{"as_of":"2026-08-08T14:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dbf3deeba5e903f18826f4a30bfebd27a0d5f3f20249e240dbb928809e9d318c","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:44:19.119237Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2505.21109/citation-record","integrity":"/paper/2505.21109/integrity","json":"/paper/2505.21109/citation-record.json","paper":"/paper/2505.21109"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:26.218499Z","title":"“OpenAI.” https://openai.com","venue":null,"work_id":"d584ef59-af80-4a3d-91bc-6fb4dcabaad9","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.280501Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:d8b49556a0a00e9d638a5caac6371e3d02fa7bad74a90f077b9a33e704c0ab45","observation_id":"23a5d96a-75c8-4e11-8519-6fca093876aa","resolution":{"observed_at":"2026-08-07T13:44:26.306428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:26.002658Z","title":"“Gemini.” https://gemini.google.com/app","venue":null,"work_id":"beee35a9-daeb-4ebd-9b7a-4b9f2fda48ce","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.417720Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:a5629c491b9d68b79c1c4aecb032df19885b2459f3d88c74d02ed7d48ad9fbf4","observation_id":"610a89db-8201-463e-bd2d-6aef4044ecf0","resolution":{"observed_at":"2026-08-07T13:44:26.094628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-07T13:44:14.495637Z","title":"Llama: Openandefficientfoundationlanguagemod- els. CoRR, abs/2302.13971, 2023. doi: 10.48550","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.495637Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:bc07bd0746b643b63cd088e501336ed4038da8f150cd6edf6e44c08d72619f78","observation_id":"1c06685d-f9fc-49eb-bcf6-ac8baca2b820","resolution":{"observed_at":"2026-08-07T13:44:14.495637Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.11964","last_updated":"2024-04-18T07:50:10Z","snapshot_observed_at":"2026-08-08T06:22:36.073468Z","submitted_at":"2024-04-18T07:50:10Z","title":"From Language Models to Practical Self-Improving Computer Agents","version":1},"cited_work":{"arxiv_id":"2404.11964","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.11964","snapshot_observed_at":"2026-08-07T13:44:20.476479Z","title":"From Language Models to Practical Self-Improving Computer Agents","venue":"cs.AI","work_id":"6ffb9809-9a2c-4041-894b-0e6cd7cdb094","year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.571505Z"},"links":{"cited_paper":"/paper/2404.11964","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:b75b7d15270f415f572c1aabdd7e81a036699348f8f49e46447b59ee2e1e6e4a","observation_id":"c35cacc6-ce1f-4023-9b82-ae83a4b78d8e","resolution":{"observed_at":"2026-08-07T13:44:20.509610Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07864","last_updated":"2023-09-19T08:29:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-14T17:12:03Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07864","snapshot_observed_at":"2026-08-07T13:44:14.656509Z","title":"TheRiseandPotentialofLargeLanguage Model Based Agents: A Survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.656509Z"},"links":{"cited_paper":"/paper/2309.07864","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:7ad2bd60f5550d886fbbd55abb3ae962cadcee7fca4b3951d0b5acc3d9f7fa17","observation_id":"8c35abd7-cf79-4aa7-9919-8a7a037ecca2","resolution":{"observed_at":"2026-08-07T13:44:14.656509Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:25.739946Z","title":"ReAct — Synergizing Reasoning and Acting in Language Models","venue":null,"work_id":"2f5e0539-116d-47bc-8f20-fbd91f2e6290","year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.752101Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:1b82abdd01900998927bc9f83db4d25c77a6c0981ea42055d8f7e3dd022e3e6e","observation_id":"1c8df4c8-4848-4d61-a7f7-76b61fcfe7f9","resolution":{"observed_at":"2026-08-07T13:44:25.857622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:25.500012Z","title":"Data-driven innovation: What is it?","venue":null,"work_id":"a31abe3f-d2d1-47e4-9647-128c77326f86","year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.859152Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:8d1334cb0a51cec9c3692077f45e98a096c7c225eee91b402fd4baba3cdf1df6","observation_id":"96b10130-8514-4e3d-8bf0-8a36d0d4d6d2","resolution":{"observed_at":"2026-08-07T13:44:25.633947Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:25.260751Z","title":"A data-driven approach for creative concept gener- ation and