{"as_of":"2026-08-13T03:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d3b63910f96b7fe14e57b50594e9445a74798ed2f63b1cf8489ec30c97406cc9","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":"2026-08-12T06:34:41.77262+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":"2026-08-12T17:55:20.857605Z","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":"2026-08-11T14:55:48.165436Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-12T17:53:45.762849Z","title":"Deep Learning with HM - VGG: AI Strategies for Multi -modal Image Analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12151","last_updated":"2024-11-19T01:01:56Z","snapshot_observed_at":"2026-08-12T17:49:01.030258Z","submitted_at":"2024-11-19T01:01:56Z","title":"Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T17:53:45.762849Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2411.12151"},"observation_digest":"sha256:470c3d8286a76394028faf2db43da6487c8ff052f4c59d2f41a77a996427caa9","observation_id":"21bbc7e0-2c9d-4473-9d53-fe09ba5dba69","resolution":{"observed_at":"2026-08-12T17:53:45.762849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-12T17:55:20.857605Z","title":"Deep Learning with HM- VGG: AI Strategies for Multi-modal Image Analysis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12157","last_updated":"2024-11-19T01:41:56Z","snapshot_observed_at":"2026-08-12T17:48:50.253006Z","submitted_at":"2024-11-19T01:41:56Z","title":"A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:20.857605Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2411.12157"},"observation_digest":"sha256:2f4cef74069179eaeb9c24c589089f5edb951376cb1a5694a963930e24dbf319","observation_id":"d5c04e35-31bc-4105-a38f-467014e20170","resolution":{"observed_at":"2026-08-12T17:55:20.857605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-12T17:55:18.031207Z","title":"Deep Learning with HM- VGG: AI Strategies for Multi-modal Image Analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.031207Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:7a9bc1f4a94f5bc867f0f98de86fca5f4c53e2130cb4d6509537a8d709b26af2","observation_id":"11c34667-3e37-4c52-a71e-876bb8657b63","resolution":{"observed_at":"2026-08-12T17:55:18.031207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-11T19:54:34.537574Z","title":"Deep Learning with HM- VGG: AI Strategies for Multi-modal Image Analysis","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.06249","last_updated":"2024-12-09T06:47:42Z","snapshot_observed_at":"2026-08-11T19:50:03.366364Z","submitted_at":"2024-12-09T06:47:42Z","title":"Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T19:54:34.537574Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2412.06249"},"observation_digest":"sha256:54fe2780217507b1580c177bee6b486118fd9e23ccfadc894fc05e32369ec95a","observation_id":"99e826e0-94c2-44d0-8f1d-943368e0bcfd","resolution":{"observed_at":"2026-08-11T19:54:34.537574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":"2410.24046","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-11T14:55:48.165436Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","venue":"eess.IV","work_id":"108166c7-276e-45dd-8e10-5bd3feb53475","year":2024},"citing_paper":{"arxiv_id":"2501.14745","last_updated":"2024-12-16T06:37:09Z","snapshot_observed_at":"2026-08-11T14:51:28.690428Z","submitted_at":"2024-12-16T06:37:09Z","title":"AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T14:55:48.075750Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2501.14745"},"observation_digest":"sha256:813c3d1248bc2a2f528bf547a8ad23605c9cf006d8f830524b87a78a6b2e31aa","observation_id":"d090adbb-da58-48b9-89df-5a855e39da5b","resolution":{"observed_at":"2026-08-11T14:55:48.171185Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.24046/citation-record","integrity":"/paper/2410.24046/integrity","json":"/paper/2410.24046/citation-record.json","paper":"/paper/2410.24046"},"outbound":[],"paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.24046."}