{"as_of":"2026-08-10T19:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4335cbeb9e6c0dd481783768e7c617e8dc5bc794172240d1c949f80a9dea0f2a","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T17:36:27.834749Z","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":"2026-08-07T15:27:24.809687Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.23822","last_updated":"2024-10-31T11:07:26Z","snapshot_observed_at":"2026-07-06T19:42:47.238254Z","submitted_at":"2024-10-31T11:07:26Z","title":"Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23822","snapshot_observed_at":"2026-08-09T17:36:27.834749Z","title":"CoRR abs/2410.23822 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00832","last_updated":"2025-02-02T16:05:23Z","snapshot_observed_at":"2026-08-10T08:18:24.087989Z","submitted_at":"2025-02-02T16:05:23Z","title":"Generalization of Medical Large Language Models through Cross-Domain Weak Supervision","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T17:36:27.834749Z"},"links":{"cited_paper":"/paper/2410.23822","citing_paper":"/paper/2502.00832"},"observation_digest":"sha256:fcfb47c7f332fe2ca998058883eee5051e180941dda654101431293cc2212c2e","observation_id":"c04f979b-5d03-4491-9b1e-f93dd01b8f6b","resolution":{"observed_at":"2026-08-09T17:36:27.834749Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23822","last_updated":"2024-10-31T11:07:26Z","snapshot_observed_at":"2026-07-06T19:42:47.238254Z","submitted_at":"2024-10-31T11:07:26Z","title":"Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23822","snapshot_observed_at":"2026-08-08T17:26:28.762817Z","title":"Parameter-efficient fine-tuning medical multimodal large language models for medical visual grounding.arXiv preprint arXiv:2410.23822, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05928","last_updated":"2025-07-11T04:08:20Z","snapshot_observed_at":"2026-08-10T08:06:05.636111Z","submitted_at":"2025-02-09T15:08:10Z","title":"ClinKD: Cross-Modal Clinical Knowledge Distiller For Multi-Task Medical Images","version":4},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:28.762817Z"},"links":{"cited_paper":"/paper/2410.23822","citing_paper":"/paper/2502.05928"},"observation_digest":"sha256:ed79ceb930e55c6d88a1e80675d00fc0737b0a9dd8b54e4a17fee424ca08a089","observation_id":"d4c6f41c-3374-47b6-8195-7c141732ab98","resolution":{"observed_at":"2026-08-08T17:26:28.762817Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23822","last_updated":"2024-10-31T11:07:26Z","snapshot_observed_at":"2026-07-06T19:42:47.238254Z","submitted_at":"2024-10-31T11:07:26Z","title":"Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding","version":1},"cited_work":{"arxiv_id":"2410.23822","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.23822","snapshot_observed_at":"2026-08-07T15:27:24.809687Z","title":"Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding","venue":"cs.CV","work_id":"c9745967-f036-4f03-a210-68013516a230","year":2024},"citing_paper":{"arxiv_id":"2505.15123","last_updated":"2025-08-24T14:40:35Z","snapshot_observed_at":"2026-08-09T16:58:46.218963Z","submitted_at":"2025-05-21T05:16:45Z","title":"Seeing the Trees for the Forest: Rethinking Weakly-Supervised Medical Visual Grounding","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:27:23.081062Z"},"links":{"cited_paper":"/paper/2410.23822","citing_paper":"/paper/2505.15123"},"observation_digest":"sha256:fac19fea9a12d20fcd4d291312ff57f81b77cc272f6e2fa794e874a89ef89312","observation_id":"5a02727f-df45-4f4e-bc18-5e82890a4c5b","resolution":{"observed_at":"2026-08-07T15:27:24.815273Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.23822/citation-record","integrity":"/paper/2410.23822/integrity","json":"/paper/2410.23822/citation-record.json","paper":"/paper/2410.23822"},"outbound":[],"paper":{"arxiv_id":"2410.23822","last_updated":"2024-10-31T11:07:26Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T19:42:47.238254Z","submitted_at":"2024-10-31T11:07:26Z","title":"Parameter-Efficient Fine-Tuning Medical Multimodal Large Language Models for Medical Visual Grounding"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.23822."}