{"as_of":"2026-08-21T19:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9b4424df7e73eb8013ba840338d5a7a17cfa3cd3de61f6335cc09440144c54b9","coverage":[{"denominator":77,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":77,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-08T19:45:46.002113Z","state":"measured"},{"denominator":77,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":77,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2607.05985/citation-record","integrity":"/paper/2607.05985/integrity","json":"/paper/2607.05985/citation-record.json","paper":"/paper/2607.05985"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T20:45:37.905624Z","title":"The design structure system: A method for managing the design of complex systems,","venue":null,"work_id":"945a2cc2-3ff8-4518-a166-0cb0c6087178","year":1981},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:f52032808399801dff3c9e8fa6b2224557b949f602aa1dad339e13cc23bdba2c","observation_id":"827e2c7b-9e41-419a-a1b1-1ba3d8d2f53b","resolution":{"observed_at":"2026-07-08T20:45:37.906803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.917073Z","title":"Eppinger and T","venue":null,"work_id":"8fd6c268-86aa-4b11-a31f-8e1d2305503d","year":2012},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:162bb0f5b5ce8060a4198614de0bbaa5a75668dbbc0bbf084b3099be03eb0c91","observation_id":"31db4d5b-641f-4f01-8259-3e3a0dd8dbcb","resolution":{"observed_at":"2026-07-08T20:45:37.918193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.617968Z","title":"Design structure matrix extensions and innovations: A survey and new opportunities,","venue":null,"work_id":"cb1ef200-3a29-4d4e-b7bc-39cee8ccf499","year":2015},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:f6931dc7886490ed4c6bd586ad75c8b7fb0e02f6e7408b20bb038c70ec2415c5","observation_id":"b7d2887c-0241-4a92-accc-85d98b995a41","resolution":{"observed_at":"2026-07-08T20:55:35.619533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.889005Z","title":"Predicting change propagation in complex design,","venue":null,"work_id":"9d4574d6-01bf-4456-a179-65652d86decf","year":2004},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:9c8f32e48d9be26e388ace7274375ed585bb44499580d72896ad003afe000d9b","observation_id":"cb34999c-2917-4c8f-9b37-0b08eca6c53a","resolution":{"observed_at":"2026-07-08T20:45:37.890595Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.898599Z","title":"Generation of a function-component-parameter multi-domain matrix from structured textual function specifications,","venue":null,"work_id":"8dcc39db-3bf8-4535-b249-88360b7ec22e","year":2018},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:fb696826113259a722cb402cc47d5b00788c899243b3dc29e6ad2d4bf44e857e","observation_id":"212d3eda-5cf3-4aa3-a09d-9cfaa134fc8e","resolution":{"observed_at":"2026-07-08T20:45:37.899813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.900474Z","title":"Knowledge management technology,","venue":null,"work_id":"5653bd76-31cb-49bd-b61a-89a478ca97d3","year":2001},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:b55775cbf2111503d2fd375ef959dc4863eec96a699b3f96ef1a717eacaeb972","observation_id":"9fefafab-8c22-4897-9575-b264b87cb39c","resolution":{"observed_at":"2026-07-08T20:45:37.901546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.893243Z","title":"Guest Editors’ Introduction: Knowledge Management in Software Engineering ,","venue":null,"work_id":"12fac022-9dc3-4a4d-ac0d-f648795e8ce9","year":2002},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:80ab5e214a4e1b9ed862b582e83c73c09c8e7c134280ff15bffcf1e4a1eaf04c","observation_id":"e962297f-ea86-47a1-a970-a7cc6cd246e5","resolution":{"observed_at":"2026-07-08T20:45:37.894460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.885016Z","title":"Rubens,Science and technical writing: A manual of style","venue":null,"work_id":"cdc0a2e3-6d07-42d9-a65e-31b6fa14ab63","year":2002},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:f749ae97cb7c95d8782cd17e4a94e6ebc7dd9cde3154ed35a3c7a5b1c861e181","observation_id":"2f61fa52-bda4-4171-9e71-b89395e7b030","resolution":{"observed_at":"2026-07-08T20:45:37.886210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.886970Z","title":null,"venue":null,"work_id":"4b4f804f-66e3-405f-a9f5-8232f45f298b","year":2002},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:ea3f810d04228cd5297019c93780eabda2ea2bdbb79e89f7498d3b969a9076c1","observation_id":"749f0be4-a9d8-4a97-9adf-67d52cc1b5e3","resolution":{"observed_at":"2026-07-08T20:45:37.888258Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.891326Z","title":"Model-based systems engineering: Moti- vation, current status, and research