{"as_of":"2026-08-09T12:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e5f80c71bf37f94c8fc5017f5cef3675091aaed85caab69921fc410e2023cabf","coverage":[{"denominator":26,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":26,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:52:48.276234Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:25:25.199085Z","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":"2026-05-21T05:59:40.968045Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.20644","snapshot_observed_at":"2026-08-07T11:25:25.199085Z","title":"Hcqa- 1.5@ ego4d egoschema challenge 2025.arXiv preprint arXiv:2505.20644, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.02550","last_updated":"2025-06-11T11:16:41Z","snapshot_observed_at":"2026-08-08T21:33:55.672848Z","submitted_at":"2025-06-03T07:36:52Z","title":"Technical Report for Ego4D Long-Term Action Anticipation Challenge 2025","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:25:25.199085Z"},"links":{"cited_paper":"/paper/2505.20644","citing_paper":"/paper/2506.02550"},"observation_digest":"sha256:b62bda46e46b86a0e4cc34140bd0cfd62f2d141be961cf1fa719106cff7a6bd0","observation_id":"d15d61c0-265f-4f8a-88da-fe45678c392d","resolution":{"observed_at":"2026-08-07T11:25:25.199085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.20644","snapshot_observed_at":"2026-08-07T10:59:13.051571Z","title":"Hcqa- 1.5@ ego4d egoschema challenge 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.03710","last_updated":"2025-06-04T08:41:42Z","snapshot_observed_at":"2026-08-08T23:16:00.887765Z","submitted_at":"2025-06-04T08:41:42Z","title":"OSGNet @ Ego4D Episodic Memory Challenge 2025","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T10:59:13.051571Z"},"links":{"cited_paper":"/paper/2505.20644","citing_paper":"/paper/2506.03710"},"observation_digest":"sha256:b977f94e654996392b8ae9c81673bb666df03bb184245c9545d1455ab30ebe50","observation_id":"ed5ab977-67e4-444b-a337-d8a01db63b69","resolution":{"observed_at":"2026-08-07T10:59:13.051571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"cited_work":{"arxiv_id":"2505.20644","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.20644","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"HCQA-1.5 @ Ego4D EgoSchema challenge 2025","venue":null,"work_id":"e7df1b39-225e-44cb-9a52-9c12055188cb","year":2025},"citing_paper":{"arxiv_id":"2605.20901","last_updated":"2026-05-20T08:42:56Z","snapshot_observed_at":"2026-07-06T23:31:27.989406Z","submitted_at":"2026-05-20T08:42:56Z","title":"VISTA: Technical Report for the Ego4D Short-Term Object Interaction Anticipation at EgoVis 2026","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-21T05:56:24.066641Z"},"links":{"cited_paper":"/paper/2505.20644","citing_paper":"/paper/2605.20901"},"observation_digest":"sha256:7a6edbff56366c0319af6300f813247bfe20fc54d1ce1efbf1d57bd4ba2dc489","observation_id":"0fbd7d62-d046-4937-83d5-efe6ca1246ca","resolution":{"observed_at":"2026-05-21T05:59:40.970085Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"cited_work":{"arxiv_id":"2505.20644","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.20644","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"HCQA-1.5 @ Ego4D EgoSchema challenge 2025","venue":null,"work_id":"e7df1b39-225e-44cb-9a52-9c12055188cb","year":2025},"citing_paper":{"arxiv_id":"2605.20904","last_updated":"2026-05-20T08:47:50Z","snapshot_observed_at":"2026-07-06T23:31:27.989406Z","submitted_at":"2026-05-20T08:47:50Z","title":"JFAA: Technical Report for the EPIC-KITCHENS-100 Action Anticipation Challenge at EgoVis 