applications

ComfyStudio is open. We're launching a physical R&D studio and artist residency program in LA this May pairing working VFX artists, animator…

ComfyStudio is open. We're launching a physical R&D studio and artist residency program in LA this May pairing working VFX artists, animators, and pipeline folks with the ComfyUI team to build hybrid

applicationscomfyui--x

Applications

Comparative Insights on Adversarial Machine Learning from Industry and Academia: A User-Study Approach

DGX agent

arXiv:2602.04753v2 Announce Type: replace-cross Abstract: An exponential growth of Machine Learning and its Generative AI applications brings with it significant security challenges, often referred to

applicationsarxiv-cs-ai

28 Apr 2026

Computational Design and Co-Robotic Fabrication for Material Reuse in Architecture

arXiv:2604.24648v1 Announce Type: new Abstract: Climate change and resource depletion demand a shift from the dominant linear 'take-make-use-dispose' paradigm of construction toward circular, low-wast

Contrastive Learning for Multimodal Human Activity Recognition with Limited Labeled Data

arXiv:2604.23281v1 Announce Type: cross Abstract: Human activity recognition serves as the foundation for various emerging applications. In recent years, researchers have used collaborative sensing of

CyberCane: Neuro-Symbolic RAG for Privacy-Preserving Phishing Detection with Formal Ontology Reasoning

arXiv:2604.23563v1 Announce Type: cross Abstract: Privacy-critical domains require phishing detection systems that satisfy contradictory constraints: near-zero false positives to prevent workflow disr

Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring

arXiv:2511.23036v2 Announce Type: replace-cross Abstract: Explaining online time series monitoring models is crucial across sensitive domains such as healthcare and finance, where temporal and context

DenoGrad: A Gradient-Based Framework for Data Refinement in Tabular and Time-Series Learning

arXiv:2511.10161v2 Announce Type: replace Abstract: In the Data-Centric Artificial Intelligence (AI) paradigm, improving data quality is essential for robust machine learning. However, many denoising

Do Protective Perturbations Really Protect Portrait Privacy under Real-world Image Transformations?

arXiv:2604.23688v1 Announce Type: new Abstract: Proactive defense methods protect portrait images from unauthorized editing or talking face generation (TFG) by introducing pixel-level protective pertu

Dual-domain Multi-path Self-supervised Diffusion Model for Accelerated MRI Reconstruction

arXiv:2503.18836v2 Announce Type: replace-cross Abstract: Magnetic resonance imaging (MRI) is a vital diagnostic tool, but its inherently long acquisition times reduce clinical efficiency and patient

DualGuard: Dual-stream Large Language Model Watermarking Defense against Paraphrase and Spoofing Attack

arXiv:2512.16182v2 Announce Type: replace-cross Abstract: With the rapid development of cloud-based services, large language models have become increasingly accessible through various web platforms. H

EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks

arXiv:2604.23570v1 Announce Type: new Abstract: The advancement of robot learning is currently hindered by the scarcity of large-scale, high-quality datasets. While established data collection methods

Equivariant Filter for Radar-Inertial Odometry

arXiv:2604.23033v1 Announce Type: new Abstract: Radar-Inertial Odometry (RIO) based on the Extended Kalman Filter (EKF) relies on accurate extrinsic calibration between the radar and the Inertial Meas

ESPADA: Execution Speedup via Semantics Aware Demonstration Data Downsampling for Imitation Learning

arXiv:2512.07371v3 Announce Type: replace-cross Abstract: Behavior-cloning based visuomotor policies enable precise manipulation but often inherit the slow, cautious tempo of human demonstrations, lim

Expert Evaluation of LLM's Open-Ended Legal Reasoning on the Japanese Bar Exam Writing Task

arXiv:2604.23730v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance on legal benchmarks, including multiple-choice components of bar exams. However, their capaci

FedRef: Bayesian Fine-Tuning using a Reference Model to Mitigate Catastrophic Forgetting for Heterogeneous Federated Learning

arXiv:2506.23210v5 Announce Type: replace-cross Abstract: Federated learning (FL) enables collaborative model training across distributed clients while preserving data privacy. However, data and syste