opportunities,","venue":null,"work_id":"47e6c55e-6b01-436e-9408-59c8015fef8b","year":2018},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:32c73ebc5f56063fd0cb9cbb018324fa84cdbef3a127af029e4221b5f1c445bc","observation_id":"79ca4d83-a1e7-4e9c-a064-aff95e7c918f","resolution":{"observed_at":"2026-07-08T20:45:37.892546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.879117Z","title":"A taxonomy of mbse approaches by languages, tools and methods,","venue":null,"work_id":"9806b180-ab8b-4499-a6fa-906b64b64eb2","year":2022},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:c80c04fa8764cee8d0cc42b85a8de4879a4ffaa3f6c498fb45f4fedfbf9ad583","observation_id":"6e58a58f-feae-4db3-ae24-e623a39411ea","resolution":{"observed_at":"2026-07-08T20:45:37.880319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.877261Z","title":"Model-based systems engineering: Evaluating perceived value, metrics, and evidence through literature,","venue":null,"work_id":"591f5e0b-5d90-4327-ba2f-c950369063ca","year":2023},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d704a2f67cbdc082f21033ca5c9032fee530cf9ca9e701b6e6ad76ec2d4dbc84","observation_id":"80059040-feb7-4673-9ae9-3f85296f75ba","resolution":{"observed_at":"2026-07-08T20:45:37.878542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.880872Z","title":"Utilization of system models in model-based systems engineering: Definition, classes and research directions based on a systematic literature review,","venue":null,"work_id":"be085564-9a46-49f1-80bc-57b87b51af9b","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:3d76133045df4cbd7d2a87bd8f425a945840b4416479865694875fad946f7492","observation_id":"e61d5fdd-9a76-4fc0-ae19-da06f2539664","resolution":{"observed_at":"2026-07-08T20:45:37.882193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.882999Z","title":"Bridging the Gap Between Requirements Engineer- ing and Systems Architecting: The Elephant Specification Language,","venue":null,"work_id":"0bb81d43-2f64-43f9-b66a-f9e19f53a4cf","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d1be5cd7f3e195de1ec128f9537ee247f3d652b825b21751e0f92ac96894bc04","observation_id":"aca9c905-7134-4308-bc10-1433c610b618","resolution":{"observed_at":"2026-07-08T20:45:37.884266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.895052Z","title":"Deep learning for ai,","venue":null,"work_id":"2a8a165e-f9c4-48e0-bd25-b6a3d38ae299","year":2021},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:8650ffc2521bf287cf7c083e4d756fd245ee9f65d237a06c00b97b3ba6162326","observation_id":"343fb037-1cc6-4ddc-a858-ea75eba7a4c8","resolution":{"observed_at":"2026-07-08T20:45:37.896151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12712","last_updated":"2023-04-13T20:41:31Z","snapshot_observed_at":"2026-08-18T22:17:47.865607Z","submitted_at":"2023-03-22T16:51:28Z","title":"Sparks of Artificial General Intelligence: Early experiments with GPT-4","version":5},"cited_work":{"arxiv_id":"2303.12712","doi":"10.48550/arxiv.2303.12712","metadata_source":"pith","pith_arxiv_id":"2303.12712","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Sparks of Artificial General Intelligence: Early experiments with GPT-4","venue":"cs.CL","work_id":"a23cfe92-7f7c-424b-98d4-b386a83002fb","year":2023},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/2303.12712","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d7598ab1cad0b0d32c65766477ffd2e20576887640fb7e130d8d3183e34fa7e7","observation_id":"1238e984-b301-48a1-9679-446bf927fa54","resolution":{"observed_at":"2026-07-08T19:55:33.959583Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.902195Z","title":"Auto-DSM: Using a Large Language Model to Generate a Design Structure Matrix,","venue":null,"work_id":"dcd86d97-6c54-4f81-b621-bee47cb5063d","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:3cda27b52629c4ede19355979309b45b395d454191a2e921982511eadcfa1cc2","observation_id":"f7c73ba1-e686-41f0-ac80-c35449005eea","resolution":{"observed_at":"2026-07-08T20:45:37.903409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-11T02:07:57.548428Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,","venue":null,"work_id":"b5aae673-de94-47cc-990e-5e144541a530","year":2025},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:335992e3410273d380063e3e79241ef200fefd6e9f4402f3afe8d8dc742a89eb","observation_id":"a29d1c56-a608-4254-931e-51bd214e554b","resolution":{"observed_at":"2026-07-08T20:45:36.112979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.591434Z","title":"Survey of hallucination in natural language