{"as_of":"2026-08-03T21:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6fe2ce8de171ce4472959a1778ec4c08fe6b53197b00ba3d8763782138158de3","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T19:39:07.667815Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-03T06:30:56.289259+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.04374/citation-record","integrity":"/paper/2607.04374/integrity","json":"/paper/2607.04374/citation-record.json","paper":"/paper/2607.04374"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:9482081912faeb0c770ef28032342e9b66e2068a7d9d33cb9fadc06a5f6f8b20","observation_id":"7f19847d-1877-4ad0-ba11-54d250ab2992","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Peeking Inside the Black -Box: A Survey on Explainable Artificial Intelligence (XAI)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:b0c2de36c921f0e971cbc5f67754b1c213ddd047646efb2fda7ab2fcfb2e553f","observation_id":"2a42a667-21cc-41f2-8ec2-06acd44192d9","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"and Aha, D.W","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:63519101ae0585eee52a685976043d1b2dc9750000fd3b0aa7ee1f4c59a88a4d","observation_id":"b765e6c8-e7ab-44f1-bc85-a3ba8d6cb1e1","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:bb67c383918d0e2e65d3c00f689c570ca91d9260691014bf8cafcb479b3c5ab9","observation_id":"733018a6-f484-4b57-b70e-4b4ad2626179","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:df4d18350b34bf1e7b1777a825d1e307c6f0a8cf39ad71e787b8d3b2f6b7d8ae","observation_id":"19d39b5d-57f9-49e6-9099-2b3d040ce9f4","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Explaining Explanations: An Overview of Interpretability of Machine Learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:43f02f068f74aac8382f7ddfc00643872166074c444f9c5b1e5b29e80df155c2","observation_id":"48e395d9-31ea-4650-898b-74d6d20da61e","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.08608","last_updated":"2017-03-02T19:32:10Z","snapshot_observed_at":"2026-07-30T22:42:20.127902Z","submitted_at":"2017-02-28T02:19:20Z","title":"Towards A Rigorous Science of Interpretable Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.08608","snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Towards a Rigorous Science of Interpretable Machine Learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"cited_paper":"/paper/1702.08608","citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:c34b12047b21a21afe96f3c199424e810f3d08574e1670c3c78c04bae8ee81e9","observation_id":"d3538433-e0ef-4c9d-99d0-c3f014f1f686","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, 2nd ed.; Leanpub: Victoria, BC, Canada, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:2c96adedc4b82229ce4e4b039e8199e6bb14037787b3f091e1df1f025aa17095","observation_id":"ec294aed-21da-41fb-bfd4-1a938ceb2f72","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Why Should I Trust You?","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:b81fdd61a466ebdd02abdc2cff517912575b4f8b3308dc301b24e62f2e88012a","observation_id":"05e31d62-a2f6-40db-90a3-41304dafed77","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"A Unified Approach to Interpreting Model Predictions","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:802c8799a9178c617166e74e058784baef8389b11473a1e4fd641e1f7b6d2b83","observation_id":"e70f265a-0549-48fc-b11e-8d7d5fa7a86e","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"From Local Explanations to Global Understanding with Explainable AI for Trees","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:97c6c5e2ab186038a41a0a3a827cd379e79de4fc5edbda3e75f5ca3b7cc4462a","observation_id":"5364e6f6-b0e8-47ea-97cf-339a0160b9df","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Anchors: High -Precision Model-Agnostic Explanations","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:52c7eb301f749b9bf748b5608322855cf6f35ed16f2830ed64babdf4ae4baa1e","observation_id":"6c6320e4-4dbf-4fe0-8caf-db4c992d984a","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"&amp; sayres, R","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:0c3e41e236acd1fa7317d6783bfbc0d2f03319a966aab2462f4ced0bd3f19e23","observation_id":"4ed66baf-8e52-4410-943f-4106329af189","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.08049","last_updated":"2018-06-21T02:33:44Z","snapshot_observed_at":"2026-07-06T06:46:01.245927Z","submitted_at":"2018-06-21T02:33:44Z","title":"On the Robustness of Interpretability Methods","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.08049","snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"On the Robustness of Interpretability Methods","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"cited_paper":"/paper/1806.08049","citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:6312cca05bb997199596a47e8c06c65ffea413f5ec0c66830fabd7450e011a6e","observation_id":"3f28b3c9-c739-4ef3-8ccb-a878e028778a","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"On