{"as_of":"2026-08-09T04:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f56b694edbda1ca20ca316ef5b14efc1e391178cbb6b45b0f08a42b93c0ab77d","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:59:06.336251Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T07:49:39.231730Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17015","snapshot_observed_at":"2026-08-07T04:59:06.336251Z","title":"Wang, Y ., Li, H., Tang, Z., Tao, H., Wang, Y ., Yuan, Z., Chen, Z., Duan, W., and Xu, Y","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09398","last_updated":"2026-06-02T05:25:50Z","snapshot_observed_at":"2026-08-07T04:46:52.068122Z","submitted_at":"2025-06-11T05:04:29Z","title":"Efficient Prediction of SO(3)-Equivariant Hamiltonian Matrices via SO(2) Local Frames","version":4},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T04:59:06.336251Z"},"links":{"cited_paper":"/paper/2401.17015","citing_paper":"/paper/2506.09398"},"observation_digest":"sha256:cb2a6da63f053b981de498c03f9aca666f3ef95a4d8b2da0adb4fe460c785295","observation_id":"b6ca7b83-5a22-4af6-80ab-f997545c3259","resolution":{"observed_at":"2026-08-07T04:59:06.336251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17015","snapshot_observed_at":"2026-08-06T20:06:28.469729Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.03840","last_updated":"2025-07-04T23:53:47Z","snapshot_observed_at":"2026-08-07T06:27:56.670360Z","submitted_at":"2025-07-04T23:53:47Z","title":"Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:06:28.469729Z"},"links":{"cited_paper":"/paper/2401.17015","citing_paper":"/paper/2507.03840"},"observation_digest":"sha256:c5874e481c909eb6ad442bc66e222819d5c9d8a389413bcc0e952488b9335255","observation_id":"b72e7ee4-94b3-4b88-99cf-154c99099d6d","resolution":{"observed_at":"2026-08-06T20:06:28.469729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17015","snapshot_observed_at":"2026-08-05T05:52:52.838159Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.04875","last_updated":"2025-09-05T07:42:32Z","snapshot_observed_at":"2026-08-05T05:52:49.461220Z","submitted_at":"2025-09-05T07:42:32Z","title":"Hot-Ham: an accurate and efficient E(3)-equivariant machine-learning electronic structures calculation framework","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T05:52:52.838159Z"},"links":{"cited_paper":"/paper/2401.17015","citing_paper":"/paper/2509.04875"},"observation_digest":"sha256:439783d3e979409891471089ff22baa17f2aef40c767408f80eab24a84f0d22c","observation_id":"874f3723-9e47-47c0-bff9-53032231ba41","resolution":{"observed_at":"2026-08-05T05:52:52.838159Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer","version":1},"cited_work":{"arxiv_id":"2401.17015","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.17015","snapshot_observed_at":"2026-07-04T07:49:39.231730Z","title":null,"venue":null,"work_id":"2e9cf0ae-46d2-4959-be19-d9323118c80e","year":2024},"citing_paper":{"arxiv_id":"2605.11512","last_updated":"2026-05-12T04:30:17Z","snapshot_observed_at":"2026-07-06T23:23:21.034839Z","submitted_at":"2026-05-12T04:30:17Z","title":"$G^0W^0$ implementation based on the pseudopotential and numerical-atomic-orbital basis-set framework: Algorithms and benchmarks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-13T01:57:43.414502Z"},"links":{"cited_paper":"/paper/2401.17015","citing_paper":"/paper/2605.11512"},"observation_digest":"sha256:2f3899e41b2453b9411d55b4972d0e0928e8292d60b4a5ed745a9caa2951c26c","observation_id":"19f02273-1f89-4114-9926-ad2412b4e709","resolution":{"observed_at":"2026-05-13T02:07:08.856390Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer","version":1},"cited_work":{"arxiv_id":"2401.17015","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.17015","snapshot_observed_at":"2026-07-04T07:49:39.231730Z","title":null,"venue":null,"work_id":"2e9cf0ae-46d2-4959-be19-d9323118c80e","year":2024},"citing_paper":{"arxiv_id":"2606.21251","last_updated":"2026-06-19T09:29:38Z","snapshot_observed_at":"2026-08-08T08:57:43.688341Z","submitted_at":"2026-06-19T09:29:38Z","title":"AI-accelerated metallized $\\sigma$-bonding screening for superconductor discovery","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-26T12:48:40.446650Z"},"links":{"cited_paper":"/paper/2401.17015","citing_paper":"/paper/2606.21251"},"observation_digest":"sha256:64d9cca32a4b9d93514c8a513014ef85a8d789376246743d6a2d8f3e76ecf58e","observation_id":"f80b60fa-7259-4fb9-91a5-8f537b8a8085","resolution":{"observed_at":"2026-07-04T07:49:39.233290Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2401.17015/citation-record","integrity":"/paper/2401.17015/integrity","json":"/paper/2401.17015/citation-record.json","paper":"/paper/2401.17015"},"outbound":[],"paper":{"arxiv_id":"2401.17015","last_updated":"2024-01-30T13:51:28Z","latest_version":1,"primary_category":"physics.comp-ph","snapshot_observed_at":"2026-08-08T09:52:33.425830Z","submitted_at":"2024-01-30T13:51:28Z","title":"DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.17015."}