applications

A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data

arXiv:2601.17717v3 Announce Type: replace Abstract: Large Language Models (LLMs) have emerged as powerful tools for generating data across various modalities. By transforming data from a scarce resour

Applications

Applied Materials opens a $500M chip equipment manufacturing campus in Singapore, making the city-state home to ~50% of its production capacity alongside the US (Cheng Ting-Fang/Nikkei Asia)

DGX agent

Cheng Ting-Fang / Nikkei Asia: Applied Materials opens a 500M chip equipment manufacturing campus in Singapore, making the city-state home to ~50% of its production capacity alongside the US — SINGAPO

applicationstechmeme

11 Jun 2026

Bridging the Modality Gap in Forensic Image Retrieval

arXiv:2606.12294v1 Announce Type: new Abstract: Automated image retrieval plays an increasingly critical role in modern forensic analysis, supporting investigative workflows that rely on efficient com

CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting

arXiv:2511.09789v2 Announce Type: replace Abstract: Recent advances in deep forecasting models have achieved remarkable performance, yet most approaches still struggle to provide both accurate predict

Categorical Robustness Assessment for Machine Learning based Network Intrusion Detection Systems

arXiv:2606.12075v1 Announce Type: cross Abstract: Network Intrusion Detection Systems (NIDS) heavily utlize Machine Learning (ML) but ML models can be manipulated via adversarial attacks. These attack

Contactless 3D Human Body Measurement Using Depth Cameras for Smart Health Monitoring

arXiv:2606.11578v1 Announce Type: new Abstract: Contactless body measurement technologies are becoming increasingly significant for smart health monitoring, digital health applications, and remote pat

DAM-VLA: Decoupled Asynchronous Multimodal Vision Language Action model

arXiv:2606.12105v1 Announce Type: cross Abstract: Vision-language-action (VLA) models inherit a shared synchronous clock from vision-language pretraining, processing every input at one rate. This is m

DeceptionX: Explainable Deception Detection with Multimodal Large Language Models

arXiv:2606.11385v1 Announce Type: new Abstract: Deception detection is a critical and highly challenging task within affective computing and behavioral analysis. Existing deep learning methods typical

Deformable In-Hand Slip-Aware Tactile Sensor with Integrated Velocity, Force/Torque, and Pressure Map Sensing

arXiv:2606.11952v1 Announce Type: new Abstract: This paper introduces a novel tactile sensor for in-hand manipulation with slip-aware control that integrates velocity, force/torque, and pressure map s

Detecting AI-Generated Content on Social Media with Multi-modal Language Models

arXiv:2606.11200v1 Announce Type: new Abstract: Generative AI has enabled the creation of photorealistic images and videos that are increasingly disseminated on social media, often used for spam, misi

applicationsarxiv-cs-cl

Diffusion-based Cumulative Adversarial Purification for Vision Language Models

arXiv:2506.03933v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown remarkable capabilities in multimodal understanding, yet their susceptibility to adversarial perturba

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners?

arXiv:2606.12402v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time com

Fast-SDE: Efficient Single-Microphone Sound Source Distance Estimation in Reverberant Environments

arXiv:2606.12339v1 Announce Type: cross Abstract: Sound source distance estimation (SDE) is a critical capability in human-robot interaction. An inappropriate interaction distance not only reduces the

Federated continual learning: A comprehensive survey on lifelong and privacy-preserving learning over distributed and non-stationary data

arXiv:2606.11272v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative and privacy-preserving model training across distributed clients, but most existing FL systems implicitl

Few-Shot Resampling for Scalable Statistically-Sound Data Mining

arXiv:2606.11235v1 Announce Type: new Abstract: A key step in knowledge discovery is the evaluation of data mining results. In several applications, including pattern mining, graph analysis, and other

FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI

arXiv:2606.11500v1 Announce Type: cross Abstract: The success of large-scale deep learning models in neuroscience is fundamentally constrained by severe data heterogeneity. Native fMRI data aggregated

