{"as_of":"2026-08-23T10:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e5ff83b743ee6a843c8e3a1ba2b36ec15bf0836643fe59e7b2af3f0aff6e5621","coverage":[{"denominator":35,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":35,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:23:52.163084Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2506.15687/citation-record","integrity":"/paper/2506.15687/integrity","json":"/paper/2506.15687/citation-record.json","paper":"/paper/2506.15687"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-17T03:25:04.404839Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-07T14:23:49.081662Z","title":"Abdin, J","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.081662Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:07da7b627d328dcaba62f118504ad3effb89fa1b69fe26454792cd4ea67596e0","observation_id":"aa0a0f37-dc12-48ef-879e-705934c81fe6","resolution":{"observed_at":"2026-08-07T14:23:49.081662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:56.287932Z","title":"Ainsworth and J","venue":null,"work_id":"2bb10a0b-64d8-44db-9674-9a3515235f16","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.147477Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:057be3b146bd68bc121cf8f105f99a63744d7d97c1f4f30f203b84d31de9e202","observation_id":"597cf95b-1a92-4018-b553-e37d6aecc283","resolution":{"observed_at":"2026-08-07T14:23:56.343562Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:56.087501Z","title":"empirical interpolation","venue":null,"work_id":"f521c967-f470-4e89-bc93-2049e44c466a","year":2004},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.254956Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:a4e37e8d6f9e590f8d4c0d2de96ea69906f93738fec34e377e3508f90b829c3b","observation_id":"dc075f14-fcbe-47b3-a029-357fa0c1a66a","resolution":{"observed_at":"2026-08-07T14:23:56.180711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:55.890377Z","title":"Binev, A","venue":null,"work_id":"e29a713b-296d-4215-9544-c37c7c710daf","year":2011},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.409689Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:1a2359043c8cb34dafe6d9a7964f93149616d5d0483b812225ba0b70449964dc","observation_id":"3960ae8e-2983-48d6-81a7-1cfdf2e87071","resolution":{"observed_at":"2026-08-07T14:23:55.963611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:55.738427Z","title":"Brown, B","venue":null,"work_id":"438d8366-bec5-43f0-8c27-5ef8739ff4dc","year":1901},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.523084Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:d8955495a3e61b20fb05435d0563aa80cddb9314c0dd1f142a5184faaa4747f3","observation_id":"5eba236a-7357-4e39-96c2-a1f38aad9569","resolution":{"observed_at":"2026-08-07T14:23:55.821521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:55.530944Z","title":null,"venue":null,"work_id":"d4d895de-cc0a-4210-950a-1bf39fc18dfe","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.658296Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:0fc00c2d4083fa8cb7cfe48f5c616c797c351ff08022aae5004725eb163a4e40","observation_id":"c5378c6d-d94e-4785-9aac-155fa8fef609","resolution":{"observed_at":"2026-08-07T14:23:55.636726Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:55.316458Z","title":null,"venue":null,"work_id":"37e2396c-2e27-4cbb-91b6-821c771d6cf9","year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.769373Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:af4ff32f212ec6b196db62a8a82ad0356255ea066fd6fbc792c015c5d4711292","observation_id":"04875530-6192-4076-b0ea-870617ebd008","resolution":{"observed_at":"2026-08-07T14:23:55.407259Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:55.167916Z","title":"Chen and S","venue":null,"work_id":"30c5c7ae-b9c6-48c3-aa6e-76c1e9469fb7","year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.887840Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:09f93c75e493361ce55a032a72bb4a0473fbc5e36d12a9c2db16287ecedc7a89","observation_id":"79f1a0c7-961b-44de-8d20-4ab45863f735","resolution":{"observed_at":"2026-08-07T14:23:55.256131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:49.991049Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:49.991049Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:56f8167aec53defff305ebceba59e71b4a479d2ffea69d8dfc026874180b119f","observation_id":"0a3a67b7-82c1-4999-a1b6-63be492aa758","resolution":{"observed_at":"2026-08-07T14:23:49.991049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:50.143914Z","title":"DeVore, B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.143914Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:57e19a158c388045da0b37c81869834d8a7a63c71971e5aafea436e65303031b","observation_id":"9f5422c4-e6da-49b4-8a8f-fa76c0a9e555","resolution":{"observed_at":"2026-08-07T14:23:50.143914Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:50.259467Z","title":"Dhariwal