generation,","venue":null,"work_id":"3d0be242-0273-4ed3-bdf2-e34a3c9da8da","year":2023},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:92e2e11b44c47fca967363f5fe1701ac9443396553d7ea49d82c52dfc91247a4","observation_id":"ff6425ce-469b-4cde-92cc-af093764258a","resolution":{"observed_at":"2026-07-08T20:55:35.592537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.098305Z","title":"Know your limits: A survey of abstention in large language models,","venue":null,"work_id":"0add1b8b-3750-4823-b8d2-0576b093c7d2","year":2025},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:f1b16de7d2d5b1816c53e6ae870e4e4c675d79209d4d8172a42b92e5b9c08030","observation_id":"fba21bdf-0344-44b4-a09d-9f95bf96ba67","resolution":{"observed_at":"2026-07-08T20:45:36.099366Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01563","last_updated":"2024-04-04T11:32:03Z","snapshot_observed_at":"2026-08-16T14:03:40.226273Z","submitted_at":"2024-04-04T11:32:03Z","title":"Mitigating LLM Hallucinations via Conformal Abstention","version":1},"cited_work":{"arxiv_id":"2405.01563","doi":"10.48550/arxiv.2405.01563","metadata_source":"pith","pith_arxiv_id":"2405.01563","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mitigating LLM hallucinations via conformal abstention, 4 2024","venue":"cs.LG","work_id":"b776d949-6f20-4359-bee3-56d21bd58524","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/2405.01563","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:af9eeb43f58831b5d5b1cb8736528215533fd09e2ba0f548444d3cbe2b7522b6","observation_id":"3b691098-c46c-453b-9282-8f7ae2d4b49a","resolution":{"observed_at":"2026-07-08T19:55:33.956409Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16221","last_updated":"2024-09-24T14:25:58Z","snapshot_observed_at":"2026-08-19T23:11:40.435660Z","submitted_at":"2024-07-23T06:56:54Z","title":"Do LLMs Know When to NOT Answer? Investigating Abstention Abilities of Large Language Models","version":2},"cited_work":{"arxiv_id":"2407.16221","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.16221","snapshot_observed_at":"2026-07-08T19:55:33.960847Z","title":"Do llms know when to not answer? investigating abstention abilities of large language models.arXiv preprint arXiv:2407.16221","venue":"cs.CL","work_id":"fbe2f53d-5ccf-4007-8582-5d2688add694","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/2407.16221","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:03b8e2ec631c3896ae26bfea76094dc8f78d2cf6ae6f811aab35d518a4e72298","observation_id":"7cbb30f9-6e33-4599-8211-fc5229f886a2","resolution":{"observed_at":"2026-07-08T19:55:33.962308Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.612495Z","title":"How many random seeds? statistical power analysis in deep reinforcement learning experiments,","venue":null,"work_id":"f1c56859-3aee-426a-82c0-c5c302741aeb","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:850ef9612500a26d7d7fec1ab6e58e3259664a27fe6842b6e46fe5a06dd620ca","observation_id":"5bb0ba74-ed11-4d78-b2fe-da7fa76f2d37","resolution":{"observed_at":"2026-07-08T20:55:35.613701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1806.08295","last_updated":"2018-07-05T06:50:33Z","snapshot_observed_at":"2026-08-18T13:01:04.967846Z","submitted_at":"2018-06-21T15:39:19Z","title":"How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments","version":2},"cited_work":{"arxiv_id":"1806.08295","doi":null,"metadata_source":"pith","pith_arxiv_id":"1806.08295","snapshot_observed_at":"2026-07-08T19:55:33.971005Z","title":"How Many Random Seeds? Statistical Power Analysis in Deep Reinforcement Learning Experiments","venue":"cs.LG","work_id":"4e911bc0-5394-4867-b4c7-90dba31bb148","year":2018},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/1806.08295","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:6994d52089d04cda3531e24560ebde06bc776cabeab35bd75f9c8f7ee1cb0926","observation_id":"251f690d-17c5-4e7c-9575-4dcc1eb516c8","resolution":{"observed_at":"2026-07-08T19:55:33.972391Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.08387","last_updated":"2020-12-15T16:01:21Z","snapshot_observed_at":"2026-08-18T14:16:04.991941Z","submitted_at":"2020-12-15T16:01:21Z","title":"Run, Forest, Run? On Randomization and Reproducibility in Predictive Software Engineering","version":1},"cited_work":{"arxiv_id":"2012.08387","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.08387","snapshot_observed_at":"2026-07-08T19:55:33.968624Z","title":"Run, Forest, Run? On Randomization and Reproducibility in Predictive Software