FOCUS on Contamination: Hydrology-Informed Noise-Aware Learning for Geospatial PFAS Mapping

arXiv:2502.14894v5 Announce Type: replace-cross Abstract: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with significant public health impacts, yet large-scale m

From Uniform to Learned Graph Priors: Diffusion for Structure Discovery

arXiv:2606.11831v1 Announce Type: cross Abstract: Neural relational inference (NRI) methods discover interaction graphs from trajectories through variational reasoning on discrete potential edges. How

HiPi: Reproducible High-Fidelity Piezoresistive Sensors for Robotic Manipulation

arXiv:2606.11372v1 Announce Type: new Abstract: Piezoresistive tactile sensors are attractive for robotic manipulation because they are thin, lightweight, low-cost, and scalable to dense large-area se

Improving Human Diving Endurance with a Field-Deployable, Untethered Exoskeleton

arXiv:2606.11704v1 Announce Type: new Abstract: Human endurance in underwater locomotion is fundamentally restricted by high energetic demands to overcome drag and the finite supply of self-contained

Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions

arXiv:2604.25018v2 Announce Type: replace-cross Abstract: The Internet of Everything (IoE) represents an evolution of the Internet of Things (IoT) by integrating people, data, processes, and things in

LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data

arXiv:2606.11268v1 Announce Type: new Abstract: Understanding and forecasting lake dynamics is critical for monitoring water quality and ecosystem health across lakes and reservoirs. While machine lea

LaQual: An Automated Framework for LLM App Quality Evaluation

arXiv:2508.18636v2 Announce Type: replace-cross Abstract: Representing a new paradigm in software distribution, LLM app stores are rapidly emerging, offering users diverse choices for content generati

Learning Unions of Convex Sets via Invertible Latent Decomposition for Path Planning

arXiv:2606.12027v1 Announce Type: new Abstract: Collision-free path planning in cluttered, real-world environments relies on a representation of the collision-free space, and existing representations

M4FC: a Multimodal, Multilingual, Multicultural, Multitask Real-World Fact-Checking Dataset

arXiv:2510.23508v3 Announce Type: replace Abstract: Existing real-world datasets for multimodal fact-checking have multiple limitations: they contain few instances, cover on only one or two languages,

applicationsarxiv-cs-cl

MLaGA: Multimodal Large Language and Graph Assistant

arXiv:2506.02568v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated substantial efficacy in advancing graph-structured data analysis. Prevailing LLM-based graph methods

Momentum LMS Theory beyond Stationarity: Stability, Tracking, and Regret

arXiv:2602.11995v2 Announce Type: replace Abstract: In large-scale data processing scenarios, data often arrive in sequential streams generated by complex systems that exhibit drifting distributions a

Noise-Aware Framework for Correcting Corrupted Labels

arXiv:2606.11695v1 Announce Type: cross Abstract: High-quality labeled data is essential for training reliable ML/DL models. However, real-world datasets often contain a considerable proportion of cor

Non-Equilibrium MAV-Capture-MAV via Time-Optimal Planning and Reinforcement Learning

arXiv:2503.06578v2 Announce Type: replace Abstract: The capture of flying MAVs (micro aerial vehicles) has garnered increasing research attention due to its intriguing challenges and promising applica

Phase-Based Multi-Gait Learning for a Salamander-Like Robot

arXiv:2511.08299v2 Announce Type: replace Abstract: Salamander-like robots are designed inspired by the skeletal structure of their biological counterparts. However, existing controllers cannot fully

Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

arXiv:2606.11605v1 Announce Type: cross Abstract: Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex

Privacy-Preserving Federated Autoencoder for ECG Anomaly Detection on Edge Devices

arXiv:2606.11556v1 Announce Type: cross Abstract: Continuous electrocardiography (ECG) monitoring could surface rhythm abnormalities before they escalate into cardiovascular events. However, a deploya

SpikeTAD: Spiking Neural Networks for End-to-End Temporal Action Detection

arXiv:2606.12033v1 Announce Type: new Abstract: Video understanding is a crucial part of computer vision, with numerous application scenarios. With the increasing popularity of mobile devices, an incr