and A","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.259467Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:9585746e0384893859b975f6b849066640ab9331df606542b9ee8cefd7089f8c","observation_id":"daea3657-79df-40e2-b480-597f0613312a","resolution":{"observed_at":"2026-08-07T14:23:50.259467Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.969331Z","title":"Fresca, L","venue":null,"work_id":"ad9f7034-957b-4a7e-9604-5f583c3b362b","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.390435Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:d21ef02880556790dc26c15efbab1d4d5b7f8c8066c68f1cfeabed6dc6922a7d","observation_id":"597727d8-8b32-426d-b980-4c1dd6f32a85","resolution":{"observed_at":"2026-08-07T14:23:55.037032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.778225Z","title":"Fresca and A","venue":null,"work_id":"cf5e30a1-e45e-4404-8e57-d9dea83a94d1","year":2022},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.480952Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:a93d10fc757b0ddd33e778d024c24162d4b4363786e0515369c4f5203822d62c","observation_id":"fcbe22a0-a706-4deb-bf7e-8753d53d6515","resolution":{"observed_at":"2026-08-07T14:23:54.869353Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.596749Z","title":null,"venue":null,"work_id":"9769dc79-5d95-4028-a8d5-42352f92f2ca","year":2023},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.580298Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:cd142878a993113765951fa34a803517b1c33d0cf8131180b07311a7b9f1eef8","observation_id":"47e06d6b-0f08-4c7b-ab8b-07eb6c5daa33","resolution":{"observed_at":"2026-08-07T14:23:54.674469Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.457852Z","title":null,"venue":null,"work_id":"0f5c2a22-1675-48a7-a282-d188c2367bdb","year":2018},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.743363Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:5481d0a0932effa6c367849093d8f63c9c2bd61f38934958d0eaf7ec4e32727a","observation_id":"bb03a5a6-6f94-48a0-925c-a110c3a12e37","resolution":{"observed_at":"2026-08-07T14:23:54.528988Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:50.864262Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.864262Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:824e315264842e2fd5e2d683c473f7f460176607e7ae1d73aeac4b27550407e0","observation_id":"1594860b-f4cf-4b93-b7ff-7bf5213f3435","resolution":{"observed_at":"2026-08-07T14:23:50.864262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.296909Z","title":null,"venue":null,"work_id":"10cd7be9-7242-49c1-b6e5-c8beede22977","year":2016},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:50.973505Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:d969182b0e7a15e6bdfcd790228626b59bff28bc34b325bb266a9c8397b8d3d2","observation_id":"6fc73fef-8485-4c19-bdc5-bf3be3df0d2e","resolution":{"observed_at":"2026-08-07T14:23:54.357277Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:54.103835Z","title":null,"venue":null,"work_id":"cfb15c8d-6f0a-4224-a4a5-e2162acf0a74","year":2018},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.101644Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:c35b7812127752538eddc359f5e278495ad01c78749d37c834305be2b99aa788","observation_id":"402bd7e0-dc14-4485-9d0b-9568b3e3e3ab","resolution":{"observed_at":"2026-08-07T14:23:54.183012Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.945395Z","title":null,"venue":null,"work_id":"a63d8df2-2d53-4026-bc40-9b580db7313c","year":2023},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.135765Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:81df601c216685cc641826f53b18a5b95f7eff69bd3c738be44b3e8fd2ef5c9a","observation_id":"c213dac7-e2bd-4439-82f2-d8536cfda6bc","resolution":{"observed_at":"2026-08-07T14:23:54.026550Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.788904Z","title":"Huang, Z","venue":null,"work_id":"ab8d9a35-e40c-4e06-8c11-1b567fbe1d7c","year":2022},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.138848Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:fa44d510d40c3cb9279f52eeb4ca805caac4129ffadcb87bfec55b45d847f681","observation_id":"64a946c6-0c58-4aa2-a786-0e12016675dd","resolution":{"observed_at":"2026-08-07T14:23:53.855664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.638108Z","title":null,"venue":null,"work_id":"7f163681-9596-4819-80ef-f67d969e71ca","year":2025},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.207558Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:439eaac85c9405be9fafcc9c7ddc32f9480ddf716c9f0808428be180b7b4c74c","observation_id":"0d61d01d-23a0-4729-9d23-0b28dd49df71","resolution":{"observed_at":"2026-08-07T14:23:53.702115Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.497896Z","title":null,"venue":null,"work_id":"66d6a08f-160b-493c-b9eb-86d33024fc5f","year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.266546Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:f540a2da3c47766b3fdec0c55e1f2c0aa2b40368d01958510d1b13824bf700fe","observation_id":"8c78c47d-199f-49d5-862e-0ec70dd45f5d","resolution":{"observed_at":"2026-08-07T14:23:53.538748Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.317903Z","title":null,"venue":null,"work_id":"ca5a7c1e-4cd5-41c6-b5d8-b15817d1bf73","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.363618Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:b1b1b7a55d36caac7ee4f2bac8136e5d90f073823804248986a9e4fa1c3e16fd","observation_id":"10819d8b-a29d-43c0-a809-4ce105a845df","resolution":{"observed_at":"2026-08-07T14:23:53.399317Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.174990Z","title":null,"venue":null,"work_id":"7d0413de-e455-4f82-8c55-c9dd58f72abb","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.422572Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:36b2e44e90b97a00e2092f9a3630e68b5696f773550a80bea042dee09264beca","observation_id":"0a4d4b55-f8b8-459f-b737-f6538eb39758","resolution":{"observed_at":"2026-08-07T14:23:53.238534Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02994","last_updated":"2024-01-23T04:43:56Z","snapshot_observed_at":"2026-08-22T07:47:22.098897Z","submitted_at":"2024-01-04T07:45:49Z","title":"Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02994","snapshot_observed_at":"2026-08-07T14:23:51.484850Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.484850Z"},"links":{"cited_paper":"/paper/2401.02994","citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:f7d4c8a0bd08b227419fab568686fd268116a95293fc7f9d1b22bd661522c359","observation_id":"8cdf2c60-a3d8-453f-b53d-490e94c854f8","resolution":{"observed_at":"2026-08-07T14:23:51.484850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.15790","last_updated":"2025-02-26T06:34:55Z","snapshot_observed_at":"2026-08-19T23:45:09.602398Z","submitted_at":"2024-09-24T06:36:56Z","title":"Small Language Models: Survey, Measurements, and Insights","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.15790","snapshot_observed_at":"2026-08-07T14:23:51.551308Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.551308Z"},"links":{"cited_paper":"/paper/2409.15790","citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:1886c6e3951c5a21773b9c4ce1c6812cd1c43cd4e7ca2e5c5b9e7864e4669df4","observation_id":"78df61d9-714a-43f4-b9da-f300032c2220","resolution":{"observed_at":"2026-08-07T14:23:51.551308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:53.007269Z","title":"Maday and O","venue":null,"work_id":"972c9ec4-32a2-4573-893c-7fbc2a7e8871","year":2013},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.594722Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:10399b1276a6754f32fced5852e9f58dcb0bca03399cb1ce82604d6c18a14fbb","observation_id":"2310294c-a424-4a2c-975b-a7163c3ac4a8","resolution":{"observed_at":"2026-08-07T14:23:53.063062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:52.881038Z","title":"Maday, O","venue":null,"work_id":"5045902e-aca2-4013-afe1-f3c5574221dc","year":2015},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.672441Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:e309c706c1638a4effb336a51c3125a24582993c1445948ef8a8b876cc80d8f2","observation