evaluation","venue":null,"work_id":"c0891e88-bcda-4b19-9ad3-1e3506604ba8","year":2020},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:14.960100Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:449c05e5a44e626354f4388c8aafd2b223fca4d396f60a95eaa84c9b22ee7394","observation_id":"778bc98c-c82b-418d-8162-238869dbf03a","resolution":{"observed_at":"2026-08-07T13:44:25.355198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:25.185388Z","title":"EW-Tune: A FrameworkforPrivatelyFine-TuningLargeLanguageMod- els with Differential Privacy","venue":null,"work_id":"67871633-612c-4270-a308-cc6afd90ff24","year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.058952Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:3d2949a1a666f3f1be4b115c584263c5a4193156e52a318c2020d207844b3f0a","observation_id":"c4dd6ab9-fa65-4781-bbf2-bcaf01411316","resolution":{"observed_at":"2026-08-07T13:44:25.251535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:25.024116Z","title":"Exploring the limits of transfer learning withaunifiedtext-to-texttransformer","venue":null,"work_id":"938829cb-552f-4955-9a17-ee57646ffaa5","year":2020},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.128433Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:021b3df4d6718a3ca75e20437426e8fc62c21966b1d7367c88d7a0d09bed7a15","observation_id":"11cb460c-d4da-4bdd-8a3e-26718d7d869c","resolution":{"observed_at":"2026-08-07T13:44:25.094263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:24.797909Z","title":"Languagemodelsare unsupervisedmultitasklearners","venue":null,"work_id":"2bf715e2-b77c-494d-a7ea-9dcf998eb75a","year":2019},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.199054Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:aafc37e2e7786d16da2cf915abd9123ae6700d559596d0b0d349f72eb1d00f21","observation_id":"259d55dd-0b9d-4125-a906-b8a96651a5c2","resolution":{"observed_at":"2026-08-07T13:44:24.897979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:24.612890Z","title":"AttentionisAllyouNeed","venue":null,"work_id":"78a8ba68-2ea8-4de9-a22f-6d2d9d1185bb","year":2017},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.285410Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:4c71363127862444d764eb23cc43942f7c98f17efdc9980ccb8b9eb8d206bb0c","observation_id":"bd0d2b1a-9085-4b8b-8ca8-8661daae4275","resolution":{"observed_at":"2026-08-07T13:44:24.693819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:24.433227Z","title":"meta-llama/Llama-3.2-1B-Instruct","venue":null,"work_id":"9d59d765-f862-4fdd-8d27-8d022ae61a10","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.399722Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:0d61c92da6c6e346a6703faa055c616ccd9dc622226478fc675f0cf35068bbcd","observation_id":"0c29a3a3-91f5-4a02-9c5e-cc5e2a5af913","resolution":{"observed_at":"2026-08-07T13:44:24.521498Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T13:44:15.473525Z","title":"The Llama 3 Herd of Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.473525Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:78c01204073f46a4fc91304667b2431ceaad837338b4849f796cadfb8a006618","observation_id":"c83faa44-fb73-413a-ae47-e71d920863db","resolution":{"observed_at":"2026-08-07T13:44:15.473525Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:24.273630Z","title":"Causal Parrots: Large Lan- guage Models May Talk Causality But Are Not Causal","venue":null,"work_id":"1af78a02-c5d5-4bc3-8a0d-a10f5200cc50","year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.594146Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:edd528b0dc321ce4a3a6dca5dfe691ff23f2f98d6da7dc3a2fe36553a08e71d5","observation_id":"ec8b88e4-4b2e-48a0-ab07-e377e4d93918","resolution":{"observed_at":"2026-08-07T13:44:24.343603Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08039","last_updated":"2024-07-10T20:37:42Z","snapshot_observed_at":"2026-07-06T18:44:28.967181Z","submitted_at":"2024-07-10T20:37:42Z","title":"Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08039","snapshot_observed_at":"2026-08-07T13:44:15.766537Z","title":"Knowl- edge Overshadowing Causes Amalgamated Hallucination in Large Language Models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.766537Z"},"links":{"cited_paper":"/paper/2407.08039","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:82602ce84b8e141d54683569aceedbe7862f426298f76c679a5fd1d83dafd5d7","observation_id":"a8a1f837-03ac-4926-b388-f8d42cbd9462","resolution":{"observed_at":"2026-08-07T13:44:15.766537Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:24.138578Z","title":"Conceptual Design Generation Using Large Language