Entropy

arXiv:2606.29489v1 Announce Type: new Abstract: When humans translate, not every word depends equally on the surrounding context. Some tokens, particularly function words like pronouns and auxiliaries

researcharxiv-cs-cl

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection

arXiv:2606.30587v1 Announce Type: cross Abstract: Researchers and practitioners increasingly apply Large Language Models (LLMs) for automated vulnerability detection. Recent work has shown that LLMs a

Artificial Intelligence Index Report 2026

arXiv:2606.15708v2 Announce Type: replace Abstract: Welcome to the ninth edition of the AI Index report. As AI continues to advance rapidly, the question becomes whether the systems built around it ca

Benchmarking on Tasks That Matter: Dataset Selection for Preserving Model Rankings

model-releasesarxiv-cs-lg

arXiv:2606.27997v1 Announce Type: new Abstract: Benchmarks of machine learning models often include many datasets, making evaluation expensive. For efficiency, it is preferable to perform evaluations

Beyond MoCap: Scaling Motion Tokenizers with Synthetic Human Motion for Generative Modeling

arXiv:2606.27547v1 Announce Type: new Abstract: Human motion generation models are fundamentally constrained by the limited diversity of motion capture datasets, which predominantly contain common, re

Contagion Networks: Evaluator Preference Propagation in Multi-Agent LLM Systems

model-releasesarxiv-cs-ai

arXiv:2606.20493v2 Announce Type: replace-cross Abstract: When large language models serve as evaluators in multi-agent systems, their strategy preferences -- whether induced by explicit prompts or by

Controllable Histopathology Image Synthesis with Training-free Structural Initialization and Textural Modulation

arXiv:2606.27935v1 Announce Type: new Abstract: Deep learning has demonstrated remarkable success in high-throughput histopathology image analysis. However, the performance of learning-based models cr

CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association

arXiv:2606.28179v1 Announce Type: cross Abstract: Identifying robust associations between cardiac imaging phenotypes and clinical diseases is fundamental to population-scale cardiovascular research an

DDSA: Dual-Domain Strategic Attack for Spatial-Temporal Efficiency in Adversarial Robustness Testing

arXiv:2601.14302v2 Announce Type: replace-cross Abstract: Image transmission and processing systems in resource-critical applications face significant challenges from adversarial perturbations that co

DexCompose: Reusing Dexterous Policies for Multi-Task Manipulation with a Single Hand

arXiv:2606.28323v1 Announce Type: cross Abstract: Dexterous manipulation policies can solve individual skills, but composing them to perform multiple tasks with a single hand remains challenging. Addi

From General-Purpose Audio Tagging to Spatially Grounded Sound Event Localization and Detection

arXiv:2606.27751v1 Announce Type: cross Abstract: This report investigates the extension of pretrained General-Purpose Audio Tagging (GP-AT) models toward spatially grounded Sound Event Localization a

Halt Fast! Early Stopping for Certified Robustness

arXiv:2606.27694v1 Announce Type: cross Abstract: Randomized Smoothing (RS) provides rigorous robustness guarantees for neural networks without architectural constraints, yet its adoption is limited b

Applications

KISS-IMU: Self-supervised Inertial Odometry with Motion-balanced Learning and Uncertainty-aware Inference

arXiv:2603.06205v2 Announce Type: replace Abstract: Inertial measurement units (IMUs), which provide high-frequency linear acceleration and angular velocity measurements, serve as fundamental sensing

applicationsarxiv-cs-ro