applications

Cybernetic Android Avatar 'Yui': System Integration, Field Deployment, and Evaluation

arXiv:2606.08099v1 Announce Type: new Abstract: Remote communication technologies have become widely used; however, supporting a sense of shared physical space and conveying rich non-verbal cues remai

applicationsarxiv-cs-ro

Detecting Aimbot Cheaters in MOGs

DGX agent

arXiv:2606.07650v1 Announce Type: cross Abstract: Multiplayer Online Games have become a multibillion dollar industry in the entertainment sector. However, the presence of cheaters undermines the expe

applicationsarxiv-cs-cv

9 Jun 2026

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

DOME: Learning Transferable Domain Variables from Sparse Supervision for Test-Time Adaptation

arXiv:2606.07646v1 Announce Type: cross Abstract: Test-time adaptation (TTA) aims to align a model to shifting test domains using only unlabeled streaming data. Most existing methods implicitly infer

DroneDAR: Long-Range Drone Distance Estimation Using Monocular Vision and Bounding-Box Features

arXiv:2606.07756v1 Announce Type: new Abstract: Accurate distance estimation for small drones in long-range imagery is important for tracking and situational awareness, yet remains challenging due to

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

DynaOD: Dynamic Origin-Destination Flow Generation with Discrete-to-Continuous Temporal Semantic Modeling

arXiv:2606.09086v1 Announce Type: new Abstract: Dynamic origin-destination (OD) flow generation seeks to synthesize realistic mobility dynamics from temporal context alone, without relying on historic

eBook: Exploring the Future of AI Infrastructure

As AI moves from experimentation to production, infrastructure requirements are evolving rapidly. This eBook examines the market, technology, and operational shifts driving the next generation of clou

applicationsvultr

Efficient Scaling of LLM Training with Flexible Context Parallelism

arXiv:2602.21788v2 Announce Type: replace-cross Abstract: Scaling long-context capabilities is crucial for Large Language Models (LLMs). However, real-world data contain a large number of sequences wi

Enhancing Strawberry Yield Forecasting with Backcasted IoT Sensor Data and Machine Learning

arXiv:2504.18451v2 Announce Type: replace Abstract: Rapid global population growth underscores the need for digitally enabled agricultural systems that support sustainable food production and data-dri

Fable: 'create a visually interesting shader that can run in twigl-dot-app make it like an infinite city of neo-gothic towers partially drow…

applicationsethan-mollick--x

Fable: 'create a visually interesting shader that can run in twigl-dot-app make it like an infinite city of neo-gothic towers partially drowned in a stormy ocean with large waves.' 'Make it better' Al

FAWAM: Force-Aware World Action Models for Closed-Loop Contact-Rich Manipulation

arXiv:2606.08555v1 Announce Type: new Abstract: Force signals provide critical interaction cues for contact-rich robotic manipulation. However, existing methods mostly use force as an additional obser

applicationsarxiv-cs-ro

FF-JEPA: Long-Horizon Planning in World Models with Latent Planners

arXiv:2606.09311v1 Announce Type: new Abstract: Joint Embedding Predictive Architectures (JEPAs) have shown promising world modeling capabilities, enabling planning in latent space by optimizing actio

FMplex: Model Virtualization for Serving Extensible Foundation Models

arXiv:2606.09643v1 Announce Type: cross Abstract: Foundation models (FMs) are increasingly used as backbones for downstream tasks across language, vision, time-series, and multimodal applications. Yet

From Shortcuts to Reasoning: Robust Post-Training of Theory of Mind with Reinforcement Learning

arXiv:2606.09092v1 Announce Type: new Abstract: Theory of Mind (ToM) is a must-acquire skill for modern foundation model systems to operate effectively and safely in the real world. Recent works have

G2G: Exploiting Intra-Group Geometry for Inter-Group Pose Estimation

arXiv:2606.08284v1 Announce Type: new Abstract: Recovering the relative 6-DoF pose between two image groups underlies cross-sequence relocalization and multi-camera rig odometry. Each group carries kn

GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators

arXiv:2606.08343v1 Announce Type: new Abstract: We introduce GENERIC-FNO, the first neural operator to embed the full GENERIC (metriplectic) structure of nonequilibrium thermodynamics -- reversible, e

GimmBO: Interactive Generative Image Model Merging via Bayesian Optimization

arXiv:2601.18585v2 Announce Type: replace Abstract: Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapter

Have I Solved This Before? Retrieving Similar Segmentation Problems for Evolutionary Learning

arXiv:2606.08155v1 Announce Type: new Abstract: Reliable integration and solid configuration of monitoring systems constitute a fundamental prerequisites for achieving high efficiency and productivity

Heterophily-Aware Adaptive Knowledge Distillation for Hypergraph Neural Networks

arXiv:2606.08978v1 Announce Type: new Abstract: Hypergraph knowledge distillation aims to retain the predictive performance of a hypergraph neural network (HNN) teacher while reducing inference costs

Hybrid Neural Network and Conventional Controller Approach for Robust Control of Highly Unstable Systems: Application to Tilt-Rotor Control

arXiv:2606.08714v1 Announce Type: cross Abstract: Multirotors are widely used in applications ranging from surveillance to precision agriculture, yet conventional designs remain limited by their under

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation

arXiv:2509.10334v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) have recently achieved strong results in semantic segmentation, yet their deployment on resource-constrained device

I want to share some thoughts about the impact of AI on org structure. This is based on early conversations with some of the top CHROs in Fo…

applicationsallie-k--miller--x

I want to share some thoughts about the impact of AI on org structure. This is based on early conversations with some of the top CHROs in Fortune 500 companies as well as other C-Suite leaders and sta

iMaC: Translating Actions into Motion and Contact Images for Embodied World Models

arXiv:2606.09813v1 Announce Type: cross Abstract: Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and interactive environment simulation. However, conventio

In-Context Learning of Stochastic Differential Equations with Foundation Inference Models

arXiv:2502.19049v3 Announce Type: replace Abstract: Stochastic differential equations (SDEs) describe dynamical systems where deterministic flows, governed by a drift function, are superimposed with r

Infrastructure reality check: Broadcom makes the private cloud case for AI

Production AI is pushing private cloud back into the center of enterprise infrastructure. The shift is not just about where workloads run. It is about cost control, security, governance and the need t

applicationssiliconangle

Jas: AI-Paired Engineering as a Revival of N-Version Programming

arXiv:2606.07828v1 Announce Type: cross Abstract: I report a case study in AI-paired software engineering: five working ports of a vector illustration application across Rust, Swift, OCaml, Python, an

Kalshi plans to require users seeking to make bets in some markets linked to material nonpublic information to submit an online form disclosing where they work (Wall Street Journal)

Wall Street Journal: Kalshi plans to require users seeking to make bets in some markets linked to material nonpublic information to submit an online form disclosing where they work — The popular predi

applicationstechmeme

Land cover and flood type govern the detection limits of satellite-based flood mapping across diverse global flood events

arXiv:2606.07780v1 Announce Type: new Abstract: Floods are among the most destructive natural hazards, and their increasing frequency under climate change makes satellite-based inundation mapping esse

Larch: Learned Query Optimization for Semantic Predicates

arXiv:2606.07923v1 Announce Type: cross Abstract: With the advent of Large Language Models (LLMs), many database systems introduced semantic operators that enabled analytical queries over unstructured

Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook

arXiv:2310.10196v3 Announce Type: replace-cross Abstract: Temporal data, including time series and spatio-temporal data, are pervasive in real-world applications. Generated in massive volumes by physi

Latent Structural Categorical Matrix Completion with Application to Quasispecies Analysis

arXiv:2606.08188v1 Announce Type: cross Abstract: Matrix completion has been extensively studied for real-valued data, but existing methods are often limited in handling categorical variables. We prop