Fraud Detection in Cryptocurrency Markets with Spatio-Temporal Graph Neural Networks

arXiv:2604.24590v1 Announce Type: new Abstract: Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market ma

From Equations to Algorithms and Data: Transforming Microwave Engineering and Education with Machine Learning

arXiv:2604.22792v1 Announce Type: cross Abstract: Conventional microwave engineering education relies heavily on analytical methods, canonical circuit topologies, and intuition-driven design, which ha

GeoCert: Certified Geometric AI for Reliable Forecasting

arXiv:2604.23474v1 Announce Type: new Abstract: Forecasting systems in science must be accurate, physically consistent, and certifiably reliable. Most existing models address prediction, constraint en

GIFT: Global stabilisation via Intrinsic Fine Tuning

arXiv:2604.23312v1 Announce Type: cross Abstract: Deep reinforcement learning policies achieve strong performance in complex continuous control environments with nonlinear contact forces. However, the

GLIER: Generative Legal Inference and Evidence Ranking for Legal Case Retrieval

arXiv:2604.23779v1 Announce Type: cross Abstract: The semantic gap between colloquial user queries and professional legal documents presents a fundamental challenge in Legal Case Retrieval (LCR). Exis

Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations

arXiv:2511.09749v2 Announce Type: replace Abstract: Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris f

HeiSD: Hybrid Speculative Decoding for Embodied Vision-Language-Action Models with Kinematic Awareness

arXiv:2603.17573v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) Models have become the mainstream solution for robot control, but suffer from slow inference speeds. Speculative

Human-1 by Josh Talks: A Full-Duplex Conversational Modeling Framework in Hindi using Real-World Conversations

arXiv:2604.23295v1 Announce Type: cross Abstract: Full-duplex spoken dialogue systems can model natural conversational behaviours such as interruptions, overlaps, and backchannels, yet such systems re

I’m going to build a bunch of deepagents examples (using deepagent deploy) over the next few days What examples would people want to see?

applicationsharrison-chase--x

Harrison Chase announced plans to create multiple deepagents examples using the deepagent deploy tool and solicited community input on which examples would be most valuable. This post likely seeks fee

Implicit Framing in Obstetric Counseling Notes: A Grounded LLM Pipeline on a VBAC-Eligible Cohort

arXiv:2604.23059v1 Announce Type: new Abstract: Clinical framing -- the linguistic manner in which clinical information is presented -- can influence patient understanding and decision-making, with im

Into the Omniverse: Manufacturing’s Simulation-First Era Has Arrived

Manufacturing is shifting from relying solely on real-world testing, as high-fidelity simulation now produces synthetic training data accurate enough for production-grade AI. NVIDIA Omniverse librarie

applicationsnvidia-blog

Introducing DigitalOcean AI-Native Cloud for Production AI Workloads

DigitalOcean announced a new AI-native cloud platform designed to support production artificial intelligence workloads with optimized infrastructure and services. The offering likely provides speciali

applicationsdigitalocean

IoT-Enhanced CNN-Based Labelled Crack Detection for Additive Manufacturing Image Annotation in Industry 4.0

arXiv:2604.22857v1 Announce Type: new Abstract: This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional ne

It also has a tendency to just take on obligations to you without noting them anywhere.

applicationsethan-mollick--x

This post likely discusses how AI systems, particularly language models, can implicitly agree to tasks or commitments during conversations without formally recording or tracking these obligations, whi

Latent-Hysteresis Graph ODEs: Modeling Coupled Topology-Feature Evolution via Continuous Phase Transitions

arXiv:2604.24293v1 Announce Type: cross Abstract: Graph neural ordinary differential equations (Graph ODEs) extend graph learning from discrete message-passing layers to continuous-time representation

LatentStealth: Unnoticeable and Efficient Adversarial Attacks on Expressive Human Pose and Shape Estimation

arXiv:2505.12009v2 Announce Type: replace Abstract: Expressive human pose and shape estimation (EHPS) plays a central role in digital human generation, particularly in live-streaming applications. How

Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design

arXiv:2511.21213v2 Announce Type: replace-cross Abstract: Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, ZT. To accelerate the dis