Mod- els","venue":null,"work_id":"2d05b833-244e-4454-a509-1373928bd284","year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:15.904086Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:4b88e85e0708ecb856ecd6fdb32647c449168be2319d706c781af170037a0140","observation_id":"2809eeee-e6b0-4d69-8f9d-97a80ede640c","resolution":{"observed_at":"2026-08-07T13:44:24.194853Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:23.824126Z","title":"Augmenting human innovation teams with arti- ficial intelligence: Exploring transformer-based language models","venue":null,"work_id":"c50b19c6-0ff1-464a-8f8e-2d9889f6cc16","year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.085852Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:d36348c1a40688eb573a117e46145462c00edb1054b16a19e0539e0d4c0e5b36","observation_id":"7c4b36a7-9d5c-40d6-9679-6b2041b38593","resolution":{"observed_at":"2026-08-07T13:44:23.977587Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2023.11030","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:20.292112Z","title":"Artificial intelligence prompt engineering as a new digital competence: Anal- ysis of generative AI technologies such as ChatGPT","venue":null,"work_id":"733b9aa2-22ea-4b03-b479-806c53eccd08","year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.228519Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:6e151b8dcb3624c17e620414f2c3c2d50e2ce83eee4df301fe8fd73f88be8656","observation_id":"f39037b7-91fa-4896-b247-0f7b37047d78","resolution":{"observed_at":"2026-08-07T13:44:20.354730Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.04023","last_updated":"2023-11-28T09:01:12Z","snapshot_observed_at":"2026-08-07T14:17:12.140094Z","submitted_at":"2023-02-08T12:35:34Z","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.04023","snapshot_observed_at":"2026-08-07T13:44:16.364579Z","title":"A Multi- task, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.364579Z"},"links":{"cited_paper":"/paper/2302.04023","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:25cb8a5d3d5f77103d252affed7051784dd3ee99827dc0471f301311f1ecc105","observation_id":"52ca97b8-f104-45be-8c6d-b91590acb696","resolution":{"observed_at":"2026-08-07T13:44:16.364579Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:23.457450Z","title":"Finetuned Language Models Are Zero-Shot Learners","venue":null,"work_id":"80ae391b-2b7a-40db-9305-61f34b59523f","year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.480503Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:55c009b8d0282cd7870f14f6c89870d2e14357080117416bb9b4418206943f16","observation_id":"388669ea-1f38-459f-b53b-525bcc88f6c1","resolution":{"observed_at":"2026-08-07T13:44:23.660525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.08239","last_updated":"2022-02-10T16:30:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-20T15:44:37Z","title":"LaMDA: Language Models for Dialog Applications","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.08239","snapshot_observed_at":"2026-08-07T13:44:16.575098Z","title":"LaMDA: Language Models for Dialog Applications","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.575098Z"},"links":{"cited_paper":"/paper/2201.08239","citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:cb42c93ad525a9c95c2fb048724e0270586c95487878dae9f52bb763803b8b93","observation_id":"d94bb597-0046-4af5-81ca-07cc1ad6f6f9","resolution":{"observed_at":"2026-08-07T13:44:16.575098Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:23.225146Z","title":"Efficient Hierarchical Domain Adaptation for Pretrained Language Models","venue":null,"work_id":"4342c37e-43ad-428c-830b-e74cd401ae62","year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.678860Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:44382b373d7f875e29055861746cbdf7dc8b217c571e15897ea6a16af1903342","observation_id":"b08bb37a-b6db-4969-862a-65a39c98c116","resolution":{"observed_at":"2026-08-07T13:44:23.330405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:22.969542Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","venue":null,"work_id":"f4c81180-b2db-49e9-97d8-a2871dd4a12b","year":2022},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.751024Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:c086d93e20d992eb4acb34076d159067a62c45dd5eb483bd5c945ba039ca6604","observation_id":"7ac8ef22-f9a9-450c-92e2-46e1d968fa94","resolution":{"observed_at":"2026-08-07T13:44:23.116858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:22.668001Z","title":"Retrieval-augmented generation for knowledge-intensive NLP