Engineering","venue":"cs.SE","work_id":"724e2689-765c-46b7-8fcc-81e765a2c78c","year":2020},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/2012.08387","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:ccbdc6c0c20b3aedd3173fcf493a68d4e99eb3725b1c16a854f80551bde56da4","observation_id":"894db903-8405-4889-9f38-58efa1576569","resolution":{"observed_at":"2026-07-08T19:55:33.970005Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.875277Z","title":null,"venue":null,"work_id":"7962af81-b392-4c65-aec5-16c2c9237fe1","year":2020},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d60e43c2e49a555630ebf52d772b2ca4391d442e6a5078f136b34d0e442c299e","observation_id":"0bf5aead-424d-40a8-92ec-6f9c31cd273f","resolution":{"observed_at":"2026-07-08T20:45:37.876461Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.896720Z","title":"Beizer,Software Testing Techniques","venue":null,"work_id":"990cb912-ab35-44f6-b205-b4507664e9a4","year":2003},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:67e8d21ac2e93111d4414aa57a6d826778d3cdecfae81b7bf5759c737427da28","observation_id":"38fa3ca2-d5aa-422f-8155-42c30df93e96","resolution":{"observed_at":"2026-07-08T20:45:37.898030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.904023Z","title":"Myers, C","venue":null,"work_id":"d7cd50dd-cd23-4459-84a8-30dbf428e3c1","year":2011},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:161925620ad04d9582344586f4b93c6c24009a9747e762f5c62cd9b5de3db0c6","observation_id":"f5e7ae46-8810-49f8-acc9-c5e498d7a1e2","resolution":{"observed_at":"2026-07-08T20:45:37.905103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.872652Z","title":null,"venue":null,"work_id":"03e2c42c-06a4-4eed-a2ae-470b04df0128","year":2005},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:08577617cfbc92e5303795095da26f355b6feb7e479cb326b8f0f4d4d3697bb3","observation_id":"b6abafae-ae97-48c2-a40d-19670f8d446f","resolution":{"observed_at":"2026-07-08T20:45:37.873984Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.593038Z","title":"Degree of modularity in engineering systems and products with technical and business constraints,","venue":null,"work_id":"92482883-3bff-4715-a680-b7b15d52369f","year":2007},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:08421834adf96b27ffd0fa8f50510a8396259974d5a9900d01030915a384e63a","observation_id":"18949d70-1f38-48e1-8cff-e517149eaacc","resolution":{"observed_at":"2026-07-08T20:55:35.594418Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.606934Z","title":"An introduction to roc analysis","venue":null,"work_id":"92d3505b-355a-4f2b-bd47-d9a6b558f577","year":2006},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:7e8738ecc7491fe55aa634e70c3328c0ae705e38e3c561663cff87990874d034","observation_id":"111a47ec-e5e8-4bc6-b060-726c854c3914","resolution":{"observed_at":"2026-07-08T20:55:35.608087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.099975Z","title":"Scikit-learn: Machine learning in python,","venue":null,"work_id":"78355956-f7d6-4848-a9b2-63cff21768ae","year":2011},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:62065a7c4da16740549693e3b85a9c4f6bee69642a3ec1195d5d575016f820d3","observation_id":"b6af7bb9-d24c-4b3f-96e9-d117945e4612","resolution":{"observed_at":"2026-07-08T20:45:36.101059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.583883Z","title":"On the foundations of noise-free selective classifi- cation","venue":null,"work_id":"b497305c-99a0-4458-bd0b-478937bb1e9f","year":2010},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:396f0efe9da9775beb8bd90580c5d7c5d3c5a2d800a86759d4d9931c306cf074","observation_id":"3a3c8680-4239-4cba-8a52-f1a2e41742ce","resolution":{"observed_at":"2026-07-08T20:55:35.585072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.096626Z","title":"Selectivenet: A deep neural network with an integrated reject option,","venue":null,"work_id":"a56eba97-2694-4edc-8b80-14d012a11f78","year":2019},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:410ee90e07f768d733796c55f428c92580133afbf68f137cd7c5343ffde9e576","observation_id":"92d757ee-318a-4c22-af55-2dfae4b2925a","resolution":{"observed_at":"2026-07-08T20:45:36.097729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.598441Z","title":"The hitchhikers guide to testing statistical significance in natural language processing,","venue":null,"work_id":"aa46d6f3-db48-47c5-8176-6b558f43717a","year":2018},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:eed345b5dfff5a419da4be2a3068408b33a62c331c2940486476becf432df0b0","observation_id":"26017ba4-6ddc-41f5-a1f4-426c9c61d617","resolution":{"observed_at":"2026-07-08T20:55:35.599581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.077938Z","title":"Unreproducible research is reproducible,","venue":null,"work_id":"5f27a7e9-7680-4828-92d2-358bc7b6d0f9","year":2019},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:34bd521228edf4711d49ed6e2e60ebce33069528a8385b784b7a7f843615e5e1","observation_id":"d3fa6142-9ca8-43ea-b230-12dc16f87c0e","resolution":{"observed_at":"2026-07-08T20:45:36.078885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1711.02173","last_updated":"2018-02-24T19:44:38Z","snapshot_observed_at":"2026-08-15T03:06:48.317810Z","submitted_at":"2017-11-06T20:59:58Z","title":"Synthetic