{"as_of":"2026-08-09T12:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:779a419a6e6ed89964549d5fdce508c1ad52bc624f23592b3fc9a30b7666cd3c","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:07:25.504405Z","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":"2026-05-16T15:42:41.519963Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.14519","last_updated":"2025-04-01T17:59:17Z","snapshot_observed_at":"2026-08-08T04:32:35.112465Z","submitted_at":"2024-11-21T16:45:43Z","title":"Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14519","snapshot_observed_at":"2026-08-06T21:07:25.504405Z","title":"Tra-moe: Learning trajectory prediction model from multiple domains for adaptive policy condition- ing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01016","last_updated":"2025-07-01T17:59:44Z","snapshot_observed_at":"2026-08-07T10:56:40.594954Z","submitted_at":"2025-07-01T17:59:44Z","title":"VQ-VLA: Improving Vision-Language-Action Models via Scaling Vector-Quantized Action Tokenizers","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T21:07:25.504405Z"},"links":{"cited_paper":"/paper/2411.14519","citing_paper":"/paper/2507.01016"},"observation_digest":"sha256:475930b13c56dda14dee043de107239d8322bed3148d5f6e266ce2062c71b52d","observation_id":"e1d8b0a8-5381-4bc9-bd51-22bf5b3618a4","resolution":{"observed_at":"2026-08-06T21:07:25.504405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14519","last_updated":"2025-04-01T17:59:17Z","snapshot_observed_at":"2026-08-08T04:32:35.112465Z","submitted_at":"2024-11-21T16:45:43Z","title":"Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning","version":2},"cited_work":{"arxiv_id":"2411.14519","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.14519","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tra-moe: Learning trajectory prediction model from multiple domains for adaptive policy conditioning","venue":null,"work_id":"50caa896-acaa-4b9f-829e-02cafee33d45","year":2024},"citing_paper":{"arxiv_id":"2507.04447","last_updated":"2025-08-26T08:23:50Z","snapshot_observed_at":"2026-08-05T16:56:52.400110Z","submitted_at":"2025-07-06T16:14:29Z","title":"DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-16T15:42:41.363422Z"},"links":{"cited_paper":"/paper/2411.14519","citing_paper":"/paper/2507.04447"},"observation_digest":"sha256:ea23e938b04a1ccbafc557840ac50ce1f853644e9516efcbdec9eee939badcf9","observation_id":"48604d1a-4b26-428d-809a-6c534db4262f","resolution":{"observed_at":"2026-05-16T15:42:41.521798Z","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/2411.14519/citation-record","integrity":"/paper/2411.14519/integrity","json":"/paper/2411.14519/citation-record.json","paper":"/paper/2411.14519"},"outbound":[],"paper":{"arxiv_id":"2411.14519","last_updated":"2025-04-01T17:59:17Z","latest_version":2,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-08T04:32:35.112465Z","submitted_at":"2024-11-21T16:45:43Z","title":"Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning"},"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":"2026-08-09T06:31:02.800959+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 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.14519."}