tasks","venue":null,"work_id":"97048b55-b530-4d40-8101-f94ed3534ea4","year":2020},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:16.895862Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:e4f8900e6e29af080244252bd6697d949934fcdabd4540f4e0a59f397269e2ff","observation_id":"674c9750-33fb-4187-b3e0-e2c3afce69eb","resolution":{"observed_at":"2026-08-07T13:44:22.772591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:22.469557Z","title":"Enhancing Retrieval-Augmented Generation: AStudyofBestPractices","venue":null,"work_id":"8e078c33-fd0e-4d11-a137-19895139dfaa","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.024656Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:5546caa507c547ffe1951645d250ce72623612283c87a370b8c53fdb63ae2fe7","observation_id":"179ef7ef-71a7-4bf4-825a-324a2dc89dc6","resolution":{"observed_at":"2026-08-07T13:44:22.563831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:44:17.134042Z","title":"Im- proving large language model applications in biomedicine with retrieval-augmented generation: a systematic re- view, meta-analysis, and clinical development guide- lines","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.134042Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:e9857027a4385d61bc5a2de24d02f4392b860f68c55e6316150c948338f1fde5","observation_id":"207642cb-adee-4873-8ce8-e7f54f10696b","resolution":{"observed_at":"2026-08-07T13:44:17.134042Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:22.296148Z","title":"Question-Based Retrieval using Atomic Units for Enterprise RAG","venue":null,"work_id":"e0ca26a5-a51e-4d3b-af71-3c0179ae3286","year":null},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.266315Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:0c8be33dba9eb696f84df62849993ddcf7285a74e6b461aa5cdb0f7550246f7e","observation_id":"ddaa0105-963f-4a7b-aeba-6ca77032942a","resolution":{"observed_at":"2026-08-07T13:44:22.369260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:21.886450Z","title":"Benchmarking Large Language Models in Retrieval-Augmented Generation","venue":null,"work_id":"f6c77582-c96e-4f5d-ae86-f9ef86d82e71","year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.511855Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:9cfe400ce47bdd201172b70a3af7d0e8e5568b73e3119538868d3bd47a0e4b94","observation_id":"d757ffbb-c16e-4dcc-868b-09995f52ce99","resolution":{"observed_at":"2026-08-07T13:44:21.980111Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3390/electronics13193936","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:19.775011Z","title":"In- formation Extraction of Aviation Accident Causation Knowledge Graph: An LLM-Based Approach","venue":null,"work_id":"060b0b02-0e0b-4062-907b-e071ef750d7e","year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.628526Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:40ede7eca53d81fda5b6fd164e384c18ae08624083c515b0dabf0d188e75d87e","observation_id":"697beca4-8e54-4bd7-bf3e-21ef38648668","resolution":{"observed_at":"2026-08-07T13:44:19.957190Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1021/acs.jcim.4c00857","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:19.518431Z","title":"MechBERT: Language Models for Extracting Chemical 9 and Property Relationships about Mechanical Stress and Strain","venue":null,"work_id":"f64ab642-f9cf-4ad3-9a06-51cf1dd874a5","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.742780Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:34aaec9067ac0a8ac03a81ffed1d6887e6ea7de944c2de645b01dc56c156bf7e","observation_id":"2d5898a4-4317-4924-b7da-fd35d5bfe4fc","resolution":{"observed_at":"2026-08-07T13:44:19.653368Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:21.653422Z","title":"An Approach to Intelligent Information Extraction and Utilization from Diverse Documents","venue":null,"work_id":"12f0ad6f-8716-4e03-a850-83eb93018d7c","year":null},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.831660Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:25a24be84d340be81aa986d3291ddb8bd0906ef93bbb7f982ef5fcac9e3e1c4a","observation_id":"0bbe831c-5d8d-43be-8c7a-66ef54c6ec47","resolution":{"observed_at":"2026-08-07T13:44:21.794681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:21.496721Z","title":"Single Engine Models 172, 182, T182, 206 AND T206 1996 And