and Natural Noise Both Break Neural Machine Translation","version":2},"cited_work":{"arxiv_id":"1711.02173","doi":null,"metadata_source":"pith","pith_arxiv_id":"1711.02173","snapshot_observed_at":"2026-07-08T19:55:33.966153Z","title":"Synthetic and Natural Noise Both Break Neural Machine Translation","venue":"cs.CL","work_id":"6e576401-5645-4122-8826-4fa28c2f3b0e","year":2017},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/1711.02173","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:9157287146a3c808423196a640245e687c232f1160c508d934e5d5e5d6fe2a39","observation_id":"e31c4486-53ce-41e3-b83c-c0b1250088be","resolution":{"observed_at":"2026-07-08T19:55:33.967549Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.610592Z","title":"Large sample variance of kappa in the case of different sets of raters","venue":null,"work_id":"4c871cfc-8a95-4838-b41b-56fae446cf6f","year":1979},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:fc32197a326380614b2e1be96c608544f172d2d169037d1d29984cb214cc5246","observation_id":"a7b0612a-8e03-4dee-b52b-1f678a0e2989","resolution":{"observed_at":"2026-07-08T20:55:35.611824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.581733Z","title":"An application of hierarchical kappa- type statistics in the assessment of majority agreement among multiple observers,","venue":null,"work_id":"b99fd311-ed91-4567-8a08-fd9affb46b1e","year":1977},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:badda6774efa0988df0f43bf67a4546fa238a9e2fc819fc4612af7f46329605c","observation_id":"a6a7d3c7-6158-4a12-8827-2a5448fb14f9","resolution":{"observed_at":"2026-07-08T20:55:35.583322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.600067Z","title":"A High-definition Design Structure Matrix (HDDSM) for the Quantitative Assessment of Prod- uct Architecture,","venue":null,"work_id":"3247fd28-e451-4fc4-acb3-1e2d78c25a21","year":2012},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:ceb329381296a3c95a81eafe7c17edd4a73d28b36befcb8b08b9203744c3a30d","observation_id":"bf686bce-e7ec-43fa-b4d5-60ab31215fb7","resolution":{"observed_at":"2026-07-08T20:55:35.601338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.596682Z","title":"Improving data quality in dsm modelling: A structural comparison approach,","venue":null,"work_id":"17d6d88d-ccaa-439d-b333-65161701ec29","year":2011},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:6c96b0effdeffb1a536a724641e045b3eec5668ea360b104204e52e083fa40b0","observation_id":"34ffdc3e-7a3f-484a-a279-23edbcbd518e","resolution":{"observed_at":"2026-07-08T20:55:35.597834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.589653Z","title":"Applying the design structure matrix to system decomposition and integration problems: a review and new directions,","venue":null,"work_id":"76a94586-6403-4d82-8ded-0d96fa99fac3","year":2002},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:732c266bd5aa3147e85d13fe08ecb6e819ec60290895d8ec5d2217ea08b3ab87","observation_id":"48041120-60e5-4bcc-a201-c133a2df4d18","resolution":{"observed_at":"2026-07-08T20:55:35.590893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.585629Z","title":"The foundations of cost-sensitive learning","venue":null,"work_id":"25e4cdf6-b440-4ac6-a2aa-386bbe7b9bf6","year":2001},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:6dfdc2d04e2472b708823711c36a086aff5861052a0b3b8dda807031ab17001a","observation_id":"c8e4169e-420e-419c-9318-cae16fbb07fe","resolution":{"observed_at":"2026-07-08T20:55:35.586910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.113549Z","title":"On optimum recognition error and reject tradeoff,","venue":null,"work_id":"4f96d616-75db-45e7-839a-4f42fa2456ca","year":2003},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:6d28594d6bdf5a2adecd26b96c6202788d5711bd559d02db78a2d2b06b0fc27a","observation_id":"89bbf5ef-6475-4a16-a5c2-4f646cda22a1","resolution":{"observed_at":"2026-07-08T20:45:36.114579Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.587461Z","title":"Measuring classifier performance: a coherent alternative to the area under the roc curve,","venue":null,"work_id":"01f61e71-2293-4df6-8156-364bb9925abe","year":2009},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:5fe35a6f222bcfe8760e0d1ff5e2b80d6d09044bb29d41529bca41cdd9839006","observation_id":"38af3097-cdbd-462e-ab7b-664227e1d234","resolution":{"observed_at":"2026-07-08T20:55:35.588756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.601916Z","title":"Accounting for variance in