_id":"9dc401b1-e27b-4165-b2ab-fbffa8b6202e","resolution":{"observed_at":"2026-08-07T14:23:52.932066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:52.724619Z","title":null,"venue":null,"work_id":"91bbea34-927a-4c47-a98f-cb74b3d188d8","year":2023},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.733504Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:d2b1d226a5cec1ea9734d9f0f3724b46885ede7cf308773f8833ec45103ac89a","observation_id":"b69cb480-25b5-4ff8-a86d-450799b6f4ad","resolution":{"observed_at":"2026-08-07T14:23:52.803974Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.13361","last_updated":"2023-01-19T22:20:49Z","snapshot_observed_at":"2026-08-19T13:48:36.157536Z","submitted_at":"2021-10-26T02:29:10Z","title":"A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs","version":2},"cited_work":{"arxiv_id":"2110.13361","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.13361","snapshot_observed_at":"2026-08-07T14:23:52.281166Z","title":"A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs","venue":"physics.comp-ph","work_id":"fca999f1-f0b2-4a7f-b769-770a3dbcee14","year":2021},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.825707Z"},"links":{"cited_paper":"/paper/2110.13361","citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:25c40f0dfb96d359dd09f2becd08b69a2c9943cac869a8ad2d7861d9541fa018","observation_id":"93b48186-03d8-4b4a-bb0a-e1fffc133570","resolution":{"observed_at":"2026-08-07T14:23:52.360309Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:51.883280Z","title":"Quarteroni, A","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.883280Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:13489a62e217a85cb541192d9d09f75a975cbea90d6aef08ec0a4299281b9418","observation_id":"615bcce8-d54e-4f47-b481-cbdcc46e4e37","resolution":{"observed_at":"2026-08-07T14:23:51.883280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:51.959582Z","title":"Raissi, P","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:51.959582Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:e8486d76529c07e0f2eb842c68ba8f8e447354693bf9c589f3261be46d6ddf16","observation_id":"f8904a60-616d-4afb-bdc2-7fdc23c53dcf","resolution":{"observed_at":"2026-08-07T14:23:51.959582Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07118","last_updated":"2021-04-12T08:16:59Z","snapshot_observed_at":"2026-08-14T09:17:46.140640Z","submitted_at":"2020-09-15T14:18:53Z","title":"It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07118","snapshot_observed_at":"2026-08-07T14:23:52.026903Z","title":"Schick and H","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:52.026903Z"},"links":{"cited_paper":"/paper/2009.07118","citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:afb2e4b3ddafe2cf66bce7ec2295df28d35273b2d62b8cb9e82847e5b4e0c9c6","observation_id":"64bd7638-c8f8-4413-b914-d80fbfff1749","resolution":{"observed_at":"2026-08-07T14:23:52.026903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:52.566887Z","title":null,"venue":null,"work_id":"55f4d81b-ea67-4ef3-97ac-e735ab78d0cd","year":2023},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:52.068918Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:77092e7e3adb9814b39cce6bb901dcad224c1848bcc0568706c6db7388b4655d","observation_id":"8adfe50e-3c5d-48eb-8e7c-810044ec20bf","resolution":{"observed_at":"2026-08-07T14:23:52.648707Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T14:23:52.455408Z","title":"Vaswani, N","venue":null,"work_id":"60e327a9-c87f-4e5c-83d7-928460b1083a","year":2017},"citing_paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:52.163084Z"},"links":{"citing_paper":"/paper/2506.15687"},"observation_digest":"sha256:d412349f03c1598e07a4fa3356d366843ea6c13cb1e6ffdbb72e00d450becad4","observation_id":"ecd579a5-cd5b-456a-a1cd-8abb737115fa","resolution":{"observed_at":"2026-08-07T14:23:52.517077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.15687","last_updated":"2025-05-25T14:03:10Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T00:58:28.099257Z","submitted_at":"2025-05-25T14:03:10Z","title":"S$^2$GPT-PINNs: Sparse and Small models for PDEs"},"reference_resolution":{"displayed":35,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":23,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":35},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.15687."}