2026","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-21T05:51:17.743034Z"},"links":{"cited_paper":"/paper/2505.20644","citing_paper":"/paper/2605.20904"},"observation_digest":"sha256:325208161f12993296c83440db1f6ea0dc445f3cbcc8796f527288acc7f1b819","observation_id":"fbada27c-adee-4880-8ae0-94852f55b513","resolution":{"observed_at":"2026-05-21T05:53:59.267856Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.20644/citation-record","integrity":"/paper/2505.20644/integrity","json":"/paper/2505.20644/citation-record.json","paper":"/paper/2505.20644"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-07T13:52:45.877137Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:45.877137Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:17498dda6d8f18db0cff8aa81e0cd74643eb34668f7022daf654700820c6bd3b","observation_id":"00309d1b-fc87-401f-8e71-04aa994fb696","resolution":{"observed_at":"2026-08-07T13:52:45.877137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00937","last_updated":"2023-12-01T21:34:10Z","snapshot_observed_at":"2026-08-02T08:12:01.084894Z","submitted_at":"2023-12-01T21:34:10Z","title":"Zero-Shot Video Question Answering with Procedural Programs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00937","snapshot_observed_at":"2026-08-07T13:52:45.964764Z","title":"Zero-shot video question answering with pro- cedural programs","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:45.964764Z"},"links":{"cited_paper":"/paper/2312.00937","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:0ab98a3dda3fd1c78cc7ef5a83305c04e11e76cac3de54879c233b68fb666ac9","observation_id":"7dca2ee3-cf4f-4a21-8a4b-2f5fd924c7bf","resolution":{"observed_at":"2026-08-07T13:52:45.964764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15778","last_updated":"2024-11-18T03:02:17Z","snapshot_observed_at":"2026-08-07T05:04:54.671966Z","submitted_at":"2024-06-22T07:57:58Z","title":"ObjectNLQ @ Ego4D Episodic Memory Challenge 2024","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15778","snapshot_observed_at":"2026-08-07T13:52:46.068036Z","title":"Objectnlq@ ego4d episodic memory challenge 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.068036Z"},"links":{"cited_paper":"/paper/2406.15778","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:a0d6749fc203dcb8619338c14d45c5bd7bce9d0b5c720c6a318eb45fe060c020","observation_id":"d8f38874-73e2-4f5d-9552-96fd59c9ef2f","resolution":{"observed_at":"2026-08-07T13:52:46.068036Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.04270","last_updated":"2025-05-07T09:20:12Z","snapshot_observed_at":"2026-08-07T15:49:13.116674Z","submitted_at":"2025-05-07T09:20:12Z","title":"Object-Shot Enhanced Grounding Network for Egocentric Video","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.04270","snapshot_observed_at":"2026-08-07T13:52:46.163301Z","title":"Object-shot enhanced grounding network for egocentric video","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.163301Z"},"links":{"cited_paper":"/paper/2505.04270","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:1b4f3679511cc846a697bee71d27fdf440d6861b632d5cc09eb25e64b93bf8f5","observation_id":"f5e82ec6-5935-4c86-b0b2-cbf4cbde5422","resolution":{"observed_at":"2026-08-07T13:52:46.163301Z","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":"2026-08-07T13:52:46.254112Z","title":"Ego4d: Around the world in 3,000 hours of egocentric video","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.254112Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:cf6aeee9f395c0ba40a6d7583693d8f63eecf0afe64011344d710d46c103e0e0","observation_id":"3b1fde6e-4f8b-4ed2-a73d-7a4d78327423","resolution":{"observed_at":"2026-08-07T13:52:46.254112Z","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":"2026-08-07T13:52:46.387190Z","title":"Bi-directional het- erogeneous graph hashing towards efficient outfit recom- mendation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.387190Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:cd9878b68fea4fcdab5bf87fccf95626b78ade439a600b664c4e247b043813a3","observation_id":"5a681851-a87b-4bff-8f4e-f97449355571","resolution":{"observed_at":"2026-08-07T13:52:46.387190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T13:52:46.478367Z","title":"Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.478367Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:ac7b6afaeb7eec09117fbc85318b0ea000b607e5f98326cd49da3e7044385974","observation_id":"b3c6c325-d615-44d9-a27d-a4c109922921","resolution":{"observed_at":"2026-08-07T13:52:46.478367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-07T13:52:46.596198Z","title":"Gpt-4o