On","venue":null,"work_id":"dc4f50ef-f432-4e92-8fd1-5a714484af07","year":1996},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.168093Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:6bbd38c6d3993d4352cc27ee14336d07ddb8f6d7e7bd615c2c385774405ed929","observation_id":"bd2f9d4d-33bc-4012-9725-cfd7674c4084","resolution":{"observed_at":"2026-08-07T13:44:21.565094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:21.318791Z","title":"meta-llama/Llama-3.3-70B-Instruct","venue":null,"work_id":"390107a3-cd88-4c91-8fe5-4710fdfa70cc","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.293392Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:bfd1c76669458fccd4fd761e11a6d9549a185bbba87ceb081a99197bf50fdf8f","observation_id":"26ae090e-ba9c-4327-967f-3c3dfb49bb05","resolution":{"observed_at":"2026-08-07T13:44:21.412264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:21.108583Z","title":"LangGraph","venue":null,"work_id":"0d45b25a-4eb9-4965-b5d5-86c0a3493d31","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.467489Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:e90f2c2be380a0a89de37820005d4ac1aeee2f1e4bd834e0d83807d357e178cc","observation_id":"82d956b0-e4a6-48c8-aca7-e0ac67099469","resolution":{"observed_at":"2026-08-07T13:44:21.207611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:20.897670Z","title":"meta-llama/Llama-3.1-8B-Instruct","venue":null,"work_id":"84941cd1-0323-4a8c-b8c6-b139187de233","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.600248Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:7a311a0ffcb72a3c5347d56606f8f9c9f2fc30b4e9e7030f7c5befad2921c6c7","observation_id":"e8a0b5c4-01b4-42d3-a443-784c8a1f30f6","resolution":{"observed_at":"2026-08-07T13:44:21.032101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:20.736590Z","title":"fine-tune: full fine-tuning pipeline","venue":null,"work_id":"0a07f3b0-0ae9-4117-be60-3bc9d573f7da","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.817240Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:570d9f2a8dbe2f42ba3e1b8cabbc61797bb45ffee47aa524930be21239e7694d","observation_id":"2bd4e78e-fe9f-4e02-b9d5-18c548385495","resolution":{"observed_at":"2026-08-07T13:44:20.805974Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:20.604745Z","title":"“Llama.” https://www.llama.com/","venue":null,"work_id":"b804e237-9932-44a8-8049-42d7513419fb","year":2025},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.995476Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:3d8037faa9fcd0c850e3b6cd75033f65b41d7fe30c0f8b58201e27b7952a23a8","observation_id":"a4ad8eff-bcf5-45c8-8433-010e5bc8eb34","resolution":{"observed_at":"2026-08-07T13:44:20.658765Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/11558989_19","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:19.260496Z","title":"The Bittorrent P2P File-Sharing System: Mea- surements and Analysis","venue":null,"work_id":"ac1bd2bf-74d0-449e-9979-bc4a96cead91","year":2005},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:19.119237Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:1f6024170eed2bf477fffd253e9f585d28bccd99db3ea82cb382f759915cb25f","observation_id":"09760731-f361-44a6-a7e0-2389f3bc8615","resolution":{"observed_at":"2026-08-07T13:44:19.380164Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:44:22.085406Z","title":"URL https://www.scopus.com/inward/record","venue":null,"work_id":"cbb2fe4b-c648-4087-9107-cf0fafc49411","year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":233,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:17.390437Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:f2146c700b5a7961ac6727b9396209b6993453f8845eef12cc785691c21b1f67","observation_id":"e877a408-c390-40ba-9b76-b7e18bdd7e0b","resolution":{"observed_at":"2026-08-07T13:44:22.186776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T13:44:18.021276Z","title":"URL https://www.scopus.com/inward/record","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T13:44:18.021276Z"},"links":{"citing_paper":"/paper/2505.21109"},"observation_digest":"sha256:cd6b71312e9e415e858682b7f4837c5dc1db7bf684fafe0af151f7adb098898f","observation_id":"ca665a51-4841-41b4-a4df-e31afef9092d","resolution":{"observed_at":"2026-08-07T13:44:18.021276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.21109","last_updated":"2025-05-27T12:31:24Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T03:34:43.019458Z","submitted_at":"2025-05-27T12:31:24Z","title":"A Lightweight Multi-Expert Generative Language Model System for Engineering Information and Knowledge Extraction"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":5,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":4,"verified_fuzzy":25},"total_outbound_references":41},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2505.21109."}