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data science

3,686 papers

#artificial intelligence Review Sep 2026

EnterpriseVal: Quantifying the Efficacy, Reliability and Value of Generative AI in the Enterprise

Frontier language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valuable tasks, yet most enterprise GenAI initiatives fail to show a measurable business effect and a large fraction of agentic projects are expected to be cancelled. We ar...

Abbas Ali, Muhammad Ajmal Siddiqui, Moona Zahid · 0 citations
#data science Jul 2026

Existence-Field Diffusion Model for Spatial Point Processes with Variable Cardinality

The existence-field diffusion model (EFDM), which associates each potential point with a continuous variable representing its degree of presence, is proposed, which uses Gaussian diffusion to jointly model point locations and cardinality through a simple continuous representation.

Xiaoyi Pan, C. Shelton, Rakshith Mahishi et al. · 0 citations
#artificial intelligence Review Open access Aug 2026

The Coordination Compression Trap: A Dynamic Model of AI-Enabled Productivity, Verification Debt, and Organisational Resilience in Global Knowledge Firms

Aims: This study develops a dynamic explanation for the gap between task-level artificial intelligence productivity and durable enterprise value. It introduces verification debt, the accumulated stock of unverified assumptions, weak review, concealed dependencies, deferred validation, and capability loss. Study Design:...

Kwan-Hong Tan · 4 citations
#data science Open access Oct 2026

Technology-Enhanced Problem-Based Learning for Developing Analytical Thinking and Science Process Skills in Biology Education

PBL is more effective for students with low BSPS, whereas Discovery Learning is more effective for students with high BSPS, highlighting that instructional effectiveness depends on students’ initial skill levels and support the development of adaptive learning strategies in science education.

Muhammad Sirih, Jahidin, Nurrijal et al. · 1 citation
#data science Jul 2026

Hopformer: Homogeneity-Pursuit Transformer for Time Series Forecasting

Hopformer (Homogeneity-Pursuit Transformer), a two-stage framework that addresses multiple time-series with high-dimensional covariates, and proves that SPA achieves a near-optimal bias-variance trade-off via an oracle inequality.

Wan Zhang, Qinjie Lin, Chan Lee et al. · 0 citations
#natural language process... Preprint Aug 2026

Optimal Watermark Localization in Mixed-Source Large Language Model Texts

Watermarking provides a principled way to authenticate text generated by large language models (LLMs). In practice, however, the final text may be mixed-source, with watermark evidence surviving at only a subset of token positions after rewriting, insertion, deletion, or paraphrasing. Although prior work has studied gl...

José H. Blanchet, T. Cai, Xiang Li et al. · 1 citation · ⚡1
#natural language process... Preprint Open access Sep 2026

Foundations of Stochastic Lexical Calculus: Semantic Descent and Random Dynamics on Probability Simplices

Large language models produce prompt-dependent probabilities over words, whereas scientific systems require uncertainty over meaningful states that can be updated as evidence arrives. We develop an observable framework for determining when language-derived probabilities support such a sequential state representation. T...

Matthew F Dixon · 0 citations
#machine learning Preprint Aug 2026

A Quantum/Classical Example Oracle Separation for Making Things Up

There are distributions that can be efficiently generated by a quantum learner with access to quantum samples, but not by a quantum learner with access to only classical samples, making progress to answering this question in the affirmative.

Kenny Chen · 0 citations

Fast Training of Mixture-of-Experts for Time Series Forecasting via Expert Loss Integration

We propose a novel Mixture-of-Experts framework, referred to as Expert Loss Integration MoE (EliMoE), for time series forecasting. EliMoE addresses the optimization problem arising from small gating weights by incorporating expert-specific losses, which provide each expert with a direct learning signal independent of t...

Btissame El Mahtout, F. Ziel · 0 citations
#machine learning Open access Feb 2026

Score-based diffusion models for severely ill-posed problems in diffuse optical tomography

It is shown that both the model-based approach and approximate diffusion-based sampling degrade significantly in the presence of limited-view geometry and real experimental data, whereas UCoS yields more accurate reconstructions.

Fabian Schneider, Meghdoot Mozumder, Konstantin Tamarov et al. · 1 citation
#machine learning Preprint Open access Sep 2026

On the Inherent Privacy Amplification of Missing Data

Privacy preservation is critical in many high-stakes domains such as medicine and finance, where sensitive data must be analyzed without compromising individual confidentiality. At the same time, these applications often involve datasets with inherent missing values due to non-response or data corruption for example. M...

Simon Roburin (LPSM), Rafa{\"e}l Pinot (LPSM), Erwan Scornet (LPSM) · 0 citations

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GPT-Lab Nov 3, 2026

Sovereignty Is the Option to Leave

Is your company’s AI sovereign? A practical guide for CIOs on AI vendor lock-in, EU Data Act switching, cloud sovereignty, and testing your exit plan before you need it. The post Sovereignty Is the Option to Leave appeared first on GPT-Lab.

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