system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.596198Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:5672f0f60afaba3b34fbef9b935bd8f15fc838fc2ebe515307b52af2d5069b0a","observation_id":"87bba397-c7e3-4b47-a1a5-f296dea8325e","resolution":{"observed_at":"2026-08-07T13:52:46.596198Z","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":"2026-08-07T13:52:46.758920Z","title":"Egoschema: A diagnostic benchmark for very long- form video language understanding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.758920Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:b292d97c094db13486b2e87c7d84d845bdc83a57e4f277af60a1b00294c9b68a","observation_id":"9a9a8877-fad1-4627-b811-606db55c351b","resolution":{"observed_at":"2026-08-07T13:52:46.758920Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:52:49.247986Z","title":"Egoschema: A diagnostic benchmark for very long- form video language understanding","venue":null,"work_id":"188e8238-98fb-4864-b5ab-4cc3e31abe99","year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.827961Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:9781f0824c9a9b41ca81b050f047c681bd38e508ab4569dbff3495b66c80cedc","observation_id":"67fd6c94-31f7-4781-8c91-9629e24320c8","resolution":{"observed_at":"2026-08-07T13:52:49.324116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.07395","last_updated":"2024-12-30T09:51:22Z","snapshot_observed_at":"2026-08-01T19:49:29.658899Z","submitted_at":"2023-12-12T16:10:19Z","title":"A Simple Recipe for Contrastively Pre-training Video-First Encoders Beyond 16 Frames","version":2},"cited_work":{"arxiv_id":"2312.07395","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.07395","snapshot_observed_at":"2026-08-07T13:52:48.717341Z","title":"A Simple Recipe for Contrastively Pre-training Video-First Encoders Beyond 16 Frames","venue":"cs.CV","work_id":"ef632d64-3b9d-4e19-a2dc-337fd27cb0b4","year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:46.903982Z"},"links":{"cited_paper":"/paper/2312.07395","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:5d5b0a1722c62cdccdce24d201f2019c1ee73778479c1cfb6754e28971a1a7e3","observation_id":"80a6817b-41d1-4fa4-9a70-f87f50f234cb","resolution":{"observed_at":"2026-08-07T13:52:48.799428Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-07-06T17:41:42.995949Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-07T13:52:47.016912Z","title":"Gemini 1.5: Unlocking multimodal under- standing across millions of tokens of context","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.016912Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:0da36e1dd2efc4936a02d7019edd5eb47a9a46bc434aec6344639b985fcea1f3","observation_id":"72fa2132-2f0a-42d9-bac2-0d276cbb2d25","resolution":{"observed_at":"2026-08-07T13:52:47.016912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.10517","last_updated":"2024-03-15T17:57:52Z","snapshot_observed_at":"2026-08-08T16:44:49.841179Z","submitted_at":"2024-03-15T17:57:52Z","title":"VideoAgent: Long-form Video Understanding with Large Language Model as Agent","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.10517","snapshot_observed_at":"2026-08-07T13:52:47.085245Z","title":"Videoagent: Long-form video understand- ing with large language model as agent","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.085245Z"},"links":{"cited_paper":"/paper/2403.10517","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:08c0b771b37b004df39041b58a488aea84c421c48075037613ea9c135c84a151","observation_id":"de31d2bc-24b0-4290-928d-141577e8d402","resolution":{"observed_at":"2026-08-07T13:52:47.085245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.05269","last_updated":"2024-11-05T22:08:14Z","snapshot_observed_at":"2026-08-08T23:23:37.595238Z","submitted_at":"2023-12-07T19:19:25Z","title":"LifelongMemory: Leveraging LLMs for Answering Queries in Long-form Egocentric Videos","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.05269","snapshot_observed_at":"2026-08-07T13:52:47.158946Z","title":"Lifelongmem- ory: Leveraging llms for answering queries in egocentric