Search: “papers”

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

arXiv:2605.15760v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard

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Learning Dynamic Structural Specialization for Underwater Salient Object Detection

DGX agent

arXiv:2605.15535v1 Announce Type: new Abstract: Underwater salient object detection (USOD) has attracted increasing attention for underwater visual scene understanding and vision-guided robotic applic

model-releasesarxiv-cs-cv

18 May 2026

Applications

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity

arXiv:2605.15242v1 Announce Type: new Abstract: The reliability of Healthcare Information Systems (HIS) is frequently compromised by human-induced data entry errors, which existing statistical anomaly

applicationsarxiv-cs-lg

LRCP: Low-Rank Compressibility Guided Visual Token Pruning for Efficient LVLMs

arXiv:2605.15621v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal understanding, but their inference cost grows rapidly with the number of visual tokens, e

safetyarxiv-cs-cv

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation

arXiv:2605.15231v1 Announce Type: cross Abstract: Nonlinear finite element crash simulations are accurate but computationally expensive, limiting their use in iterative design optimisation. Machine-le

Multimodal Object Detection Under Sparse Forest-Canopy Occlusion

arXiv:2605.15326v1 Announce Type: new Abstract: Reliable detection of humans beneath forest canopy remains a difficult remote-sensing challenge due to sparse, structured, and viewpoint-dependent occlu

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

arXiv:2602.10687v3 Announce Type: replace-cross Abstract: Existing forgery detection methods are often limited to uni-modal or bi-modal settings, failing to handle the interleaved text, images, and vi

safetyarxiv-cs-ai

On RGB-TIR Stereo Calibration under Extreme Resolution Asymmetry

arXiv:2605.15860v1 Announce Type: new Abstract: Accurate geometric calibration of RGB-thermal infrared (TIR) stereo camera systems is essential for multimodal building envelope analysis, yet remains c

Agents

On the Convergence Rates of Federated Q-Learning across Heterogeneous Environments

arXiv:2409.03897v3 Announce Type: replace Abstract: Large-scale multi-agent systems are often deployed across wide geographic areas, where agents interact with heterogeneous environments. There is an

agentsarxiv-cs-lg

Online Vector Quantized Attention

arXiv:2602.03922v3 Announce Type: replace Abstract: Standard sequence mixing layers used in language models struggle to balance efficiency and performance. Self-attention performs well on long context

Operator-Controlled 6G: From Connectivity Infrastructure to Guaranteed Digital Services

arXiv:2605.15553v1 Announce Type: cross Abstract: Sixth-generation mobile networks (6G) are approaching a structural inflection point. Five generations of vendor-led architectures have left operators

Optimizing Line Segment Inspection with Limited-Range Drones

arXiv:2605.15765v1 Announce Type: cross Abstract: Optimization problems with drones are widely studied in a variety of civilian tasks, mainly due to their ability to traverse rough terrains and to car

researcharxiv-cs-ro

Perforated Neural Networks for Keyword Spotting

model-releasesarxiv-cs-lg

arXiv:2605.15647v1 Announce Type: new Abstract: Edge machine learning presents a unique set of constraints not encountered in cloud-scale model deployment: strict memory budgets, limited compute, and

Position: Ideas Should be the Center of Machine Learning Research

model-releasesarxiv-cs-lg

arXiv:2605.15253v1 Announce Type: new Abstract: Machine learning research increasingly bifurcates into two disconnected modes: benchmark-driven engineering that prioritizes metrics over understanding,

PRB-RUPFormer: A Recursive Unified Probabilistic Transformer for Residual PRB Forecasting

arXiv:2605.15363v1 Announce Type: new Abstract: Accurate forecasting of residual Physical Resource Blocks (PRBs) is critical for proactive network slice provisioning, energy-efficient operation, and s

Applications

Preprocessing Algorithm Leveraging Geometric Modeling for Scale Correction in Hyperspectral Images for Improved Unmixing Performance

arXiv:2508.08431v3 Announce Type: replace-cross Abstract: Spectral variability significantly impacts the accuracy and convergence of hyperspectral unmixing algorithms. Many methods address complex spe

applicationsarxiv-cs-cv

Quantum Artificial Intelligence for Mission-Critical Systems: Foundations, Architectural Elements, and Future Directions

arXiv:2511.09884v2 Announce Type: replace Abstract: Mission critical (MC) applications such as defense operations, energy management, cybersecurity, and aerospace control require reliable, determinist

safetyarxiv-cs-ai

RAR: Retrieving And Ranking Augmented MLLMs for Visual Recognition

model-releasesarxiv-cs-ai

arXiv:2403.13805v2 Announce Type: replace-cross Abstract: CLIP (Contrastive Language-Image Pre-training) uses contrastive learning from noise image-text pairs to excel at recognizing a wide array of c

