applications

Conveyance: A Versatile Framework for Learning in Structured Class Spaces

arXiv:2605.28420v1 Announce Type: new Abstract: While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-ag

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Data Formulator 0.7: AI-powered data analytics for enterprise data

DGX agent

Data Formulator introduces AI-powered analytics for enterprise data workflows. Data teams can easily bring enterprise data into an AI-ready workspace where users can explore, analyze, and visualize da

applicationsmicrosoft-research

28 May 2026

Degradation-Aware Cooperative Multi-Modal GNSS-Denied Localization Leveraging LiDAR-Based Robot Detections

arXiv:2510.20480v2 Announce Type: replace Abstract: Accurate long-term localization using onboard sensors is crucial for robots operating in Global Navigation Satellite System (GNSS)-denied environmen

applicationsarxiv-cs-ro

Dell and H2O.ai target the token-cost problem with vertical AI models

As artificial intelligence adoption accelerates inside enterprises, the economics of generative AI are forcing a fundamental rethink. Runaway token costs, data sovereignty demands and a growing gap be

applicationssiliconangle

Do readers prefer AI-generated Italian short stories?

arXiv:2601.17363v2 Announce Type: replace-cross Abstract: This study investigates whether readers prefer AI-generated short stories in Italian over one written by a renowned Italian author. In a blind

EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction

arXiv:2605.28101v1 Announce Type: cross Abstract: Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive s

Every LLM API call depends on the inference engine underneath it. Tokenization, scheduling, prefill, decode, KV cache, batching, and streami…

applicationstogether-ai--x

Every LLM API call depends on the inference engine underneath it. Tokenization, scheduling, prefill, decode, KV cache, batching, and streaming determine whether the experience is fast, scalable, and p

Everyone holds up Banks as seeing the future of AI, but come on...

Ethan Mollick critiques the widespread praise for Joseph E. Banks's predictions about AI's future, suggesting that the expectations placed on his foresight may be overstated. The post likely argues fo

FinBoardBench: Benchmarking Dynamic Wealth Management and Strategic Financial Reasoning of LLMs via Board Game Simulations

arXiv:2605.27896v1 Announce Type: new Abstract: Recently, large language models (LLMs) have achieved superior performance in static financial reasoning and simple dynamic trading tasks. However, exist

applicationsarxiv-cs-cl

Fine-Tuned LLM as a Complementary Predictor Improving Ads System

arXiv:2605.27856v1 Announce Type: cross Abstract: Recommendation systems power engagement and monetization across feeds, ads, and short-video platforms, but translating the latest advances in Large La

FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation

arXiv:2605.21832v2 Announce Type: replace Abstract: Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates coll

France's market regulator warns crypto companies they could face blacklisting and lawsuits if they don't have MiCA licenses by the EU's June 30 deadline (Elizabeth Howcroft/Reuters)

Elizabeth Howcroft / Reuters: France's market regulator warns crypto companies they could face blacklisting and lawsuits if they don't have MiCA licenses by the EU's June 30 deadline — France's top ma

applicationstechmeme

From Causal Discovery to Dynamic Causal Inference in Neural Time Series

arXiv:2603.20980v2 Announce Type: replace-cross Abstract: Time-varying causal models provide a powerful framework for studying dynamic scientific systems, yet most existing approaches assume that the

GEM: Generative Supervision Helps Embodied Intelligence

arXiv:2605.28548v1 Announce Type: new Abstract: Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Acti

GraD-IBD: Graph Representation Learning from Diagnosis Trajectories for Early Detection of Inflammatory Bowel Disease

arXiv:2605.27799v1 Announce Type: new Abstract: International Classification of Diseases (ICD) is a globally recognized coding system that records diagnostic events during each patient encounter, prov

GraphSteal: Structural Knowledge Stealing from Graph RAG via Traversal Reconstruction

arXiv:2605.28645v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances LLMs by grounding generation in query-relevant external evidence. Beyond unstructured text corpora, Grap

applicationsarxiv-cs-cl

How enterprise leaders are scaling AI agents across their organization

Enterprise leaders are implementing AI agents across their organizations through strategies that address deployment, governance, and integration challenges. The article from Databricks likely covers b

applicationsdatabricks

I have spoken to lots of companies that blew through their token budget for the year in months, but a half a billion dollars on internal emp…

Ethan Mollick discusses companies that rapidly depleted their annual token budgets within months, with some spending hundreds of millions of dollars on internal employee use of large language models.