videos","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.158946Z"},"links":{"cited_paper":"/paper/2312.05269","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:ed890b1491ff9f59ea673cbdf8aa22fe6587c571f23300ed2acad5818c9930df","observation_id":"193ecce4-cb6a-41d2-894e-55cb1b61ad08","resolution":{"observed_at":"2026-08-07T13:52:47.158946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.15377","last_updated":"2024-08-14T14:31:50Z","snapshot_observed_at":"2026-08-01T19:17:08.239976Z","submitted_at":"2024-03-22T17:57:42Z","title":"InternVideo2: Scaling Foundation Models for Multimodal Video Understanding","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.15377","snapshot_observed_at":"2026-08-07T13:52:47.260706Z","title":"Internvideo2: Scaling video foundation mod- els for multimodal video understanding","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.260706Z"},"links":{"cited_paper":"/paper/2403.15377","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:4ab28944f055b866fef4de41cbb46b4be4e63f926a8ad13740d0392572c1b8c6","observation_id":"4f82f8a4-75f2-4b0b-bd9f-12cdf4e124f5","resolution":{"observed_at":"2026-08-07T13:52:47.260706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.09994","last_updated":"2025-08-07T14:15:07Z","snapshot_observed_at":"2026-08-07T17:08:18.712292Z","submitted_at":"2025-03-13T03:05:11Z","title":"TIME: Temporal-Sensitive Multi-Dimensional Instruction Tuning and Robust Benchmarking for Video-LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.09994","snapshot_observed_at":"2026-08-07T13:52:47.347803Z","title":"Time: Temporal-sensitive multi-dimensional instruc- tion tuning and benchmarking for video-llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.347803Z"},"links":{"cited_paper":"/paper/2503.09994","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:3462a48cf7dfa52565d8fd7fdad21fa87c4bd480c42af622ed87c3ef102d2c25","observation_id":"c068a17e-05cb-405c-8a87-1e3aa9a5b555","resolution":{"observed_at":"2026-08-07T13:52:47.347803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-07T13:52:47.441675Z","title":"Qwen3 technical report","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.441675Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:a5d0193637c33165f0c1ce4fb8f8b5398d88330ebe8f019b7df7b667711ae7b2","observation_id":"8946bc22-2d2f-4797-9ed1-0c636a65981e","resolution":{"observed_at":"2026-08-07T13:52:47.441675Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.14178","last_updated":"2024-03-29T08:13:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-27T13:27:01Z","title":"mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.14178","snapshot_observed_at":"2026-08-07T13:52:47.510628Z","title":"mplug-owl: Modularization empowers large language models with multimodality","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.510628Z"},"links":{"cited_paper":"/paper/2304.14178","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:c7911f7cdfb5bec4617d5652710f723b2a44bf3e26e778a44f39ad8416e48a7a","observation_id":"a2d47cb6-9509-4678-ba47-00417f4e7550","resolution":{"observed_at":"2026-08-07T13:52:47.510628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17235","last_updated":"2024-10-10T05:17:00Z","snapshot_observed_at":"2026-07-06T17:09:24.271573Z","submitted_at":"2023-12-28T18:58:01Z","title":"A Simple LLM Framework for Long-Range Video Question-Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17235","snapshot_observed_at":"2026-08-07T13:52:47.594214Z","title":"A sim- ple llm framework for long-range video question-answering","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.594214Z"},"links":{"cited_paper":"/paper/2312.17235","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:00ca591838d1ee374fe9ac991ed21c9192dcc1ed0c54add99af5c9553c0c9049","observation_id":"89b6721f-3457-49b3-88e1-24ab7fba52b6","resolution":{"observed_at":"2026-08-07T13:52:47.594214Z","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":"2026-08-07T13:52:47.697062Z","title":"Multimodal dialog system: Rela- tional graph-based context-aware question understanding","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.697062Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:4cce69e0e5feeddc06728bef1b707060bcb28d511e07786f4a1444fe6fb32dc9","observation_id":"d49ef4a6-3257-4047-a7c4-f447560d8be7","resolution":{"observed_at":"2026-08-07T13:52:47.697062Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:52:49.051582Z","title":"Attribute-guided collab- orative learning for partial person re-identification","venue":null,"work_id":"fc2573c3-2f14-495b-a03e-9bce55c26d18","year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.789396Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:fff0f64d42bfd98a8285bd086fb708e3486eda892dd34972e145a2c5fff937cd","observation_id":"82c94243-2b3c-4076-ac80-4679517a6a54","resolution":{"observed_at":"2026-08-07T13:52:49.170673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07259","last_updated":"2025-03-12T05:09:37Z","snapshot_observed_at":"2026-07-06T16:31:03.559653Z","submitted_at":"2023-10-11T07:37:13Z","title":"Uncovering Hidden Connections: Iterative Search and Reasoning for Video-grounded Dialog","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07259","snapshot_observed_at":"2026-08-07T13:52:47.883128Z","title":"Uncovering hidden connections: Iterative tracking and reasoning for video-grounded dialog","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.883128Z"},"links":{"cited_paper":"/paper/2310.07259","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:cdd4ddd8a7ae443fb148e19b7c0ba838a3f8ef38b87ca29532c3152921f27efa","observation_id":"12afb00c-9e49-4505-abda-cdf65d3eb9c7","resolution":{"observed_at":"2026-08-07T13:52:47.883128Z","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":"2026-08-07T13:52:47.972820Z","title":"Multi-factor adaptive vision selec- tion for egocentric video question answering","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:47.972820Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:e49f88b18741a94780c352472bc0e9297fdd63e79a91b90e1ee7830410b35a85","observation_id":"5f3f7379-e9b7-429e-a6e6-e2b60e4dc4a0","resolution":{"observed_at":"2026-08-07T13:52:47.972820Z","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":"2026-08-07T13:52:48.050363Z","title":"Hcqa@ ego4d egoschema challenge","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:48.050363Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:48b9a4ce84b55f49b05b26c81a1ab65a029cc2a9e91a9f7bfdf8c1b7fe5675f6","observation_id":"278b02d5-06a6-4851-924a-f9030a0c2c8c","resolution":{"observed_at":"2026-08-07T13:52:48.050363Z","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":"2026-08-07T13:52:48.276234Z","title":"Exo2ego: Exocentric knowledge guided mllm for egocentric video understanding","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:48.276234Z"},"links":{"citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:c4e1ebb25dc739b570e789324c96c485b09349d82414e4695e7858df3d75e532","observation_id":"47d2f134-b5cc-488c-bdfe-7b5abc997ee6","resolution":{"observed_at":"2026-08-07T13:52:48.276234Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.15771","last_updated":"2024-10-29T02:38:27Z","snapshot_observed_at":"2026-08-06T07:53:27.979224Z","submitted_at":"2024-06-22T07:20:39Z","title":"HCQA @ Ego4D EgoSchema Challenge 2024","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.15771","snapshot_observed_at":"2026-08-07T13:52:48.177755Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:48.177755Z"},"links":{"cited_paper":"/paper/2406.15771","citing_paper":"/paper/2505.20644"},"observation_digest":"sha256:9cd7449ac0d7368a659aa61ddf0a2954460323e82dbc2a908e2008e1bb35f879","observation_id":"78568f41-dda2-4173-8471-f0c9980dce8f","resolution":{"observed_at":"2026-08-07T13:52:48.177755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.20644","last_updated":"2025-05-27T02:45:14Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T13:47:38.739847Z","submitted_at":"2025-05-27T02:45:14Z","title":"HCQA-1.5 @ Ego4D EgoSchema Challenge 2025"},"reference_resolution":{"displayed":26,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":1,"verified_fuzzy":2},"total_outbound_references":26},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 4 inbound Pith citation observations for arXiv:2505.20644."}