applications

Token Is All You Price

arXiv:2510.09859v4 Announce Type: replace-cross Abstract: A seller of a dynamic information service under an information-throughput constraint screens buyers who privately differ in urgency. We charac

Toward Real-World Adoption of Portrait Relighting via Hybrid Domain Knowledge Fusion

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arXiv:2604.23094v1 Announce Type: new Abstract: The real-world adoption of portrait relighting is hindered by dataset domain gaps, camera sensitivity, and computational costs. We address these challen

applicationsarxiv-cs-cv

28 Apr 2026

Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding

arXiv:2603.11831v2 Announce Type: replace Abstract: The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate

Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption

arXiv:2604.23245v1 Announce Type: cross Abstract: The use of Machine Learning (ML) for data-driven decision-making often relies on access to sensitive datasets, which introduces privacy challenges. Tr

Unconstrained Multi-view Human Pose Estimation with Algebraic Priors

arXiv:2604.24312v1 Announce Type: cross Abstract: Recovering 3D human pose from multi-view imagery typically relies on precise camera calibration, which is often unavailable in real-world scenarios, t

Unleashing the Agility of Wheeled-Legged Robots for High-Dynamic Reflexive Obstacle Evasion

arXiv:2604.23761v1 Announce Type: new Abstract: Wheeled-legged robots combine the energy efficiency of wheeled locomotion with the terrain adaptability of legged systems, making them promising platfor

Variational Grey-Box Dynamics Matching

arXiv:2602.17477v3 Announce Type: replace Abstract: Deep generative models such as flow matching and diffusion models have shown great potential in learning complex distributions and dynamical systems

VeriLLMed: Interactive Visual Debugging of Medical Large Language Models with Knowledge Graphs

arXiv:2604.23356v1 Announce Type: new Abstract: Large language models (LLMs) show promise in medical diagnosis, but real-world deployment remains challenging due to high-stakes clinical decisions and

We agree. The real leading indicators are clear: breakout Codex growth ✅, enterprise offerings on every cloud ✅, the only consumer app that …

applicationsdylan-patel--x

We agree. The real leading indicators are clear: breakout Codex growth ✅, enterprise offerings on every cloud ✅, the only consumer app that matters ✅, a compute strategy built to accelerate ✅, and the

What Understanding Means in AI-Laden Astronomy

arXiv:2601.10038v2 Announce Type: replace-cross Abstract: Artificial intelligence is rapidly transforming astronomical research, yet the scientific community has largely treated this transformation as

When Silence Matters: The Impact of Irrelevant Audio on Text Reasoning in Large Audio-Language Models

arXiv:2510.00626v3 Announce Type: replace-cross Abstract: Large audio-language models (LALMs) unify speech and text processing, but their robustness in noisy real-world settings remains underexplored.

'Yeah, my OpenClaw runs entirely on talkie-1930-13b-base, I connect to it only through telegram. No, not that telegram.'

applicationsethan-mollick--x

This post describes a personal AI setup called 'OpenClaw' that runs on the talkie-1930-13b-base model and is accessed via a custom Telegram interface, with the author humorously clarifying this is not

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg

Your search is failing because it's looking at words, not meaning. 🛑 Will Templeton, CTO and co-founder at Allspice, explains the 'Synonym …

Your search is failing because it's looking at words, not meaning. 🛑 Will Templeton, CTO and co-founder at Allspice, explains the 'Synonym Trap': ❌ User says 'Boston Butt' ❌ DB says 'Pork Shoulder' ❌

applicationspinecone--x

A Brain-Inspired Deep Separation Network for Single Channel Raman Spectra Unmixing

arXiv:2604.22324v1 Announce Type: new Abstract: Raman spectra obtained in real world applications are often a noisy combination of several spectra of various substances in a tested sample. Unmixing su

A Nationwide Japanese Medical Claims Foundation Model: Balancing Model Scaling and Task-Specific Computational Efficiency

arXiv:2604.22348v1 Announce Type: new Abstract: Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising app

Algorithmic Compliance and Regulatory Loss in Digital Assets

arXiv:2603.04328v2 Announce Type: replace Abstract: We study the deployment performance of machine learning based enforcement systems used in cryptocurrency anti money laundering (AML). Using forward

An Interdisciplinary and Cross-Task Review on Missing Data Imputation

arXiv:2511.01196v3 Announce Type: replace-cross Abstract: Missing data is a fundamental challenge in data science, significantly hindering analysis and decision-making across a wide range of disciplin

Analysis: as of late 2025, 79 of 500 tracked software companies including HubSpot, Adobe, and Salesforce adopted usage-based AI fees, more than doubling on 2024 (The Information)

The Information: Analysis: as of late 2025, 79 of 500 tracked software companies including HubSpot, Adobe, and Salesforce adopted usage-based AI fees, more than doubling on 2024 — Dozens of enterprise

applicationstechmeme

Analysis of 100 actively traded software company loans since January 20 finds sector-wide price pressure as investors seek defensive moats against AI disruption (Sam Goldfarb/Wall Street Journal)

Sam Goldfarb / Wall Street Journal: Analysis of 100 actively traded software company loans since January 20 finds sector-wide price pressure as investors seek defensive moats against AI disruption — M

applicationstechmeme

Build and deploy an automatic sync solution for Amazon Bedrock Knowledge Bases

In this post, we explore an automated solution that detects S3 events and triggers ingestion jobs while respecting service quotas and providing comprehensive monitoring. This serverless solution uses

applicationsaws-ml-blog

China is blocking the Manus acquisition by Meta. A few things stand out: - China has historically been more opaque and less public in restri…

applicationsyohei-nakajima--x

China is blocking the Manus acquisition by Meta. A few things stand out: - China has historically been more opaque and less public in restricting foreign acquisitions of Chinese tech assets, while the