Learning to Decipher from Pixels -- A Case Study of Copiale

arXiv:2604.23683v1 Announce Type: new Abstract: Historical encrypted manuscripts require both paleographic interpretation of cipher symbols and cryptanalytic recovery of plaintext. Most existing compu

Learning to Rotate: Temporal and Semantic Rotary Encoding for Sequential Modeling

arXiv:2604.24717v1 Announce Type: new Abstract: Every Transformer architecture dedicates enormous capacity to learning rich representations in semantic embedding space -- yet the rotation manifold act

LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models

arXiv:2604.23809v1 Announce Type: new Abstract: Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity s

M^2-VLA: Boosting Vision-Language Models for Generalizable Manipulation via Layer Mixture and Meta-Skills

arXiv:2604.24182v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models predominantly rely on end-to-end fine-tuning. While effective, this paradigm compromises the inherent genera

Machine-Learning-Based Classification of Radio Frequency Building Loss

arXiv:2604.24143v1 Announce Type: new Abstract: Accurate modeling of outdoor-to-indoor (O2I) and indoor-to-indoor (I2I) signal loss is important for improving indoor wireless network performance in de

MetaEarth3D: Unlocking World-scale 3D Generation with Spatially Scalable Generative Modeling

arXiv:2604.22828v1 Announce Type: cross Abstract: Recent generative AI models have achieved remarkable breakthroughs in language and visual understanding. However, although these models can generate r

Microsoft is rolling out Copilot 365 to all of Accenture's roughly 743,000 employees, in the biggest enterprise deal for Copilot, following a 2023 pilot (Aditya Soni/Reuters)

Aditya Soni / Reuters: Microsoft is rolling out Copilot 365 to all of Accenture's roughly 743,000 employees, in the biggest enterprise deal for Copilot, following a 2023 pilot — Microsoft (MSFT.O) is

applicationstechmeme

Microsoft owns the entire Outlook interface! Another chatbot on the side that can only take limited actions to help you feels like such a wa…

applicationsethan-mollick--x

This post criticizes Microsoft's approach to integrating AI assistants into Outlook, expressing frustration that the AI chatbot has limited functionality and capabilities despite Microsoft's ownership

MINT: Multi-Vector Search Index Tuning

arXiv:2504.20018v2 Announce Type: replace-cross Abstract: Vector search plays a crucial role in many real-world applications. In addition to single-vector search, multi-vector search becomes important

ML-Guided Primal Heuristics for Mixed Binary Quadratic Programs

arXiv:2604.23053v1 Announce Type: new Abstract: Mixed Binary Quadratic Programs (MBQPs) are an important and complex set of problems in combinatorial optimization. As solving large-scale combinatorial

MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback

arXiv:2604.23107v1 Announce Type: cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding. Classical estimators such as inverse probability weighti

Modular Sensory Stream for Integrating Physical Feedback in Vision-Language-Action Models

arXiv:2604.23272v1 Announce Type: new Abstract: Humans understand and interact with the real world by relying on diverse physical feedback beyond visual perception. Motivated by this, recent approache

MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender

arXiv:2408.08686v4 Announce Type: replace-cross Abstract: Language Models (LMs) have been widely used in recommender systems to incorporate textual information of items into item IDs, leveraging their

One Size Fits None: Heuristic Collapse in LLM Investment Advice

arXiv:2604.23837v1 Announce Type: new Abstract: Large language models are increasingly deployed as advisors in high-stakes domains -- answering medical questions, interpreting legal documents, recomme

Open-Vocabulary Semantic Segmentation Network Integrating Object-Level Label and Scene-Level Semantic Features for Multimodal Remote Sensing Images

arXiv:2604.24125v1 Announce Type: new Abstract: Semantic segmentation of multi-modal remote sensing imagery plays a pivotal role in land use/land cover (LULC) mapping, environmental monitoring, and pr

OpenAI describes a report that it has missed internal goals as 'prime clickbait' and says its consumer and enterprise businesses are 'firing on all cylinders' (Seth Fiegerman/Bloomberg)

Seth Fiegerman / Bloomberg: OpenAI describes a report that it has missed internal goals as “prime clickbait” and says its consumer and enterprise businesses are “firing on all cylinders” — OpenAI push

applicationstechmeme