machine learning benchmarks,","venue":null,"work_id":"7e8c505f-e1b9-49ff-8d73-dbcf45d0543a","year":2021},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:cf16d12026c2ead36ae069dbf4465c5e1a5658c0cf0be4f0c6e6e9652a15a47f","observation_id":"db3dce14-cd60-4745-9b8d-035f4bf821ae","resolution":{"observed_at":"2026-07-08T20:55:35.603117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.608633Z","title":"Muc-5 evaluation metrics,","venue":null,"work_id":"a2ed2291-8a81-4c79-86d5-0bf5b1c676a1","year":1993},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:f1ad0208fd6473f95b5d7a6059251e9e11452c508ccbea00f3c18f3376015042","observation_id":"babe5990-a888-4b85-b91f-3316b0c6ced2","resolution":{"observed_at":"2026-07-08T20:55:35.609819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.605191Z","title":"Using mbse for the enhancement of consis- tency and continuity in modular product-service-system architectures,","venue":null,"work_id":"b368068e-2f38-4a0b-9a14-758d8047fad8","year":2021},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:8d67e67cc6af194ede6a66a00e2c3e44c370ded3a3551890b4cfd51a4cc8b5a7","observation_id":"54b36df2-d4e8-4ad9-b6a7-078601b6e686","resolution":{"observed_at":"2026-07-08T20:55:35.606423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.103380Z","title":"Complexity should not be in the eye of the beholder: how representative complexity measures respond to the commonly-held beliefs of the literature,","venue":null,"work_id":"71b68dbf-2429-4167-9bf6-4fa226951e37","year":2021},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:c1f537e660a9bf3de45cac6bc2a5b935a9b7db9243581e7c4ac194a453fba1f6","observation_id":"ae7ed926-c550-423d-994f-7be6a594b8e7","resolution":{"observed_at":"2026-07-08T20:45:36.104508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.594950Z","title":"A Prompt Pattern Catalog to Enhance Prompt Engineer- ing with ChatGPT,","venue":null,"work_id":"29b24b21-ae38-47b9-9d9a-a5e0e1097080","year":2023},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:21e0e74e067385911a008c53b2ff2a7d831de2b6a178f97d7fbd2a99eb470753","observation_id":"58ba4d9d-6247-49f1-b55e-2be4e7658244","resolution":{"observed_at":"2026-07-08T20:55:35.596157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.36227/techrxiv.22683919.v2","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Prompt Engineering For ChatGPT: A Quick Guide To Techniques, Tips, And Best Practices,","venue":null,"work_id":"bba16191-f9f0-4d79-b0ac-cb49b7153c0b","year":2023},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:09ef42b937f6d8a2234e837d74e51ab6563172adf329075f4330652bdede6477","observation_id":"71e03d5e-8c0d-4fbb-8f6c-cd774c4c6391","resolution":{"observed_at":"2026-07-08T19:55:33.653584Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-07-11T05:19:32.533172+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T05:19:32.533172+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-08-13T07:04:41.220509Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":"2201.11903","doi":"10.48550/arxiv.2201.11903","metadata_source":"pith","pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","venue":"cs.CL","work_id":"d1cf6693-a082-403c-ada9-dac7b96341f9","year":2022},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:71c7a3cb2775ef65055ba6c58e73cd651bd300ec27795cd3c6ea890c887abf2b","observation_id":"24794583-14c1-48f1-a018-107ae2e654fe","resolution":{"observed_at":"2026-07-08T19:55:33.964991Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-13T20:38:16.194749+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-13T20:38:16.194749+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.616227Z","title":"Language models are few-shot learners","venue":null,"work_id":"724771a4-4d10-4406-a9f2-d52b5b2e8ec2","year":1901},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:0c44d4fe3ed5bbc451769aef69ab2c3cec5a6b3be0c738425f31bbab3bb4775c","observation_id":"9d2f59b2-940d-4da9-ad68-3cbf28f36b4c","resolution":{"observed_at":"2026-07-08T20:55:35.617401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.110172Z","title":"Know the unknown: An uncertainty- sensitive method for llm instruction tuning,","venue":null,"work_id":"b8e94dda-6edc-4b93-ac41-afd9b7f9d7e2","year":2025},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:8684f993a10fdc4acb11c13ea4406d9b68ff704ad0c7151f4de146102e895449","observation_id":"0020b873-4cd5-42dc-8e62-846ec5b3339a","resolution":{"observed_at":"2026-07-08T20:45:36.111260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.614260Z","title":"Trusting your evidence: Hallucinate less with context- aware