Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation | Paper Citation Record

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This paper cites Lopes, Pedro Guimar ˜aes, Tiago F.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Lopes, Pedro Guimar ˜aes, Tiago F

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This paper cites Beliatis, and Mirko Presser.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Beliatis, and Mirko Presser

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This paper cites Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review

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This paper cites A Survey of Dataspace Connector Implementations.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation A Survey of Dataspace Connector Implementations

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Gamiz, C

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Verification methods for international AI agreements

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Brendan McMa- han, Ilya Mironov, Kunal Talwar, and Li Zhang

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Consistency Models for Scalable and Fast Simulation-Based Inference

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Zephyr: Direct Distillation of LM Alignment

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation LIMA: Less Is More for Alignment

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation CrypTen: Secure Multi-Party Computation Meets Machine Learning

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Verifiable Privacy-Preserving Computing

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation BloombergGPT: A Large Language Model for Finance

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Abushark, and Ahmed S

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Adding Conditional Control to Text-to-Image Diffusion Models

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation A Survey of Large Language Models

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Authentication and authorization in Data Spaces: A relationship-based access control approach for policy specification based on ODRL

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation A Service Architecture for Dataspaces

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Efficient and Scalable Self-Healing Databases Using Meta-Learning and Dependency-Driven Recovery

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Osorio-Marulanda, Gorka Epelde, Mikel Hernandez, Imanol Isasa, Nicolas Moreno Reyes, and Andoni Beristain Iraola

Reference 47

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Beyond Explainability: The Case for AI Validation

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels

Reference 51

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Encrypted Vector Similarity Computations Using Partially Homomorphic Encryption: Applications and Performance Analysis

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Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation A Somewhat Homomorphic Encryption Scheme based on Multivariate Polynomial Evaluation

Reference 54

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Observation 83d83faa-a17c-4084-8b2d-bbee509b93f1 · outbound

This paper cites Neurosymbolic AI: The 3rd Wave.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Neurosymbolic AI: The 3rd Wave

Reference 55

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Observation e5f040fe-77c3-415d-8726-27da12f91cea · outbound

This paper cites Murray, Abraham Stefanidis, William Y.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Murray, Abraham Stefanidis, William Y

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:38.290244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Tamilselvi, V.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Tamilselvi, V

Reference 57

Resolution: verified exact; raw_fallback, observed 2026-08-06T13:54:38.659585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c9f73c14-4e70-4216-bc5c-4a65cd1cd132 · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 58

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:54:38.582245Z

Source-reported events for the cited work

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Observation 4f39a83f-19c6-415f-8d8d-b97224eeb31f · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:38.299285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d87bdb98-c146-4318-b695-b71da595018b · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 60

Resolution: verified exact; doi, observed 2026-08-06T13:54:38.354571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9bcc1700-e787-4d7a-aed1-028199b5c175 · outbound

This paper cites A Comprehensive Survey on Federated Learning: Concept and Applications.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation A Comprehensive Survey on Federated Learning: Concept and Applications

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-08-06T13:54:38.484675Z

Source-reported events for the cited work

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Observation 09d9021e-42b6-4575-a7eb-8b70337a44f9 · outbound

This paper cites Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T13:54:38.308630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b05f009-f17d-49c9-a6b7-9e40011ba4d9 · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 63

Resolution: verified exact; doi, observed 2026-08-06T13:54:38.344056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1612e68a-ee2c-4377-a025-ffb21e075be7 · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 277

Resolution: unresolved; raw_fallback, observed 2026-08-06T13:54:40.243982Z

Source-reported events for the cited work

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Observation 1508ee23-1e0c-4de4-b781-821928f05976 · outbound

This paper cites 3389/feduc.2023.1183162.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation 3389/feduc.2023.1183162

Reference 2023

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:54:39.322059Z

Source-reported events for the cited work

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Observation abe7ff51-e36e-40a3-a94a-02ffdc810790 · outbound

This paper cites 3389/fdata.2024.1497535.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation 3389/fdata.2024.1497535

Reference 2024

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T13:54:39.068622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5a3fa90-15b5-449b-a1df-b107612cccc8 · outbound

This paper cites an unresolved cited work.

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation Unresolved cited work

Reference 3612

Resolution: verified exact; doi, observed 2026-08-06T13:54:38.409286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers