{"as_of":"2026-08-08T22:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a0f19399028e0dc90fecc8e5cdb5530e84f27fe2afab1d758b0c7627081765d7","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T01:30:45.804190Z","state":"measured"},{"denominator":34,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":34,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T01:30:45.707858Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.25791","snapshot_observed_at":"2026-08-01T01:30:45.707858Z","title":"arXiv:2607.25791v1 [cs.CV] 28 Jul 2026 The remainder of this paper is organized as follows: Sec- tion 2 reviews related work","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.707858Z"},"links":{"cited_paper":"/paper/2607.25791","citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:ee459a70b3629979dd7f7dcdcdcc68bdbc23e4cb885edea3f81f5f12cd5335a9","observation_id":"1c0bd681-15a2-495d-9a0a-ce2a851bff1b","resolution":{"observed_at":"2026-08-01T01:30:45.707858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2607.25791/citation-record","integrity":"/paper/2607.25791/integrity","json":"/paper/2607.25791/citation-record.json","paper":"/paper/2607.25791"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.687451Z","title":"Effective intervention requires not only detecting that a fall has occurred but also identifying the precise moment of ground impact the instant when the body hits the ground","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.687451Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:9d672589a0e4978f8ac88f8eff1e893fbb68ef5f36702df93513a73da11b14c6","observation_id":"eeb8931a-6aeb-46bb-8186-31513def30a1","resolution":{"observed_at":"2026-08-01T01:30:45.687451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.692441Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.692441Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:048d2c5375b2dd19f38ee93d11cc98670d97a0ea7448c8c73a263e9e5ee971c9","observation_id":"7d4d3f9f-867c-4393-bcfc-86d15768ebfa","resolution":{"observed_at":"2026-08-01T01:30:45.692441Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.696306Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.696306Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:1ff4044a6cc091a8361079808a109956b330b197ce50a68f33d6155aaa145300","observation_id":"b3a56129-db6a-467d-8ff4-6538fd7827cd","resolution":{"observed_at":"2026-08-01T01:30:45.696306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.700155Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.700155Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:0a21a50f6cadd9d0d88daa8dfd6eed7601e4ee09165ba75b7d8cce04bce1e651","observation_id":"1bd05b46-68ed-4c77-b37e-9038f23437cc","resolution":{"observed_at":"2026-08-01T01:30:45.700155Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.704038Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.704038Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:089d863507502e319717d6e45f50c82d2158f916c1bf76525549e266fbb69ebb","observation_id":"232bb440-8b4a-493a-8890-4f05858c46d0","resolution":{"observed_at":"2026-08-01T01:30:45.704038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.745571Z","title":"Vision-based fall detection using ST-GCN,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.745571Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:e0ac219b54976f1572f6e512c51c23b81cc1be6e1e18f4a9cceeed00cef690dd","observation_id":"63ebf8bb-a828-4357-a5b3-69498e9c2c45","resolution":{"observed_at":"2026-08-01T01:30:45.745571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.711640Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.711640Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:625231920f1b9b2f8f6aa7a626c8722aaa087e11c01e1d0b0879a91205c73699","observation_id":"85379bfd-0596-4b66-9d2f-f3f80118033b","resolution":{"observed_at":"2026-08-01T01:30:45.711640Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.716091Z","title":"Problem Formulation Given a skeletal motion sequenceS={s 1, s2,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.716091Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:dde156d7e2e008ddeecad72e283f5da2a5a6c044fb8953553594e639c4f3b479","observation_id":"70803089-7318-4e1f-af8c-114b44eca2ba","resolution":{"observed_at":"2026-08-01T01:30:45.716091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.719734Z","title":"Experimental Setup 4.1.1","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.719734Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:bf81575d00468a478d7f3cbe0945163cc0c7913d7390031339db129f9bc03632","observation_id":"020b0485-1345-4ec3-a8b0-c94535dfd3da","resolution":{"observed_at":"2026-08-01T01:30:45.719734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.25791","snapshot_observed_at":"2026-08-01T01:30:45.707858Z","title":"arXiv:2607.25791v1 [cs.CV] 28 Jul 2026 The remainder of this paper is organized as follows: Sec- tion 2 reviews related work","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.707858Z"},"links":{"cited_paper":"/paper/2607.25791","citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:ee459a70b3629979dd7f7dcdcdcc68bdbc23e4cb885edea3f81f5f12cd5335a9","observation_id":"1c0bd681-15a2-495d-9a0a-ce2a851bff1b","resolution":{"observed_at":"2026-08-01T01:30:45.707858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.723396Z","title":"Biomechanically-grounded hyperedges capture multi-joint coordination while Mamba’s linear-time com- plexity ensures real-time efficiency","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.723396Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:ada2544081b610b7d8f44894f770b4c44dc88fc757a122559cd4bfe3932063a7","observation_id":"d00152ba-dd46-4d6a-aced-4c011a5325f6","resolution":{"observed_at":"2026-08-01T01:30:45.723396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.726955Z","title":"Fall-induced injuries and deaths among older adults,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.726955Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:6422966192d2310c0bff966fad0da47d118130996424d43a7284818ad1612c51","observation_id":"a86db283-0826-444b-a6a4-7522db791c64","resolution":{"observed_at":"2026-08-01T01:30:45.726955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.730705Z","title":"UP-Fall detection dataset: A multimodal approach,","venue":null,"work_id":null,"year":1988},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.730705Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:00c9b476da92ac3f25c1a0ea4bb8e58726d4eb2f497d5c7e29e7453a14baf7bd","observation_id":"46170f56-cff9-4a79-bcdf-60350e169ae0","resolution":{"observed_at":"2026-08-01T01:30:45.730705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.734442Z","title":"Machine learning and feature ranking for impact fall detection event using multisen- sor data,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.734442Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:995966e12326a4ddb62a75167af34a99d55b234df54156a8e4020438410ddd9d","observation_id":"9071bdcd-9c3f-4094-b11f-7b8c8c695578","resolution":{"observed_at":"2026-08-01T01:30:45.734442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.738066Z","title":"Fall detec- tion based on key points of human-skeleton using Open- Pose,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.738066Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:3d157b073f8c6a68fbc7abb86e8c007a763688bd8a92c24243f23198da6f1428","observation_id":"06b05a0c-ccf5-4182-8725-6888f3a0e57a","resolution":{"observed_at":"2026-08-01T01:30:45.738066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.741593Z","title":"Spatial temporal graph convolutional networks for skeleton-based action recog- nition,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.741593Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:de6fc546268affb16dae242197d78d0304b615d4be2ae94c3142e25449eb01a0","observation_id":"15732626-6951-40b2-bbce-00852cf48518","resolution":{"observed_at":"2026-08-01T01:30:45.741593Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.749255Z","title":"Hy- pergraph neural networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.749255Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:ef8cf701558b612d7508e0f4717468cdd3936237274de4d39a6b2dca71fdc4bb","observation_id":"2777b7cf-5d14-4875-81d6-f839633d62c1","resolution":{"observed_at":"2026-08-01T01:30:45.749255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.752674Z","title":"Transformer for skeleton-based ac- tion recognition: A review of recent advances,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.752674Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:6ede8a50e2f5035c4ef021d73af73ab7fcaa6e2bea2aaa8cea093f025a6b246d","observation_id":"907b2775-ae8e-4aac-8ed8-2c38d3bef125","resolution":{"observed_at":"2026-08-01T01:30:45.752674Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.755976Z","title":"Mamba: Linear-time sequence modeling with selective state spaces,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.755976Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:061ed7c9c7a9576f16b56f1fe400374007ca6adce41d2793311787b0f8953934","observation_id":"1811df5e-254d-4dbb-b007-cc4d628ac5fe","resolution":{"observed_at":"2026-08-01T01:30:45.755976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.759302Z","title":"Umafall: A multisensor dataset for the research on automatic fall detection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.759302Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:9c8fe740c2d32093871963cca04ffc553389bf6447a11786cbedf44bea411e64","observation_id":"eb9abd8b-b070-470e-bc03-5967631e0b7a","resolution":{"observed_at":"2026-08-01T01:30:45.759302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.762960Z","title":"Skeleton-based fall detection with multiple inertial sensors using spatial- temporal graph convolutional networks,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.762960Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:51b61460da7150febcaf8a9b22694ea4dc338c93319afd162ea5b09d1f4bbf2b","observation_id":"475c636e-a380-4536-82bb-04e030e8215b","resolution":{"observed_at":"2026-08-01T01:30:45.762960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.766280Z","title":"Impact detection in fall events: Leveraging spatio-temporal graph convolutional networks and recurrent neural networks using 3d skele- ton data,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.766280Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:0eb1abf092f3ded1ab581e58952f990047554779062cd39c397acc68eb843d56","observation_id":"81c413ef-0a53-4db2-b00f-4b467c13e414","resolution":{"observed_at":"2026-08-01T01:30:45.766280Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.769552Z","title":"Hypergraph neural network for skeleton-based ac- tion recognition,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.769552Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:4f6970690441523bd851845fb26564b3a7d71e8bc936c9ce8b48860d11df53fa","observation_id":"6753a6ff-e96f-438c-a0e1-596364b595d3","resolution":{"observed_at":"2026-08-01T01:30:45.769552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.772939Z","title":"Autoregressive adaptive hypergraph transformer for skeleton-based activity recognition,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.772939Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:1b4de539cedd3e7c9bcbe355054ee3e43c85e696d6e0ff1dd0203a37890ff5fb","observation_id":"ed9163e5-604f-4a91-b686-5041da6fe65a","resolution":{"observed_at":"2026-08-01T01:30:45.772939Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19316","last_updated":"2024-03-28T11:17:00Z","snapshot_observed_at":"2026-08-06T01:32:42.324050Z","submitted_at":"2024-03-28T11:17:00Z","title":"Hypergraph-based Multi-View Action Recognition using Event Cameras","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.19316","snapshot_observed_at":"2026-08-01T01:30:45.776312Z","title":"Hypergraph-based multi-view action recognition using event cameras,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.776312Z"},"links":{"cited_paper":"/paper/2403.19316","citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:0c04132790fe01fca73419d2764ff4871b943b063382efac1364e78d2e8b6902","observation_id":"8c841328-a29f-4212-8d18-23852c38b545","resolution":{"observed_at":"2026-08-01T01:30:45.776312Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.779957Z","title":"Ensembles of deep lstm learners for activity recognition using wearables,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.779957Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:09c0ff50b5b86dd03c96f760187f3cc99db86a9788205b09acee1a3e578ced36","observation_id":"e0e7a023-9cd2-4535-bfda-89088c2e22f5","resolution":{"observed_at":"2026-08-01T01:30:45.779957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.783300Z","title":"Tcformer: A 5m- parameter transformer with density-guided aggregation for weakly-supervised crowd counting,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.783300Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:de4db84df21a7e32d2b7e5d2cfb968c60df99f3c000288a6ca2f3e68a86790ed","observation_id":"2d8605cd-ee4a-4215-92b4-e337068969fe","resolution":{"observed_at":"2026-08-01T01:30:45.783300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.786751Z","title":"Distillh-mamba: A hypergraph-mamba-based knowledge distillation model for efficient impact fall detection,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.786751Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:a99352e246638e96285aba18a9cd2e9138371e8bbfefba2bf468084a85b888f7","observation_id":"14633968-2fac-48bf-a1a5-8e37db083565","resolution":{"observed_at":"2026-08-01T01:30:45.786751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.790405Z","title":"Finite element analysis of hip frac- ture risk in elderly female: The effects of soft tissue shape, fall direction, and interventions,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.790405Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:3f48ac18c75c3065ec38fe9924fd2016723f028aeb1a84fd0bc9ff64283fcdeb","observation_id":"97e4e074-47c4-49d5-a65e-a158f8f97295","resolution":{"observed_at":"2026-08-01T01:30:45.790405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.793851Z","title":"The effect of fall biomechan- ics on risk for hip fracture in older adults: a cohort study of video-captured falls in long-term care,","venue":null,"work_id":null,"year":1914},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.793851Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:49455dfa4a4042fe0d12140b92a5d43158949bf428068c58059abda550bb300b","observation_id":"cef55d15-7794-4ad0-9475-82abb352dc3a","resolution":{"observed_at":"2026-08-01T01:30:45.793851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.797344Z","title":"An improved 3d skeletons up-fall dataset: enhancing data quality for efficient im- pact fall detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.797344Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:9fd87dc412ce065d4c2c1496c7b68727aaf9de93f043be13a881efa998b1698e","observation_id":"cb2aa128-d113-4b09-845a-c6ead1be6d64","resolution":{"observed_at":"2026-08-01T01:30:45.797344Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:30:45.800764Z","title":"Two-stream adaptive graph convolutional networks for skeleton- based action recognition,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.800764Z"},"links":{"citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:43caf567881689703080b1220e603b79d397ef469ca85da942a299f7dbcfb69e","observation_id":"b570dfdf-9d55-48a7-80eb-9f8101f81f58","resolution":{"observed_at":"2026-08-01T01:30:45.800764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09590","last_updated":"2023-03-21T17:34:34Z","snapshot_observed_at":"2026-07-06T14:19:51.472138Z","submitted_at":"2022-11-17T15:36:48Z","title":"Hypergraph Transformer for Skeleton-based Action Recognition","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09590","snapshot_observed_at":"2026-08-01T01:30:45.804190Z","title":"Hy- pergraph transformer for skeleton-based action recogni- tion,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T01:30:45.804190Z"},"links":{"cited_paper":"/paper/2211.09590","citing_paper":"/paper/2607.25791"},"observation_digest":"sha256:cfa2127821ab246c60c30a75b3116ada77f97b50349f108b238d2d70b8c111c0","observation_id":"553ba17a-a6fe-4489-9d13-d1eeeea01196","resolution":{"observed_at":"2026-08-01T01:30:45.804190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.25791","last_updated":"2026-07-28T14:43:07Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T15:28:27.589969Z","submitted_at":"2026-07-28T14:43:07Z","title":"FLASH: Efficient Impact Fall Detection with Unified Hypergraph State-Space Model"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":33},"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 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2607.25791."}