{"as_of":"2026-08-10T22:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f016f92a5615b39c106377f6b13d706e491af7f8838a7f818273d3b27f834bf7","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T14:01:38.357242Z","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":"2026-07-03T17:28:44.545474Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.07074","last_updated":"2025-05-08T16:40:59Z","snapshot_observed_at":"2026-07-06T19:30:34.984716Z","submitted_at":"2024-10-09T17:19:12Z","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07074","snapshot_observed_at":"2026-08-10T14:01:38.357242Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.15755","last_updated":"2025-01-27T03:50:30Z","snapshot_observed_at":"2026-08-10T13:55:53.163531Z","submitted_at":"2025-01-27T03:50:30Z","title":"GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T14:01:38.357242Z"},"links":{"cited_paper":"/paper/2410.07074","citing_paper":"/paper/2501.15755"},"observation_digest":"sha256:c2a96f16c822e7fda4e72c939628eca6c31adeb48e1973299e26df41523b71de","observation_id":"1e37aed3-6b49-4897-bfa5-478cb2003e0b","resolution":{"observed_at":"2026-08-10T14:01:38.357242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07074","last_updated":"2025-05-08T16:40:59Z","snapshot_observed_at":"2026-07-06T19:30:34.984716Z","submitted_at":"2024-10-09T17:19:12Z","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07074","snapshot_observed_at":"2026-08-06T11:30:45.517113Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.22668","last_updated":"2025-07-30T13:25:36Z","snapshot_observed_at":"2026-08-10T06:06:58.612687Z","submitted_at":"2025-07-30T13:25:36Z","title":"Graph-Guided Dual-Level Augmentation for 3D Scene Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T11:30:45.517113Z"},"links":{"cited_paper":"/paper/2410.07074","citing_paper":"/paper/2507.22668"},"observation_digest":"sha256:7ebb569fd7bd04026f091a31f1c0513b3d3e1bf1190c57386295aecbf39c8ea2","observation_id":"6c07cc88-ab59-4ca9-993c-cb09684e055a","resolution":{"observed_at":"2026-08-06T11:30:45.517113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07074","last_updated":"2025-05-08T16:40:59Z","snapshot_observed_at":"2026-07-06T19:30:34.984716Z","submitted_at":"2024-10-09T17:19:12Z","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","version":3},"cited_work":{"arxiv_id":"2410.07074","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.07074","snapshot_observed_at":"2026-07-03T17:28:44.545474Z","title":"Let's ask gnn: Empowering large language model for graph in-context learning","venue":null,"work_id":"5e7de06f-7fd0-4e99-bb4e-d69476967f92","year":2025},"citing_paper":{"arxiv_id":"2511.02135","last_updated":"2026-04-16T08:31:14Z","snapshot_observed_at":"2026-08-02T06:20:11.557622Z","submitted_at":"2025-11-03T23:54:24Z","title":"Graph-Based Alternatives to LLMs for Human Simulation","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-05-18T00:47:40.432039Z"},"links":{"cited_paper":"/paper/2410.07074","citing_paper":"/paper/2511.02135"},"observation_digest":"sha256:6a8430c3519f15bf092f80d1db0db1b7ec48387793dcf2e2027eaa3a4d638536","observation_id":"09a46e83-0791-4657-b9a2-fae4dde099e8","resolution":{"observed_at":"2026-05-18T00:50:33.364596Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07074","last_updated":"2025-05-08T16:40:59Z","snapshot_observed_at":"2026-07-06T19:30:34.984716Z","submitted_at":"2024-10-09T17:19:12Z","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning","version":3},"cited_work":{"arxiv_id":"2410.07074","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.07074","snapshot_observed_at":"2026-07-03T17:28:44.545474Z","title":"Let's ask gnn: Empowering large language model for graph in-context learning","venue":null,"work_id":"5e7de06f-7fd0-4e99-bb4e-d69476967f92","year":2025},"citing_paper":{"arxiv_id":"2606.15633","last_updated":"2026-06-17T05:23:30Z","snapshot_observed_at":"2026-08-08T13:05:37.982431Z","submitted_at":"2026-06-14T06:50:28Z","title":"Formalizing and Mitigating Structural Distortion in LLM Attention for Graph Reasoning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T04:07:56.287352Z"},"links":{"cited_paper":"/paper/2410.07074","citing_paper":"/paper/2606.15633"},"observation_digest":"sha256:ce32eed80778c1f41824401a714930cc0163a1a49a7b10d0d82451748903e052","observation_id":"c1a78e09-d8aa-41ef-99bb-1b20b6ea9de1","resolution":{"observed_at":"2026-07-03T17:28:44.546932Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.07074/citation-record","integrity":"/paper/2410.07074/integrity","json":"/paper/2410.07074/citation-record.json","paper":"/paper/2410.07074"},"outbound":[],"paper":{"arxiv_id":"2410.07074","last_updated":"2025-05-08T16:40:59Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:30:34.984716Z","submitted_at":"2024-10-09T17:19:12Z","title":"Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.07074."}