{"as_of":"2026-08-13T21:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9da17d4818661889c21cc7c23dee894b21d98a8b6a8c174dea7f16c8aeb19377","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:57:15.510819Z","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":"2026-08-12T11:56:24.138208Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.06297","last_updated":"2024-07-20T12:56:00Z","snapshot_observed_at":"2026-08-13T05:05:13.663882Z","submitted_at":"2023-12-11T10:59:23Z","title":"Progressive Multi-Modality Learning for Inverse Protein Folding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06297","snapshot_observed_at":"2026-08-12T11:57:15.510819Z","title":"Mmdesign: Multi- modality transfer learning for generative protein design","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.17795","last_updated":"2024-11-26T17:51:33Z","snapshot_observed_at":"2026-08-13T19:03:27.523721Z","submitted_at":"2024-11-26T17:51:33Z","title":"Pan-protein Design Learning Enables Task-adaptive Generalization for Low-resource Enzyme Design","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T11:57:15.510819Z"},"links":{"cited_paper":"/paper/2312.06297","citing_paper":"/paper/2411.17795"},"observation_digest":"sha256:ac8d0d2f5560ff0dab1f286dfa7fe675930af5f8273ab0ee57d5cb2ba4f74ce3","observation_id":"31351082-c91f-4247-a326-6ec4fed531dc","resolution":{"observed_at":"2026-08-12T11:57:15.510819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06297","last_updated":"2024-07-20T12:56:00Z","snapshot_observed_at":"2026-08-13T05:05:13.663882Z","submitted_at":"2023-12-11T10:59:23Z","title":"Progressive Multi-Modality Learning for Inverse Protein Folding","version":2},"cited_work":{"arxiv_id":"2312.06297","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.06297","snapshot_observed_at":"2026-08-12T11:56:24.138208Z","title":"Progressive Multi-Modality Learning for Inverse Protein Folding","venue":"cs.AI","work_id":"164ee560-adf2-4c5f-8d0f-164079a6fff5","year":2023},"citing_paper":{"arxiv_id":"2411.17798","last_updated":"2024-11-26T18:06:42Z","snapshot_observed_at":"2026-08-13T19:45:32.884753Z","submitted_at":"2024-11-26T18:06:42Z","title":"DapPep: Domain Adaptive Peptide-agnostic Learning for Universal T-cell Receptor-antigen Binding Affinity Prediction","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T11:56:24.078272Z"},"links":{"cited_paper":"/paper/2312.06297","citing_paper":"/paper/2411.17798"},"observation_digest":"sha256:c80f7f2de075a99d4e42c7d026ddd5ae6688db819cefcf244b8e6c3b31f67cad","observation_id":"f3ad3a70-2f65-499c-9bab-fce511392755","resolution":{"observed_at":"2026-08-12T11:56:24.141134Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2312.06297/citation-record","integrity":"/paper/2312.06297/integrity","json":"/paper/2312.06297/citation-record.json","paper":"/paper/2312.06297"},"outbound":[],"paper":{"arxiv_id":"2312.06297","last_updated":"2024-07-20T12:56:00Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-13T05:05:13.663882Z","submitted_at":"2023-12-11T10:59:23Z","title":"Progressive Multi-Modality Learning for Inverse Protein Folding"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.06297."}