{"as_of":"2026-08-09T21:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:11915d34f84ce6682af6eb7727ab48b798afa7cb49f45b7a579b4bbab533359f","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:59:23.566111Z","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":"2026-07-03T06:07:41.272189Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-08-07T05:59:23.566111Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data genera- tion","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.06535","last_updated":"2025-08-25T17:07:02Z","snapshot_observed_at":"2026-08-08T23:37:52.646461Z","submitted_at":"2025-06-06T21:06:00Z","title":"MapleGrasp: Mask-guided Feature Pooling for Language-driven Efficient Robotic Grasping","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:59:23.566111Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2506.06535"},"observation_digest":"sha256:21a044b810cf9f6b47bfa56a29747ca1dc79fac3fc963887eafab704c3bc6bee","observation_id":"4449ba98-7be0-468f-8750-45f386955cb7","resolution":{"observed_at":"2026-08-07T05:59:23.566111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-08-06T16:38:26.534028Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data generation, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.13097","last_updated":"2025-07-17T13:09:28Z","snapshot_observed_at":"2026-08-07T03:31:49.741300Z","submitted_at":"2025-07-17T13:09:28Z","title":"GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T16:38:26.534028Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2507.13097"},"observation_digest":"sha256:570a3e0bc2fc3a57bd90ba4b05b6443954a33e2ab6aab9fe039b9d40a4f1e8a9","observation_id":"62bbdd88-3c6a-4cec-b4df-71d11caf71ce","resolution":{"observed_at":"2026-08-06T16:38:26.534028Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":"2505.13441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-07-03T06:07:41.272189Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data generation.arXiv preprint arXiv:2505.13441,","venue":null,"work_id":"4df4e32b-46dc-4eb7-bbe6-f2f408aa415b","year":2025},"citing_paper":{"arxiv_id":"2605.30161","last_updated":"2026-05-28T16:18:01Z","snapshot_observed_at":"2026-07-06T23:39:29.458653Z","submitted_at":"2026-05-28T16:18:01Z","title":"Why Far Looks Up: Probing Spatial Representation in Vision-Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-29T08:06:32.403727Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2605.30161"},"observation_digest":"sha256:a55d20e01180f927bf02b69922de2f0f4f82f1a6787a46cc25f73bf133091dfa","observation_id":"6b4774fe-e62f-4f5a-903e-15105ecb286e","resolution":{"observed_at":"2026-06-29T08:13:15.703890Z","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":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":"2505.13441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-07-03T06:07:41.272189Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data generation.arXiv preprint arXiv:2505.13441,","venue":null,"work_id":"4df4e32b-46dc-4eb7-bbe6-f2f408aa415b","year":2025},"citing_paper":{"arxiv_id":"2606.06155","last_updated":"2026-06-04T13:28:51Z","snapshot_observed_at":"2026-07-29T15:22:02.359291Z","submitted_at":"2026-06-04T13:28:51Z","title":"AffordanceVLA: A Vision-Language-Action Model Empowering Action Generation through Affordance-Aware Understanding","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-28T01:23:02.576098Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2606.06155"},"observation_digest":"sha256:b3c93c5a3504ebcee910708a64834d84841698840cbca7678ae1dc79e5496b1b","observation_id":"df40962d-2dd2-4f18-834c-e2082d336555","resolution":{"observed_at":"2026-07-02T13:16:59.150618Z","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":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":"2505.13441","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-07-03T06:07:41.272189Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data generation.arXiv preprint arXiv:2505.13441,","venue":null,"work_id":"4df4e32b-46dc-4eb7-bbe6-f2f408aa415b","year":2025},"citing_paper":{"arxiv_id":"2606.11324","last_updated":"2026-07-11T14:44:40Z","snapshot_observed_at":"2026-07-16T23:17:53.174457Z","submitted_at":"2026-06-09T18:07:50Z","title":"Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T12:55:47.754632Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2606.11324"},"observation_digest":"sha256:f130f7a90bbb9b2435b4231c27ba33ca052853ee989b27057626c8773ca8f483","observation_id":"a93b02fd-28a5-4fcf-8de7-0da2adb3e3cf","resolution":{"observed_at":"2026-07-03T06:07:41.273731Z","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":"2505.13441","last_updated":"2025-09-12T23:19:44Z","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13441","snapshot_observed_at":"2026-07-14T18:07:09.018997Z","title":"Graspmolmo: Generalizable task-oriented grasping via large-scale synthetic data generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.11324","last_updated":"2026-07-11T14:44:40Z","snapshot_observed_at":"2026-07-16T23:17:53.174457Z","submitted_at":"2026-06-09T18:07:50Z","title":"Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-14T18:07:09.018997Z"},"links":{"cited_paper":"/paper/2505.13441","citing_paper":"/paper/2606.11324"},"observation_digest":"sha256:9c63c0c1191c28845355df308e10fcbc0fa9b94e3623b98c46ce9cb3b8a9c49c","observation_id":"f76459b8-b3a8-4b34-8bd4-511a60a92770","resolution":{"observed_at":"2026-07-14T18:07:09.018997Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.13441/citation-record","integrity":"/paper/2505.13441/integrity","json":"/paper/2505.13441/citation-record.json","paper":"/paper/2505.13441"},"outbound":[],"paper":{"arxiv_id":"2505.13441","last_updated":"2025-09-12T23:19:44Z","latest_version":3,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-07T15:42:59.268386Z","submitted_at":"2025-05-19T17:59:06Z","title":"GraspMolmo: Generalizable Task-Oriented Grasping via Large-Scale Synthetic Data Generation"},"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 6 inbound Pith citation observations for arXiv:2505.13441."}