T2MM: An LLM Supported Architecture For Inquiry-Based Modeling

arXiv:2606.11210v1 Announce Type: cross Abstract: Model Construction is a foundational practice in science learning that relies on visualization and interactivity. Large Language Models, increasingly

TAROT: Task-Adaptive Refinement of LLM-prior Graphs for Few-shot Tabular Learning

arXiv:2606.11640v1 Announce Type: cross Abstract: Few-shot tabular learning provides a cost-effective approach for real-world applications where annotation is costly and collecting sufficient samples

'That's AI Slop, You Bot!' Studying Accusations, Evidence, and Credibility in Online Discourse Towards LLM-Generated Comments

arXiv:2606.12073v1 Announce Type: cross Abstract: Generative AI has made fluent prose cheap to produce, breaking the old promise to readers that good writing meant real thinking. How have readers resp

The Environmental Cost of LLMs in AIED: Reporting and Practices

arXiv:2606.11215v1 Announce Type: cross Abstract: Large Language Model (LLM) usage in recent years has become increasingly widespread in the Artificial Intelligence in Education (AIED) community. Whil

TRON: Tracing Rays to Orchestrate a Neural Renderer for 3D Gaussian Reconstructions

arXiv:2606.11314v1 Announce Type: new Abstract: We introduce TRON, a rendering framework that combines 3D Gaussian ray tracing with neural rendering to enable realistic and controllable rendering of r

Unifying Learning Dynamics and Generalization in Transformers Scaling Law

arXiv:2512.22088v3 Announce Type: replace-cross Abstract: The scaling law, a cornerstone of Large Language Model (LLM) development, predicts improvements in model performance with increasing computati

uva-irlab-conv at SemEval-2026 Task 8: Multi-Turn RAG with Learned Sparse Retrieval and Listwise Reranking

arXiv:2606.11945v1 Announce Type: new Abstract: This report describes our participation in SemEval-2026 Task 8 on multi-turn retrieval and question answering. The task evaluates conversational systems

applicationsarxiv-cs-cl

Wild3R: Feed-Forward 3D Gaussian Splatting from Unconstrained Sparse Photo Collection

arXiv:2606.11894v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) removes the need for time-consuming per-scene optimization required by traditional 3DGS. However, existing fee

A Comprehensive Inference-Time Augmentation Framework in Physiological Signals: Application to PPG-Based AF Detection

arXiv:2606.10410v1 Announce Type: new Abstract: Objective: Accurate classification of physiological signals in real-world deployments is challenged by sensor noise, motion artifacts, and distribution

A Machine Learning Theory Perspective on Strategic Litigation

arXiv:2506.03411v2 Announce Type: replace Abstract: Strategic litigation involves bringing a case to court with the goal of having an impact beyond resolving the particular dispute at hand. In a commo

A Theory on Flow Matching with Neural Networks

arXiv:2606.10089v1 Announce Type: cross Abstract: In this work, we develop theoretical foundation for flow matching with neural-network-parameterized conditional velocity fields. We establish converge

ABot-Earth 0.5: Generative 3D Earth Model

arXiv:2606.09967v1 Announce Type: new Abstract: We present ABot-Earth 0.5, a generative 3D framework designed to synthesize vast, seamless 3D environments from ubiquitous, geospatially referenced sate

Access OpenAI models and Codex through your Oracle cloud commitment

OpenAI models and Codex are available to Oracle Cloud customers through an integrated partnership, allowing users to access these AI capabilities within their existing Oracle cloud infrastructure and

applicationsopenai

Active-Passive Federated Learning for Vertically Partitioned Multi-view Data

arXiv:2409.04111v2 Announce Type: replace Abstract: Vertical federated learning is a natural and elegant approach to integrate multi-view data vertically partitioned across devices (clients) while pre

AI Serving Platform That Adapts to Your Model

Databricks offers an AI serving platform designed to flexibly accommodate different machine learning models and their specific requirements. The platform likely provides features for deploying, scalin

applicationsdatabricks