the (In)fidelity and Sensitivity of Explanations","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:83ec94fe0d82cc0808f9f3835b46be5a735fc19dd58c9e611c72042e7cb6ce0c","observation_id":"e06e576a-ec82-466d-bd4f-3d5c59282af4","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Look at the Variance! Efficient Black-box Explanations with Sobol -based Sensitivity Analysis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:e2848d3c5da7f7e1c7d10a51fdc90522cc127879af7c44ee5bebeb2a54c7781d","observation_id":"0dd038e7-963e-4016-87a5-75284c784817","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:d9115828d3d562213bb8556a7b8c44b6eec8f083b0a575245a46ca58e35919de","observation_id":"bb8c0f6b-8c46-404a-bda1-4b7f52060cef","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"& Zhou, D","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:59d976bb3f260ca738f2a3a2ce37be7b3891abd1be8e76a51fc73f081f12df20","observation_id":"7ea0080b-00a0-4b00-bb46-71661f674d9a","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":"Training language models to follow instructions with human feedback","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:1ed38a3c1c32fae6495fafa106959240dc1f29774df44b2cd46f6078993f28f6","observation_id":"c7e72930-2b7d-4bae-be98-2c829252ee05","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2021.106975","doi":"10.1016/j.ijepes.2021.106975","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T00:15:01.133606Z","title":"Fault Detection and Classification in Power Systems Using Machine Learning Algorithms","venue":null,"work_id":"f578d90d-0dd3-405a-a037-a8df5d721309","year":2021},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:0c8cc2de4ea4881361c9e2465373148d25985b99df450474d460572046aa4857","observation_id":"865b80b4-d7cd-469d-bafc-3aabe699fdb5","resolution":{"observed_at":"2026-07-11T19:48:13.437272Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-03T06:30:56.289259+00:00","source":"crossref"},{"observed_at":"2026-07-12T09:20:02.654109+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T09:20:02.654109+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-03T06:30:50.922721+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:39:07.667815Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:28f0cd23ddfea03f6f3dd5c1ceb13d1d84d1aa489cdc9a078e9451d78e5bba19","observation_id":"cf330ee3-1b89-4eed-a870-f17a492601f5","resolution":{"observed_at":"2026-07-11T19:39:07.667815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/en16207210","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T19:48:13.431935Z","title":"Explainable approaches for forecasting building electricity consumption","venue":null,"work_id":"d6e1c1f3-5402-4d78-9f1a-4ddf3593eb09","year":2023},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:299632280f3f30a9878d394181d21c31d14d420c6ec6b42b989aae2f74006744","observation_id":"ce6d47da-194f-4de7-829e-5bdfb02f1f11","resolution":{"observed_at":"2026-07-11T19:48:13.433988Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-03T06:30:56.289259+00:00","source":"crossref"},{"observed_at":"2026-07-12T09:20:03.38021+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T09:20:03.38021+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-03T06:30:50.922721+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2022.125468","doi":"10.1016/j.energy.2022.125468","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T00:15:01.133606Z","title":"K., Wu, M., Chen, J., & Zhang, L","venue":null,"work_id":"dbd01a7b-bc8a-4ce4-b061-a5d77beb9a4a","year":2023},"citing_paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T19:39:07.667815Z"},"links":{"citing_paper":"/paper/2607.04374"},"observation_digest":"sha256:aeded7bc868233748b2cabcb8830e7f0ce64fce76de848741fc6ed97b13fe755","observation_id":"b13f1820-fb76-46f6-9399-f2fb81be72de","resolution":{"observed_at":"2026-07-11T19:48:13.428449Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-03T06:30:56.289259+00:00","source":"crossref"},{"observed_at":"2026-07-12T09:20:03.690394+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T09:20:03.690394+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-03T06:30:50.922721+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.04374","last_updated":"2026-07-05T16:07:35Z","latest_version":1,"primary_category":"eess.SY","snapshot_observed_at":"2026-07-11T19:39:06.536739Z","submitted_at":"2026-07-05T16:07:35Z","title":"An End-to-End Explainable AI Framework with Automated LLM-Based Natural Language Explanation Generation for Energy Systems"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":3,"verified_fuzzy":0},"total_outbound_references":23},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-03T06:30:56.289259+00:00","source":"crossref"},{"observed_at":"2026-08-03T06:30:50.922721+00:00","source":"retraction_watch"}],"thesis":"As of 3 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.04374."}