IGADA-IoT: IoT Sensor Energy Optimization in Wireless Sensor Networks Driven by Automatic Data Augmentation

arXiv:2605.27397v1 Announce Type: new Abstract: In wireless sensor networks (WSNs), data augmentation is a novel method to improve sampling-frequency decision performance, thereby enabling energy opti

It generated the images from GPT-Imagegen-1.5 via API, it did all the prompting and stuff itself.

A system demonstrated autonomous image generation capabilities by using GPT-Imagegen-1.5's API to create images without human intervention, independently formulating prompts and managing the entire ge

@jerryjliu0 This is actually impressive. Useful update for real-world document processing.

Jerry Liu highlights an impressive update relevant to real-world document processing applications. The post likely discusses improvements or new capabilities in document handling, parsing, or processi

applicationsjerry-liu--x

Learning after COVID-19 and the ICT career aspirations: Are students entering the AI era with weaker skills?

arXiv:2605.27391v1 Announce Type: cross Abstract: This paper examines whether students are entering the generative AI era with sufficiently strong educational foundations, focusing on the relationship

Learning to target with network interference

arXiv:2605.27794v1 Announce Type: cross Abstract: This paper studies adaptive targeting under network interference in a bandit setting, where treatments applied to one individual may affect others thr

Lem & Douglas Adams got AI right Presciently Golem XIV (from 1981) has an illustration of the jagged frontier as explained by an AI, Golem (…

Lem & Douglas Adams got AI right Presciently Golem XIV (from 1981) has an illustration of the jagged frontier as explained by an AI, Golem (GENERAL OPERATOR, LONG-RANGE, ETHICALLY STABILIZED, MULTIMOD

LLM-assisted sentiment analysis for integrated computational and qualitative mixed methods education research: A case study of students' written reflection assignments

arXiv:2605.27403v1 Announce Type: cross Abstract: Written reflection assignments give students valuable opportunities for critical self-assessment, meaning making, and learning processing. Additionall

LLMs actually produce bullshit for many reasons, and would continue to do so (though less) even they weren’t trained on bullshit. legal cita…

applicationsgary-marcus--x

LLMs actually produce bullshit for many reasons, and would continue to do so (though less) even they weren’t trained on bullshit. legal citation hallucinations are a nice example where the underlying

Measuring Massive Multitask Chinese Understanding

arXiv:2304.12986v3 Announce Type: replace-cross Abstract: The development of large-scale Chinese language models is flourishing, yet there is a lack of corresponding capability assessments. Therefore,

models being conscious would be harmful for humanity. it would encroach on our status and dignity. it would limit the type of things we can …

models being conscious would be harmful for humanity. it would encroach on our status and dignity. it would limit the type of things we can do with them and use them for. it would vastly accelerate hu

Most of our problems are caused by modernity, because modernity already solved most of the ones that came before.

Most of our problems are caused by modernity, because modernity already solved most of the ones that came before. Decent chance that, not even taking into account GenAI, this will be viewed as a decad

MUFG aims to become AI-native with OpenAI

Mitsubishi UFJ Financial Group (MUFG), Japan's largest financial institution, is partnering with OpenAI to integrate advanced AI capabilities across its operations and become an 'AI-native' organizati

applicationsopenai

Multi-Teacher Knowledge Distillation via Teacher-Informed Mixture Priors

arXiv:2605.27967v1 Announce Type: cross Abstract: Knowledge distillation is a powerful method for model compression, enabling the efficient deployment of complex deep learning models (teachers), inclu

ObjFiller3D: Scaling 3D Object Inpainting to Dense Multi-View Consistency

arXiv:2508.18271v2 Announce Type: replace Abstract: 3D object inpainting is commonly achieved via multi-view 2D image completion, yet independently inpainted views often suffer from cross-view inconsi