Choco automates food distribution with AI agents

Choco uses AI agents powered by OpenAI technology to automate and optimize food distribution processes, improving efficiency across supply chain operations. The system likely leverages machine learnin

applicationsopenai

Cloud cost optimization becomes an enterprise mandate as AI bills spiral

As AI rapidly rewrites enterprise economics, cloud cost optimization has become essential for preventing budgets from collapsing under AI workloads, enabling organizations to slash expenses and redire

applicationssiliconangle

CodeGraphVLP: Code-as-Planner Meets Semantic-Graph State for Non-Markovian Vision-Language-Action Models

arXiv:2604.22238v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume

Conditional anomaly detection using soft harmonic functions: An application to clinical alerting

arXiv:2604.21956v1 Announce Type: new Abstract: Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detect

Contrastive Semantic Projection: Faithful Neuron Labeling with Contrastive Examples

arXiv:2604.22477v1 Announce Type: new Abstract: Neuron labeling assigns textual descriptions to internal units of deep networks. Existing approaches typically rely on highly activating examples, often

Couldn't resist capping that off with my all-time favorite quote from Matt Levine

applicationssimon-willison--x

This post references a quote from Matt Levine, a financial columnist known for his sharp commentary on finance and markets, shared by Simon Willison on X (formerly Twitter). Without access to the spec

Dynamically Acquiring Text Content to Enable the Classification of Lesser-known Entities for Real-world Tasks

arXiv:2604.22325v1 Announce Type: new Abstract: Existing Natural Language Processing (NLP) resources often lack the task-specific information required for real-world problems and provide limited cover

Elon Musk and Sam Altman are going to court over OpenAI’s future

applicationsmit-tech-review

After a yearslong legal feud, Elon Musk and OpenAI CEO Sam Altman are heading to trial this week in Northern California in a case that could have sweeping consequences. Ahead of OpenAI’s highly antici

Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Ever…

applicationsethan-mollick--x

Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Everything else (job impact, potential risks, etc.) is downstrea

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records

arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc

GazeVLA: Learning Human Intention for Robotic Manipulation

arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra

Here's a slightly more involved view of the history of sociological theories of professions, explained with charcuterie, as one does.

applicationsethan-mollick--x

This post presents an overview of sociological theories regarding professional work and expertise, using charcuterie as an extended metaphor or analogy to explain complex concepts. The humorous approa

HFX: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling

arXiv:2508.15919v3 Announce Type: replace-cross Abstract: Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing c

HGQ-LUT: Fast LUT-Aware Training and Efficient Architectures for DNN Inference

arXiv:2604.22293v1 Announce Type: cross Abstract: Lookup-table (LUT) based neural networks can deliver ultra-low latency and excellent hardware efficiency on FPGAs by mapping arithmetic operations dir

ICPR 2026 Competition on Low-Resolution License Plate Recognition

arXiv:2604.22506v1 Announce Type: new Abstract: Low-Resolution License Plate Recognition (LRLPR) remains a challenging problem in real-world surveillance scenarios, where long capture distances, compr

@idarbek Having your backups on the same vendor as your production database puts you at risk of your vendor banning your account for some re…

applicationssimon-willison--x

@idarbek Having your backups on the same vendor as your production database puts you at risk of your vendor banning your account for some reason (like billing messups, or detected CSAM in user-uploade

Information-Theoretic Geometry Optimization and Physics-Aware Learning for Calibration-Free Magnetic Localization

arXiv:2604.22526v1 Announce Type: new Abstract: Wireless localization of permanent magnets enables occlusion-free guidance for medical interventions, yet its practical accuracy is fundamentally limite

Knowledge-driven Augmentation and Retrieval for Integrative Temporal Adaptation

arXiv:2604.22098v1 Announce Type: new Abstract: Time introduces fundamental challenges in model development and deployment: models are usually trained on historical data while deployed on future data

LeHome: A Simulation Environment for Deformable Object Manipulation in Household Scenarios

arXiv:2604.22363v1 Announce Type: cross Abstract: Household environments present one of the most common, impactful yet challenging application domains for robotics. Within household scenarios, manipul

Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand

arXiv:2510.12328v5 Announce Type: replace Abstract: Accurate rainfall forecasting, particularly for extreme events, remains a significant challenge in climatology and the Earth system. This paper pres

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching

arXiv:2604.22061v1 Announce Type: cross Abstract: Patient-trial matching requires reasoning over long, heterogeneous electronic health records (EHRs) and complex eligibility criteria, posing significa

Manifold Learning for Personalized and Label-Free Detection of Cardiac Arrhythmias

arXiv:2506.16494v3 Announce Type: replace Abstract: Electrocardiograms (ECGs) provide non-invasive measurements of heart activity and are established tools for detecting cardiac arrhythmias. Although

Mochi: Aligning Pre-training and Inference for Efficient Graph Foundation Models via Meta-Learning

arXiv:2604.22031v1 Announce Type: cross Abstract: We propose Mochi, a Graph Foundation Model that addresses task unification and training efficiency by adopting a meta-learning based training framewor

Nuclear Diffusion Models for Low-Rank Background Suppression in Videos

arXiv:2509.20886v2 Announce Type: replace Abstract: Video sequences often contain structured noise and background artifacts that obscure dynamic content, posing challenges for accurate analysis and re

Online Distributional Regression

arXiv:2407.08750v4 Announce Type: replace-cross Abstract: Large-scale streaming data are common in modern machine learning applications and have led to the development of online learning algorithms. M

OpenAI available at FedRAMP Moderate

OpenAI has achieved FedRAMP Moderate authorization, enabling U.S. federal agencies to use OpenAI's services while meeting federal security and compliance requirements. This certification demonstrates

applicationsopenai