Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T19:39:07.667815Z
Paper Citation Record · LEDGER
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems
As of 20 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.04374.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
23 of 23 outbound references displayed
- verified exact3
- verified fuzzy0
- unresolved19
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 7f19847d-1877-4ad0-ba11-54d250ab2992 · outbound
This paper cites Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2a42a667-21cc-41f2-8ec2-06acd44192d9 · outbound
This paper cites Peeking Inside the Black -Box: A Survey on Explainable Artificial Intelligence (XAI).
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Peeking Inside the Black -Box: A Survey on Explainable Artificial Intelligence (XAI)
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b765e6c8-e7ab-44f1-bc85-a3ba8d6cb1e1 · outbound
This paper cites and Aha, D.W.
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 733018a6-f484-4b57-b70e-4b4ad2626179 · outbound
This paper cites an unresolved cited work.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Unresolved cited work
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19d39b5d-57f9-49e6-9099-2b3d040ce9f4 · outbound
This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48e395d9-31ea-4650-898b-74d6d20da61e · outbound
This paper cites Explaining Explanations: An Overview of Interpretability of Machine Learning,.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Explaining Explanations: An Overview of Interpretability of Machine Learning,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d3538433-e0ef-4c9d-99d0-c3f014f1f686 · outbound
This paper cites Towards A Rigorous Science of Interpretable Machine Learning.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Towards A Rigorous Science of Interpretable Machine Learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec294aed-21da-41fb-bfd4-1a938ceb2f72 · outbound
This paper cites Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, 2nd ed.; Leanpub: Victoria, BC, Canada, 2022.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, 2nd ed.; Leanpub: Victoria, BC, Canada, 2022
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 05e31d62-a2f6-40db-90a3-41304dafed77 · outbound
This paper cites Why Should I Trust You?.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Why Should I Trust You?
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e70f265a-0549-48fc-b11e-8d7d5fa7a86e · outbound
This paper cites A Unified Approach to Interpreting Model Predictions.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems A Unified Approach to Interpreting Model Predictions
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5364e6f6-b0e8-47ea-97cf-339a0160b9df · outbound
This paper cites From Local Explanations to Global Understanding with Explainable AI for Trees.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems From Local Explanations to Global Understanding with Explainable AI for Trees
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c6320e4-4dbf-4fe0-8caf-db4c992d984a · outbound
This paper cites Anchors: High -Precision Model-Agnostic Explanations.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Anchors: High -Precision Model-Agnostic Explanations
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ed66baf-8e52-4410-943f-4106329af189 · outbound
This paper cites & sayres, R.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems & sayres, R
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3f28b3c9-c739-4ef3-8ccb-a878e028778a · outbound
This paper cites On the Robustness of Interpretability Methods.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems On the Robustness of Interpretability Methods
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e06e576a-ec82-466d-bd4f-3d5c59282af4 · outbound
This paper cites On the (In)fidelity and Sensitivity of Explanations.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems On the (In)fidelity and Sensitivity of Explanations
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dd038e7-963e-4016-87a5-75284c784817 · outbound
This paper cites Look at the Variance! Efficient Black-box Explanations with Sobol -based Sensitivity Analysis.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Look at the Variance! Efficient Black-box Explanations with Sobol -based Sensitivity Analysis
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb8c0f6b-8c46-404a-bda1-4b7f52060cef · outbound
This paper cites Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
Reference 17
- Resolution
- malformed identifier
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ea0080b-00a0-4b00-bb46-71661f674d9a · outbound
This paper cites & Zhou, D.
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7e72930-2b7d-4bae-be98-2c829252ee05 · outbound
This paper cites Training language models to follow instructions with human feedback.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Training language models to follow instructions with human feedback
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 865b80b4-d7cd-469d-bafc-3aabe699fdb5 · outbound
This paper cites Fault Detection and Classification in Power Systems Using Machine Learning Algorithms.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Fault Detection and Classification in Power Systems Using Machine Learning Algorithms
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-07-11T19:48:13.437272Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation cf330ee3-1b89-4eed-a870-f17a492601f5 · outbound
This paper cites an unresolved cited work.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Unresolved cited work
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T19:39:07.667815Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce6d47da-194f-4de7-829e-5bdfb02f1f11 · outbound
This paper cites Explainable approaches for forecasting building electricity consumption.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems Explainable approaches for forecasting building electricity consumption
Reference 22
- Resolution
- verified exact
- doi, observed 2026-07-11T19:48:13.433988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation b13f1820-fb76-46f6-9399-f2fb81be72de · outbound
This paper cites K., Wu, M., Chen, J., & Zhang, L.
An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems K., Wu, M., Chen, J., & Zhang, L
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-11T19:48:13.428449Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Pith citing papers
No inbound Pith citation observations are available.