Robust Prior-Guided Segmentation for Editable 3D Gaussian Splatting

arXiv:2605.16065v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3D-GS) enables real-time 3D scene reconstruction but lacks robust segmentation for editing tasks such as object removal, extrac

SafeGPT: Preventing Data Leakage and Unethical Outputs in Enterprise LLM Use

arXiv:2601.06366v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are transforming enterprise workflows but introduce security and ethics challenges when employees inadvertently s

safetyarxiv-cs-ai

Sampling-Based Global Optimal Control and Estimation via Semidefinite Programming

arXiv:2507.17572v3 Announce Type: replace Abstract: Global optimization has gained attraction over the past decades, thanks to the development of both theoretical foundations and efficient numerical r

researcharxiv-cs-ro

Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs

arXiv:2503.02597v3 Announce Type: replace-cross Abstract: Recent Multimodal Large Language Models (MLLMs) have demonstrated significant progress in perceiving and reasoning over multimodal inquiries,

Local Ai

Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning

arXiv:2605.15997v1 Announce Type: new Abstract: Recent progress in deep learning has significantly advanced CT image analysis, particularly for segmentation tasks. However, these advances are largely

local-aiarxiv-cs-cv

Self-Prompting Diffusion Transformer for Open-Vocabulary Scene Text Editing via In-Context Learning

arXiv:2605.15523v1 Announce Type: new Abstract: Scene text editing aims to modify text in a target region of an image while preserving surrounding background style and texture. Existing methods rely s

Self-Supervised ImageNet Representations for In Vivo Confocal Microscopy: Tortuosity Grading without Segmentation Maps

arXiv:2603.15269v2 Announce Type: replace Abstract: The tortuosity of corneal nerve fibers are used as indication for different diseases. Current state-of-the-art methods for grading the tortuosity he

Self-Supervised Learning by Curvature Alignment

arXiv:2511.17426v2 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has recently advanced through non-contrastive methods that couple an invariance term with variance, covariance,

safetyarxiv-cs-cv

SemanticOpt: Towards LLM-Based Semantic Black-Box Optimization

model-releasesarxiv-cs-ai

arXiv:2510.25404v3 Announce Type: replace-cross Abstract: Optimizing an experimental system can be extremely challenging when each experiment is expensive, time-consuming, or difficult to perform. Exi

Agents

Shaping Sparse Rewards in Reinforcement Learning: A Semi-supervised Approach

arXiv:2501.19128v5 Announce Type: replace-cross Abstract: In many real-world scenarios, reward signal for agents are exceedingly sparse, making it challenging to learn an effective reward function for

agentsarxiv-cs-ai

Tutorials

Simultaneous State Estimation and Online Model Learning in a Soft Robotic System

arXiv:2602.14092v2 Announce Type: replace-cross Abstract: Operating complex real-world systems, such as soft robots, can benefit from precise predictive control schemes that require accurate state and

tutorialsarxiv-cs-ro

SkyLink: A Large Vision-Language Model Driven Re-ranking Framework for Cross-View UAV geolocalization

arXiv:2603.08063v3 Announce Type: replace Abstract: Cross-view UAV geolocalization is fundamentally a challenging large-scale image retrieval task, aiming to determine the geographic coordinates of Un

Skyra: AI-Generated Video Detection via Grounded Artifact Reasoning

arXiv:2512.15693v2 Announce Type: replace Abstract: The misuse of AI-driven video generation technologies has raised serious social concerns, highlighting the urgent need for reliable AI-generated vid

Smoothie: Smoothing Diffusion on Token Embeddings for Text Generation

arXiv:2505.18853v2 Announce Type: replace Abstract: Diffusion models have achieved state-of-the-art performance in generating images, audio, and video, but their adaptation to text remains challenging

researcharxiv-cs-cl

Sparse ActionGen: Accelerating Diffusion Policy with Real-time Pruning

arXiv:2601.12894v2 Announce Type: replace-cross Abstract: Diffusion Policy has dominated action generation due to its strong capabilities for modeling multi-modal action distributions, but its multi-s

Spectral Priors vs. Attention: Investigating the Utility of Attention Mechanisms in EEG-Based Diagnosis

arXiv:2605.15433v1 Announce Type: new Abstract: Electroencephalograph (EEG) timeseries signals are characterized by significant noise and coarse spatial resolution, which complicates the classificatio

STABLE: Simulation-Ready Tabletop Layout Generation via a Semantics-Physics Dual System

arXiv:2605.16137v1 Announce Type: new Abstract: Generating simulation-ready tabletop scenes from task instructions is an intriguing and promising research direction in the field of Embodied AI. Howeve

safetyarxiv-cs-cv

STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices

model-releasesarxiv-cs-ai

arXiv:2605.15581v1 Announce Type: new Abstract: LLM-based root cause analysis (RCA) agents have recently emerged as a promising paradigm for incident diagnosis in microservice AIOps. However, their re

Stock Market Prediction Using Node Transformer Architecture Integrated with BERT Sentiment Analysis

arXiv:2603.05917v3 Announce Type: replace-cross Abstract: Stock market prediction presents considerable challenges for investors, financial institutions, and policymakers operating in complex market e

Task-Semantic Graph-Driven Distributed Agent Networking for Underwater Target Tracking

arXiv:2605.15528v1 Announce Type: new Abstract: Autonomous underwater vehicle (AUV) swarms are emerging as intelligent underwater networks, where each node must sense, communicate, process local data,

safetyarxiv-cs-ro

Testing properties of trees in graphical models with covariance queries

arXiv:2605.15996v1 Announce Type: cross Abstract: We consider the problem of testing properties of graphs underlying high-dimensional graphical models. We adopt the model of covariance queries introdu

Text-RSIR: A Text-Guided Framework for Efficient Remote Sensing Image Transmission and Reconstruction

arXiv:2605.15558v1 Announce Type: cross Abstract: High-resolution remote sensing imagery is critical for environmental monitoring, urban mapping, and land cover analysis, but its transmission is often

Local Ai

Ti-iLSTM: A TinyDL Approach for Logic-Level Anomaly Detection in Industrial Water Treatment Systems

arXiv:2605.15874v1 Announce Type: new Abstract: Industrial Water Treatment Systems (IWTS) are safety critical cyber-physical infrastructures and due to increased connectivity, these systems are expose

local-aiarxiv-cs-lg

Towards a more realistic evaluation of machine learning models for bearing fault diagnosis

arXiv:2509.22267v4 Announce Type: replace Abstract: Reliable detection of bearing faults is essential for maintaining the safety and operational efficiency of rotating machinery. While recent advances

safetyarxiv-cs-lg

Transformer Scalability Crisis: The First Comprehensive Empirical Analysis of Performance Walls in Modern Language Models

model-releasesarxiv-cs-lg

arXiv:2605.15413v1 Announce Type: new Abstract: Despite the remarkable success of transformer architectures in natural language processing, their scalability limitations remain poorly understood throu

Two-Dimensional Quantization for Geometry-Aware Audio Coding

arXiv:2512.01537v2 Announce Type: replace-cross Abstract: Recent neural audio codecs have achieved impressive reconstruction quality, typically relying on quantization methods such as Residual Vector

Unified High-Probability Analysis of Stochastic Variance-Reduced Estimation

arXiv:2605.15388v1 Announce Type: new Abstract: Stochastic estimators are fundamental to large-scale optimization, where population quantities must be inferred from noisy oracle observations. Although

safetyarxiv-cs-lg

Unlocking Dense Metric Depth Estimation in VLMs

arXiv:2605.15876v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at 2D tasks such as grounding and captioning, yet remain limited in 3D understanding. A key limitation is their text

Unveiling the Black Box: A Multi-Layer Framework for Explaining Reinforcement Learning-Based Cyber Agents

arXiv:2505.11708v3 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) agents are increasingly used to simulate sophisticated cyberattacks, but their decision-making processes remain op

safetyarxiv-cs-lg

Variational Autoregressive Networks with probability priors

arXiv:2605.16020v1 Announce Type: new Abstract: Monte Carlo methods are essential across diverse scientific fields, yet their efficiency is frequently hampered by critical slowing down-a sharp increas