decoding,","venue":null,"work_id":"5d707935-37cc-4a02-ad24-e88db25e1e99","year":2024},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:9ea3030c84c15974ee2772a7a681ed8b16e10428e3e802c0dd7e71d3473675fd","observation_id":"4f15b12c-cc52-4de6-9343-44c00486e987","resolution":{"observed_at":"2026-07-08T20:55:35.615385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.079416Z","title":null,"venue":null,"work_id":"2b662ee1-dae4-4baa-b037-d841666d456e","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:0b5b1feb5ac646019d29e10c6286232d40edf93161ee34ac5d09208add7a8ec6","observation_id":"6b563bee-9c60-4b3a-968c-f27d5330bf2c","resolution":{"observed_at":"2026-07-08T20:45:36.080570Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:55:35.603613Z","title":null,"venue":null,"work_id":"e94f8d7a-0bff-42e8-8cee-1d1c71a59796","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:6a1594da8aa95a673222baa628b04d6748a4608a0a0a379f6ec967e78063314c","observation_id":"0a866951-046d-41ac-958e-549756e3016a","resolution":{"observed_at":"2026-07-08T20:55:35.604662Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.932555Z","title":null,"venue":null,"work_id":"f8996b35-0dee-4c01-9230-8bfe0cc1b192","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:865671614198c1dc6c1dd445314132461a91dc3813988e45c825c2a25a54e5b9","observation_id":"2dfe22a3-2c67-48c2-ab8e-c6586fceecfb","resolution":{"observed_at":"2026-07-08T20:45:37.933551Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.934123Z","title":null,"venue":null,"work_id":"8d032a76-e518-4eb5-b50d-5b613a8c136e","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:8f468f16e6c9ca578f30de2c6e08a56736b81c947f59c0281c1d96121e1556ba","observation_id":"f0b475a8-c7e2-427b-9ee2-5f8f0487eebf","resolution":{"observed_at":"2026-07-08T20:45:37.935127Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.106805Z","title":"10: Prompt 2 for intra-subsystem interaction identification using Tilstra (2012) HDDSM","venue":null,"work_id":"a9f9dce1-0072-48a9-8b0d-71214fa10ab1","year":2012},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:2585dba7aaea849468383eca8349997f8c8177ee0eeb1b6e516949ffa918111b","observation_id":"57c96714-3c18-4911-8926-08df536fb81b","resolution":{"observed_at":"2026-07-08T20:45:36.107956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.928980Z","title":null,"venue":null,"work_id":"202c6508-159e-4d44-8824-492def1e56cd","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:60e8dae5fa61a64c2ae3cbfbd4d5a6e6b95adf2d44521a7b7be180a493712403","observation_id":"15d91513-a17d-4023-bd69-ea21246114ca","resolution":{"observed_at":"2026-07-08T20:45:37.930269Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.922145Z","title":null,"venue":null,"work_id":"04025394-9f0d-413b-9b5a-6ff409a6bc44","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:af21da4d72776cbf380ee87fd5c8bccef37975ed33bc8d07d987921aa02138b9","observation_id":"86efd049-18ac-4208-a5df-1e3da1561472","resolution":{"observed_at":"2026-07-08T20:45:37.923189Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.923741Z","title":null,"venue":null,"work_id":"83036284-a218-4837-bc64-c280aeef7173","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:3d62eff34f7667ffd638986e5ccf6cbbcee4d35c363f8637c6854a88b60ec9f1","observation_id":"00de40cb-cf57-44e3-aa40-707bb2ec97ea","resolution":{"observed_at":"2026-07-08T20:45:37.925025Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.925722Z","title":null,"venue":null,"work_id":"91d50fd9-ce47-42ff-a0ef-f86ffe059853","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:9923d1b0899b388ddcca598a79d8b96c2edaf4e8364c3cc9c5ea6f301dc42b17","observation_id":"e2e0b431-e9f7-4376-8618-5e518776cc8b","resolution":{"observed_at":"2026-07-08T20:45:37.926790Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.089969Z","title":null,"venue":null,"work_id":"9b330464-e8d4-4b02-8893-aa25eced608c","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d8c7485eafaa9d3b5ca1e0fe282ff0f598dd47de29f87981d6c093cf35f78078","observation_id":"454986a4-84c9-4fd2-bbe2-88584c98eeae","resolution":{"observed_at":"2026-07-08T20:45:36.091000Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.927302Z","title":null,"venue":null,"work_id":"d6d623af-042d-46fd-833e-5af38d008a80","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:d7e9b3503da90ec58cdccfe2c8048d32b0bf7fcbc9ccbc5d4ef95b2bedf24422","observation_id":"2fe794f2-be48-43dc-b489-e5acc2284c1e","resolution":{"observed_at":"2026-07-08T20:45:37.928322Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.930953Z","title":null,"venue":null,"work_id":"7cd17ed5-7249-48eb-a867-0c41c1f04d56","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:bea3cc3ed0518f9ca369c3480b5cc4de68a4bba82c4e4303e4cc8e11b15e1f35","observation_id":"8496c682-8581-41fe-9929