{"as_of":"2026-08-06T12:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:909b7861a55c882436923ca8aa3e4005c27302617f853e615728d9c4e9cb329f","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":17,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T08:13:03.645303Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-11T03:27:45.276446Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2511.07329","last_updated":"2026-05-16T15:05:35Z","snapshot_observed_at":"2026-07-06T22:35:22.282985Z","submitted_at":"2025-11-10T17:31:39Z","title":"Preparation of Fractal-Inspired Computational Architectures for Advanced Large Language Model Analysis","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-17T23:22:59.323897Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2511.07329"},"observation_digest":"sha256:16af61640c4a2625e8cb2761673a6ef0ff23b896e9b789620c97e96767ec4ab9","observation_id":"d9445dbc-0548-45a8-8d9b-f96eab9d5f29","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2511.07329","last_updated":"2026-05-16T15:05:35Z","snapshot_observed_at":"2026-07-06T22:35:22.282985Z","submitted_at":"2025-11-10T17:31:39Z","title":"Preparation of Fractal-Inspired Computational Architectures for Advanced Large Language Model Analysis","version":4},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-21T19:25:25.465712Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2511.07329"},"observation_digest":"sha256:8ecf791cd1d81d6dfe0aca5e75eece5ecef2e23325a7fe73452f4eb914a88142","observation_id":"67c30252-d287-40e5-a3d5-05df6742d4a0","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2512.04329","last_updated":"2026-05-16T14:54:11Z","snapshot_observed_at":"2026-08-05T16:56:16.382896Z","submitted_at":"2025-12-03T23:28:30Z","title":"A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-21T17:51:20.393473Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2512.04329"},"observation_digest":"sha256:8499a2e26e1048406643c4001cfa5057ab351ea6d71809d8dece563c4a9b3bcc","observation_id":"115089eb-08cb-418e-b5d3-1940e8c58662","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2512.24120","last_updated":"2026-04-16T12:18:23Z","snapshot_observed_at":"2026-07-06T22:40:23.205898Z","submitted_at":"2025-12-30T10:01:55Z","title":"Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-16T19:08:18.706760Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2512.24120"},"observation_digest":"sha256:2348d2ad68486feeb1ebf9d684433d8f064a6b0fd4965bf4759d368dd0df8e69","observation_id":"14bc9d48-bbf4-4b0f-ad74-12af206b53d3","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2601.08517","last_updated":"2026-05-04T13:22:35Z","snapshot_observed_at":"2026-08-02T18:38:11.484527Z","submitted_at":"2026-01-13T13:00:30Z","title":"Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T14:34:24.849584Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2601.08517"},"observation_digest":"sha256:ecb146520b19481c9460d8ce26324b516db656da21f08bd40f64b6d602f85064","observation_id":"8a903e6b-9be3-4557-a71c-3219dbfc25dd","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2604.17007","last_updated":"2026-04-18T14:37:23Z","snapshot_observed_at":"2026-08-02T22:37:42.570821Z","submitted_at":"2026-04-18T14:37:23Z","title":"MobileAgeNet: Lightweight Facial Age Estimation for Mobile Deployment","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T07:33:25.731730Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2604.17007"},"observation_digest":"sha256:82ac833402ecc623ccd91a78058adf7f72ad0e2e7caeefc8ab5f14035a465aa3","observation_id":"63fcb8a1-8f4f-41cc-9acb-f1290134ce80","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2605.03680","last_updated":"2026-05-05T12:19:30Z","snapshot_observed_at":"2026-08-01T04:13:44.068024Z","submitted_at":"2026-05-05T12:19:30Z","title":"Real Image Denoising with Knowledge Distillation for High-Performance Mobile NPUs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-07T17:58:24.076954Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2605.03680"},"observation_digest":"sha256:19ece966b546a6f9f465869163b88a840f6f51d2dadce8c461f1b50481f49be3","observation_id":"6b7434b7-b6d1-430c-a76a-ce5120221cd6","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2605.03686","last_updated":"2026-05-06T11:06:46Z","snapshot_observed_at":"2026-07-06T23:16:34.988490Z","submitted_at":"2026-05-05T12:30:19Z","title":"From Code to Prediction: Fine-Tuning LLMs for Neural Network Performance Classification in NNGPT","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-07T16:55:58.829624Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2605.03686"},"observation_digest":"sha256:f58afad43475acb316f3d774c7956df88bc102771f646b201e5bb8bad65e8302","observation_id":"fea34339-4ca5-47a8-8b1d-b5f06f98d3a8","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2605.03686","last_updated":"2026-05-06T11:06:46Z","snapshot_observed_at":"2026-07-06T23:16:34.988490Z","submitted_at":"2026-05-05T12:30:19Z","title":"From Code to Prediction: Fine-Tuning LLMs for Neural Network Performance Classification in NNGPT","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T18:27:02.838489Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2605.03686"},"observation_digest":"sha256:b3b496f044fe9a1d2bbdfa967fdffc2685aac9da7d7a216cc363f658e0bad483","observation_id":"99913c3c-9c48-4633-83b2-4168145fbf54","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2605.04903","last_updated":"2026-05-06T13:32:05Z","snapshot_observed_at":"2026-07-06T23:17:38.226365Z","submitted_at":"2026-05-06T13:32:05Z","title":"Delta-Based Neural Architecture Search: LLM Fine-Tuning via Code