Lattice: A Confidence-Gated Hybrid System for Uncertainty-Aware Sequential Prediction with Behavioral Archetypes

arXiv:2601.15423v2 Announce Type: replace Abstract: We introduce Lattice, a hybrid sequential prediction system that conditionally activates learned behavioral structure using binary confidence gating

Learning to lead in a hybrid human-AI enterprise

applicationsmit-tech-review

As adoption of AI agents looks set to surge by as much as 300% in the next two years, leadership teams are carefully considering the implications of a hybrid human-AI workforce. Unlike existing enterp

LLM-Orchestrated Conformance Checking in Stroke Care Without Computer-Interpretable Guidelines

arXiv:2606.09489v1 Announce Type: new Abstract: Objective: Conformance checking in healthcare seeks to assess whether patient care pathways adhere to clinical guidelines. However, its practical applic

LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty

arXiv:2503.18314v5 Announce Type: replace-cross Abstract: We present LoTUS, a novel Machine Unlearning (MU) method that eliminates the influence of training samples from pre-trained models, avoiding r

MedicalRec: Medical recommender system for image classification without retraining

arXiv:2606.07553v1 Announce Type: cross Abstract: The emergence of machine learning and deep learning has revolutionized the efficiency of diagnostic, therapeutic, and administrative systems in health

Minimal Solvers for Full-DoF Motion Estimation from Asynchronous Differential SfM

arXiv:2606.09218v1 Announce Type: new Abstract: As a bio-inspired intelligent sensor, event cameras have introduced a new paradigm in the intelligent perception of spatiotemporal information and visua

Modeling Stochastic Conditional Dynamics from Sparse Observations via Kernel-Stabilized Flow Matching

arXiv:2411.08314v5 Announce Type: replace Abstract: Learning to transform conditional probability densities over time is a fundamental challenge spanning probabilistic modeling and the natural science

Modeling the Diachronic Evolution of Legal Norms: An LRMoo-Based, Component-Level, Event-Centric Approach to Legal Knowledge Graphs

arXiv:2506.07853v5 Announce Type: replace Abstract: Representing the temporal evolution of legal norms is a critical challenge for automated processing. While foundational frameworks exist, they lack

Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention

arXiv:2606.09271v1 Announce Type: cross Abstract: Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria.

Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach

arXiv:2606.07585v1 Announce Type: cross Abstract: This thesis addresses group emotion recognition (GER) in-the-wild with a focus on privacy preservation. Unlike traditional emotion recognition methods

Next-Token Prediction Learns Generalisable Representations of Sleep Physiology

arXiv:2606.09605v1 Announce Type: new Abstract: Foundation models offer a promising route to compress multi-modal physiological signals into compact representations of human health, with broad applica

Nonparametric LLM Evaluation from Preference Data

arXiv:2601.21816v2 Announce Type: replace Abstract: Evaluating the performance of large language models (LLMs) from human preference data is crucial for obtaining LLM leaderboards. However, many exist

Online Learning for Supervisory Switching Control

arXiv:2603.14762v3 Announce Type: replace-cross Abstract: We study supervisory switching control for partially-observed linear dynamical systems. The objective is to identify and deploy a suitable con

Optical Music Recognition for Real-World Manuscripts with Synthetic Data

arXiv:2606.09479v1 Announce Type: new Abstract: Optical Music Recognition (OMR) has seen major progress in model design, with end-to-end methods now capable of recognising notation at all levels of co

Personalized and Robust Proactive Robot Assistance with Uncertainty-Guided LLM Reasoning

arXiv:2606.08458v1 Announce Type: new Abstract: Proactive robot assistance in household environments requires accurate prediction of human activities and object usage under dynamic and noisy condition

applicationsarxiv-cs-ro

PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning

arXiv:2606.08655v1 Announce Type: cross Abstract: To perform a wide range of daily tasks, robots need to construct a 3D representation that is semantically rich, physically grounded, and structured en