-3a00bc803cea","resolution":{"observed_at":"2026-07-08T20:45:37.932016Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.066312Z","title":null,"venue":null,"work_id":"d836eced-183a-47c9-b57e-f7410d2f9599","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:e4f1ddbe91b8cb31efed84bebdce0c34d2c2d5a713111e9594da48980578dc9b","observation_id":"afd8cb92-ed4e-4339-b15f-c3f1cab76cdb","resolution":{"observed_at":"2026-07-08T20:45:36.067321Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:36.071153Z","title":null,"venue":null,"work_id":"55d78270-b5d9-48f6-8163-75ac6fc03815","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:beee4c42bc60110163e44bae566accf531808778219054a02f502b9a1da188a9","observation_id":"3c1aff9f-ae73-469b-8efc-f30459555f2a","resolution":{"observed_at":"2026-07-08T20:45:36.072194Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.920558Z","title":null,"venue":null,"work_id":"b19e28f6-1f10-4138-872e-0bc43259c805","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:70627e8bc5823fad51cb6f5b018b820eb9221bb1c345fdea12c0198f16798495","observation_id":"66b4f349-2698-4700-93ec-969b5fef86d9","resolution":{"observed_at":"2026-07-08T20:45:37.921605Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.910763Z","title":"# Instructions: The article should:","venue":null,"work_id":"d1d6fc6b-f899-4d0c-9bd2-77763480bee5","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:82b95ebdac762da501722058bbe9d002e2ec8bc5f87000ae385dfdfb0ce69615","observation_id":"f53bd873-6535-4cc8-9dbf-178c160260ba","resolution":{"observed_at":"2026-07-08T20:45:37.911828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.909140Z","title":null,"venue":null,"work_id":"851b8fa5-462b-4760-9bb6-4ab2bc42bec4","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:4dde8b8b16ecbe9808120afeef04892660f1e00cf6ed636f51ccc329bb66cb6d","observation_id":"5e4f3a44-ee55-4f52-8ece-18bd8ec21aa8","resolution":{"observed_at":"2026-07-08T20:45:37.910218Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.912362Z","title":null,"venue":null,"work_id":"878f0ef4-8d66-4204-b4a9-b1929549dacc","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:5194f936982e30caa0194a86a75d37cf1df6491d22638df65bfa2752792d3c64","observation_id":"ce6fa0e6-d8de-417b-87a8-6ce8b7d1b8ab","resolution":{"observed_at":"2026-07-08T20:45:37.913356Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.913890Z","title":null,"venue":null,"work_id":"810639d1-77ad-40c6-a92f-1bd044d723ec","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:ac2afb000f48573eb00455db52088c94ef28d34add56acc4e55ff69ed885eea9","observation_id":"dbc605aa-ade2-4d8d-8219-ab17dff5bc02","resolution":{"observed_at":"2026-07-08T20:45:37.914879Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.918925Z","title":null,"venue":null,"work_id":"233bdc37-4166-4d14-ad99-e64842d17be8","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:0e771cc4c30497e81cadef2106a3fba3c6415ba9b3cf23b7084866468031d6ff","observation_id":"07da314c-807f-4679-86f8-8c0d1554ccc2","resolution":{"observed_at":"2026-07-08T20:45:37.920005Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.915403Z","title":"- Describe all interaction types using their **Tilstra classification**","venue":null,"work_id":"5696afcd-71cc-428b-8aa6-1348a58dd2f8","year":null},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:ccc2ce43dd2e5c111bc1551525c0494007ee1cbdd28f2e2f101554ce8f42537c","observation_id":"51a17611-4c86-43d8-824b-a647c5322852","resolution":{"observed_at":"2026-07-08T20:45:37.916532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-07-08T20:45:37.907377Z","title":"# Constraints: - **No new components, interactions, or interaction types** may be added, inferred, or assumed beyond the input data","venue":null,"work_id":"2e54f730-4d25-442e-a0f2-0057b4d08bb9","year":2012},"citing_paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-07-08T19:45:46.002113Z"},"links":{"citing_paper":"/paper/2607.05985"},"observation_digest":"sha256:60d0139f0417df8d8046efc69061a5aed59edba7c8d1302fbaeac7ac06a32283","observation_id":"047d53c3-d955-46ba-a1a8-d7b82caea654","resolution":{"observed_at":"2026-07-08T20:45:37.908576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.05985","last_updated":"2026-07-07T08:17:49Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-14T11:51:38.538522Z","submitted_at":"2026-07-07T08:17:49Z","title":"Auto-DSM Under the Lens: A Black-Box Evaluation Framework for LLM-Based DSM Generation"},"reference_resolution":{"displayed":77,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":21,"verified_exact":7,"verified_fuzzy":48},"total_outbound_references":77},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:2607.05985."}