{"as_of":"2026-08-08T19:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:740b52c15911733b225fd9b7f063c3f64a4c4a6b2f28885235eaea6eb08f178f","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:11:43.740248Z","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":"2026-07-03T17:58:47.495094Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":"2106.03843","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-07-03T17:58:47.495094Z","title":"Equivariant graph neural networks for 3d macromolecular structure","venue":null,"work_id":"80ea6253-cca8-4dfb-889b-ae4e1c91b3f0","year":2021},"citing_paper":{"arxiv_id":"2410.19471","last_updated":"2024-10-25T11:04:02Z","snapshot_observed_at":"2026-08-02T22:41:48.124142Z","submitted_at":"2024-10-25T11:04:02Z","title":"Improving Inverse Folding for Peptide Design with Diversity-regularized Direct Preference Optimization","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-23T19:03:53.675107Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2410.19471"},"observation_digest":"sha256:e35d08c7e760a710a0eeec37198dcf6cfaf4c07000a5ef745ab3f7a7bc21b511","observation_id":"a86d1cb7-d3b6-4032-b413-98219e3064f9","resolution":{"observed_at":"2026-05-23T19:05:46.886162Z","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":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-08-07T13:11:43.740248Z","title":"N., and Dror, R","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.22560","last_updated":"2025-05-28T16:38:35Z","snapshot_observed_at":"2026-08-08T06:04:28.958281Z","submitted_at":"2025-05-28T16:38:35Z","title":"Geometric Hyena Networks for Large-scale Equivariant Learning","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T13:11:43.740248Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2505.22560"},"observation_digest":"sha256:798ef94d465630d7e8866bc32034b8d5dc96d50c64ee3237490e15b12720d59c","observation_id":"d4665ed2-2d38-4cb0-91b6-c37db6c9ffdb","resolution":{"observed_at":"2026-08-07T13:11:43.740248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":"2106.03843","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-07-03T17:58:47.495094Z","title":"Equivariant graph neural networks for 3d macromolecular structure","venue":null,"work_id":"80ea6253-cca8-4dfb-889b-ae4e1c91b3f0","year":2021},"citing_paper":{"arxiv_id":"2604.23134","last_updated":"2026-04-25T04:25:50Z","snapshot_observed_at":"2026-07-06T23:09:23.591544Z","submitted_at":"2026-04-25T04:25:50Z","title":"h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T08:39:12.310362Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2604.23134"},"observation_digest":"sha256:083da00c4f0884db4db7bea02f30e411441bdb0c84c1023f469f4411781220c0","observation_id":"f20d2d46-0073-4b50-a967-71fa7b3293e7","resolution":{"observed_at":"2026-05-11T20:31:14.409682Z","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":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":"2106.03843","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-07-03T17:58:47.495094Z","title":"Equivariant graph neural networks for 3d macromolecular structure","venue":null,"work_id":"80ea6253-cca8-4dfb-889b-ae4e1c91b3f0","year":2021},"citing_paper":{"arxiv_id":"2605.31498","last_updated":"2026-06-08T17:55:28Z","snapshot_observed_at":"2026-07-06T23:40:42.277618Z","submitted_at":"2026-05-29T16:20:59Z","title":"Scalable Inference-Time Annealing with Surrogate Likelihood Estimators","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-06-28T22:54:55.415927Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2605.31498"},"observation_digest":"sha256:d98b8b2e3024fd1572c6f7997275f254f7f4ae27c65f100be38164cc54e1bc72","observation_id":"82b0f408-6f58-4a59-94d2-9ccc647e6e5d","resolution":{"observed_at":"2026-07-01T19:16:00.680972Z","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":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":"2106.03843","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-07-03T17:58:47.495094Z","title":"Equivariant graph neural networks for 3d macromolecular structure","venue":null,"work_id":"80ea6253-cca8-4dfb-889b-ae4e1c91b3f0","year":2021},"citing_paper":{"arxiv_id":"2606.11243","last_updated":"2026-06-03T09:11:28Z","snapshot_observed_at":"2026-08-08T13:48:59.651448Z","submitted_at":"2026-06-03T09:11:28Z","title":"ProHiFlo: Hierarchical Flow Matching with Functional Guidance for De Novo Protein Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-28T07:11:28.600100Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2606.11243"},"observation_digest":"sha256:2d7efd02c4c165416dfbd9122295d4e94503abc1b75be1aac05e85a46e80e60a","observation_id":"69c95747-edd5-48c6-a5e0-20a1dcc56df9","resolution":{"observed_at":"2026-07-02T07:06:44.191328Z","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":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":"2106.03843","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-07-03T17:58:47.495094Z","title":"Equivariant graph neural networks for 3d macromolecular structure","venue":null,"work_id":"80ea6253-cca8-4dfb-889b-ae4e1c91b3f0","year":2021},"citing_paper":{"arxiv_id":"2606.15495","last_updated":"2026-06-22T11:47:50Z","snapshot_observed_at":"2026-08-07T12:04:41.144948Z","submitted_at":"2026-06-13T22:44:06Z","title":"Contrastive learning of dynamical representations for enhanced molecular sampling","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-06-27T03:27:26.575957Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2606.15495"},"observation_digest":"sha256:3e765bddb698b80c8d903d836090bae4db63df20086265f4c3aea9e53e905b40","observation_id":"c4f00fc1-f37b-4125-b95e-641c23ff79cf","resolution":{"observed_at":"2026-07-03T17:58:47.496398Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2106.03843","last_updated":"2021-07-13T12:42:27Z","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.03843","snapshot_observed_at":"2026-08-02T00:14:29.289989Z","title":"arXiv (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.15101","last_updated":"2026-07-16T15:13:03Z","snapshot_observed_at":"2026-08-06T05:39:12.283450Z","submitted_at":"2026-07-16T15:13:03Z","title":"Accelerated descriptor-free path sampling for protein-ligand binding kinetics","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T00:14:29.289989Z"},"links":{"cited_paper":"/paper/2106.03843","citing_paper":"/paper/2607.15101"},"observation_digest":"sha256:8934e68718be56fcbfa2fc873d18333247a0067f791e2162806a25323f5a2815","observation_id":"527f4b0b-23f6-4321-b0d7-11713ad40568","resolution":{"observed_at":"2026-08-02T00:14:29.289989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2106.03843/citation-record","integrity":"/paper/2106.03843/integrity","json":"/paper/2106.03843/citation-record.json","paper":"/paper/2106.03843"},"outbound":[],"paper":{"arxiv_id":"2106.03843","last_updated":"2021-07-13T12:42:27Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T11:16:49.764856Z","submitted_at":"2021-06-07T17:57:04Z","title":"Equivariant Graph Neural Networks for 3D Macromolecular Structure"},"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 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2106.03843."}