Diffs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T16:28:40.262681Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2605.04903"},"observation_digest":"sha256:f45e50266fd0b5d3b35e1e8bd9dee3dc2e354d3ebe602c0291f5e407f0c41e98","observation_id":"758b29f4-e5d8-49e3-9fb4-f65750a94e93","resolution":{"observed_at":"2026-06-02T03:03:59.122865Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2605.30103","last_updated":"2026-05-28T15:45:19Z","snapshot_observed_at":"2026-07-06T23:39:24.682426Z","submitted_at":"2026-05-28T15:45:19Z","title":"Convergence Theory for Iterative LLM-Based Neural Architecture Search: A Parametric Cross-Entropy Framework with Closed-Form Proxy Reliability","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T08:56:19.606663Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2605.30103"},"observation_digest":"sha256:0602ff66ec346955aa8f00769e8995be49ca62d94af8a7774f9f06edaffaef0a","observation_id":"85c77cb4-05f6-44ea-9316-481be35496cf","resolution":{"observed_at":"2026-06-29T09:03:16.064392Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2606.20933","last_updated":"2026-06-18T20:51:42Z","snapshot_observed_at":"2026-08-01T19:51:37.032386Z","submitted_at":"2026-06-18T20:51:42Z","title":"Towards Robust Training in NNGPT AutoML Pipeline: A Loss-Optimizer Pairing Selection Study","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-26T17:46:06.322543Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2606.20933"},"observation_digest":"sha256:5b12bf0e254abb813b271acb0595e5a8262371d07dbe0b18475bde67527de1f2","observation_id":"8b3f57cc-edec-4914-bc08-065ed7750d21","resolution":{"observed_at":"2026-07-04T03:39:30.570610Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2606.23739","last_updated":"2026-06-21T13:43:27Z","snapshot_observed_at":"2026-07-06T23:58:25.400508Z","submitted_at":"2026-06-21T13:43:27Z","title":"Systematic Exploration of 4-Expert Heterogeneous Mixture-of-Experts via Automated Pipeline Search","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-26T10:43:32.533041Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2606.23739"},"observation_digest":"sha256:71d86a02bf877faa0b273700081d911334148ccc5d84e55922236826cf262711","observation_id":"de912c23-f643-43b2-bcca-bc35ead57b21","resolution":{"observed_at":"2026-07-04T08:59:42.666659Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2607.05704","last_updated":"2026-07-06T23:59:18Z","snapshot_observed_at":"2026-08-04T22:52:25.138554Z","submitted_at":"2026-07-06T23:59:18Z","title":"LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T03:26:40.346199Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2607.05704"},"observation_digest":"sha256:8a821da343f98131b26c5174732a5306c786b66a03deed95e1e6bee80849cf53","observation_id":"f6a41cae-0a01-4dc4-8070-76deda681eec","resolution":{"observed_at":"2026-07-11T03:27:45.300357Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":"2504.10552","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-11T03:27:45.276446Z","title":"Lemur neural net- work dataset: Towards seamless automl","venue":"cs.LG","work_id":"bd3aeaf0-a705-4f74-a281-43ec472e863e","year":2025},"citing_paper":{"arxiv_id":"2607.08511","last_updated":"2026-07-09T14:06:39Z","snapshot_observed_at":"2026-08-01T17:20:32.504768Z","submitted_at":"2026-07-09T14:06:39Z","title":"Systematic Evaluation of Learning Rate Scheduling Strategies Across Heterogeneous Architectures","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-10T06:13:42.239715Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2607.08511"},"observation_digest":"sha256:42a312c3d465f0add6cf46018f3a255237e516d2207ccf184d7118abbf9a142e","observation_id":"7e0bc5e2-f620-47c3-b4c9-e0df0e144299","resolution":{"observed_at":"2026-07-10T06:16:51.284448Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-07-14T04:33:33.238860Z","title":"LEMUR neu- ral network dataset: Towards seamless AutoML,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.11591","last_updated":"2026-07-13T14:14:30Z","snapshot_observed_at":"2026-08-03T04:03:27.187479Z","submitted_at":"2026-07-13T14:14:30Z","title":"Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-14T04:33:33.238860Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2607.11591"},"observation_digest":"sha256:0553c7fdb556b30ad43f0d9dd99e74ab87d8d67bc8e62efd9555abb42fa304dc","observation_id":"95895342-3ef8-44d3-a4af-2fb08b3a08ae","resolution":{"observed_at":"2026-07-14T04:33:33.238860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.10552","snapshot_observed_at":"2026-08-02T08:13:03.645303Z","title":"arXiv preprint arXiv:2504.10552 (2025),https://arxiv.org/abs/2504.10552","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20516","last_updated":"2026-07-07T22:31:53Z","snapshot_observed_at":"2026-08-04T19:10:00.882891Z","submitted_at":"2026-07-07T22:31:53Z","title":"Scaling Closed-Loop Feature Channel Configuration with LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T08:13:03.645303Z"},"links":{"cited_paper":"/paper/2504.10552","citing_paper":"/paper/2607.20516"},"observation_digest":"sha256:0a6dfa06a142d6aa575629f4ad6f61bf5be584c7612b4bd52584dcbd3d1be072","observation_id":"37142e7f-1ad4-4df4-b52e-ad4176ffca9e","resolution":{"observed_at":"2026-08-02T08:13:03.645303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.10552/citation-record","integrity":"/paper/2504.10552/integrity","json":"/paper/2504.10552/citation-record.json","paper":"/paper/2504.10552"},"outbound":[],"paper":{"arxiv_id":"2504.10552","last_updated":"2025-09-24T10:29:39Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T21:09:17.062196Z","submitted_at":"2025-04-14T09:08:00Z","title":"LEMUR Neural Network Dataset: Towards Seamless AutoML"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2504.10552."}