Online Irregular Multivariate Time Series Forecasting via Uncertainty-Driven Dual-Expert Calibration

arXiv:2605.28603v1 Announce Type: cross Abstract: Irregular multivariate time series forecasting is critical in many real-world applications, where time series are irregularly sampled and exhibit dyna

OphIn-500K: Curating Web-Scale Visual Instructions for Scaling Ophthalmic Multimodal Large Language Models

arXiv:2605.27916v1 Announce Type: cross Abstract: The advancement of general medical Multimodal Large Language Models (MLLMs) has shown great potential for building conversational assistants to suppor

applicationsarxiv-cs-cl

Performance and Explainability Requirements of Evolutionary Algorithms in Real-World Physics-Informed Optimization

arXiv:2605.28164v1 Announce Type: cross Abstract: Evolutionary computation offers a variety of tools to solve complex real-world optimization problems. However, research often focuses on smaller, simp

Principled Algorithms for Optimizing Generalized Metrics in Multi-Label Learning

arXiv:2605.28767v1 Announce Type: new Abstract: Many real-world classification tasks require predicting multiple labels per instance, necessitating the optimization of complex evaluation metrics such

QuITE: Query-Based Irregular Time Series Embedding

arXiv:2605.28166v1 Announce Type: cross Abstract: Irregular Multivariate Time Series (IMTS) are common in practice, yet their irregular sampling complicates effective modeling. Existing approaches typ

REC-CBM: Rubric-Aware Error-Correction Concept Bottleneck Models for Trustworthy Open-Ended Grading

arXiv:2605.27402v1 Announce Type: cross Abstract: Open-ended grading is central to equitable and personalized education, yet manual grading remains time-consuming and costly, underscoring the need for

Representation-Conditioned Diffusion Models for Guided Training Data Generation

arXiv:2605.27495v1 Announce Type: new Abstract: Data availability remains a critical bottleneck in many deep learning applications. Large-scale datasets are often expensive to collect, curate and anno

ResearchLoop: An Evidence-Gated Control Plane for AI-Assisted Research

arXiv:2605.28282v1 Announce Type: new Abstract: AI-assisted research compresses ideation, implementation, evaluation, and manuscript writing into a single interactive loop. This compression is useful,

Rethinking Video-Language Model from the Language Input Perspective

arXiv:2605.27920v1 Announce Type: new Abstract: Driven by the wave of large language models, Video-Language Models (VLMs) have become a significant yet challenging technology to bridge the gap between

Revisiting Change Detection Methods for their Application to Serac Fall Time-Lapse Monitoring

arXiv:2605.28100v1 Announce Type: cross Abstract: In an era where climate change aggravates environmental uncertainties, the identification and detection of event precursors are becoming crucial to mi

Rising AI spend turns FinOps into a boardroom strategist

Artificial intelligence has turned technology spending into a strategic boardroom priority across the entire enterprise. Companies are now using FinOps data to decide where capital goes and the value

applicationssiliconangle

Show, Don't TELL: Explainable AI-Generated Text Detection

arXiv:2605.27921v1 Announce Type: new Abstract: Research on AI-generated text detection has presented a number of approaches to discern human from AI prose, some of which achieving high in-distributio

Simultaneous Contact Selection and Planning for Contact-Rich Manipulation with Cascaded Optimization

arXiv:2605.27972v1 Announce Type: new Abstract: We propose an optimization-based framework for robust contact-rich manipulation. Recent contact-implicit methods enable online hybrid planning across co

applicationsarxiv-cs-ro

SMILE-Next: Teaching Large Language Models to Detect, Classify, and Reason about Laughter

arXiv:2605.28084v1 Announce Type: cross Abstract: Laughter is a complex social signal that conveys communicative intent beyond amusement. While prior work has focused on isolated laughter analysis tas

Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models

arXiv:2605.28711v1 Announce Type: new Abstract: The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between dist

Starburst bets on semantic context to solve enterprise AI trust problem

Starburst Data Inc. today is expanding its push into enterprise artificial intelligence with the introduction of a platform aimed at allowing organizations to run AI workloads directly on distributed

applicationssiliconangle