{"as_of":"2026-08-07T21:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1e19fe0cc68346d2766dfbb6dad822d15693c52e3d1eef53318958cf9a91ebd1","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:55:54.697904Z","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":"2026-06-30T07:34:21.243055Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-08-07T00:55:54.697904Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12468","last_updated":"2025-06-17T03:17:11Z","snapshot_observed_at":"2026-08-07T00:46:40.868394Z","submitted_at":"2025-06-14T12:14:15Z","title":"Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:55:54.697904Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2506.12468"},"observation_digest":"sha256:176d8e2c50628c7340b15c88032d4260f00f95396b0fa3fa73d046b77781faa4","observation_id":"1750b650-e19e-4892-96df-3a2eb559f631","resolution":{"observed_at":"2026-08-07T00:55:54.697904Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2508.07117","last_updated":"2026-04-22T15:08:37Z","snapshot_observed_at":"2026-07-06T22:10:35.711171Z","submitted_at":"2025-08-09T23:22:38Z","title":"From Nodes to Narratives: Explaining Graph Neural Networks with LLMs and Graph Context","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-18T23:30:11.590032Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2508.07117"},"observation_digest":"sha256:8517cb020ed4f71f501a7095185ae1eca21086668dc92d618dcf070a66e69b57","observation_id":"c6e0e9ff-1522-40b6-b105-e23fbe0012d8","resolution":{"observed_at":"2026-05-18T23:31:54.439896Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2510.16416","last_updated":"2026-05-17T05:54:56Z","snapshot_observed_at":"2026-08-02T06:39:30.995519Z","submitted_at":"2025-10-18T09:22:40Z","title":"SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning","version":4},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-21T20:24:02.748854Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2510.16416"},"observation_digest":"sha256:d9426b489266818538b3f843147c916f4b73ec2e8d351cd32667147535fe0e1e","observation_id":"7e118424-0813-4c3e-9ff4-f18d2d1f7b42","resolution":{"observed_at":"2026-05-21T20:24:21.384495Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-08-03T23:37:55.267414Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2511.07457","last_updated":"2026-07-20T02:41:15Z","snapshot_observed_at":"2026-08-06T01:49:16.929228Z","submitted_at":"2025-11-06T21:56:58Z","title":"GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T23:37:55.267414Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2511.07457"},"observation_digest":"sha256:5da34f00370861a9a5609a567c6d96d9948d709724e424ba2e824f9a7b904d7f","observation_id":"effb1f1b-ba34-4ba1-acec-4bce5c1895eb","resolution":{"observed_at":"2026-08-03T23:37:55.267414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-08-03T00:07:39.878803Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.11641","last_updated":"2026-05-31T02:32:04Z","snapshot_observed_at":"2026-08-04T07:46:12.428271Z","submitted_at":"2026-02-12T06:53:35Z","title":"Both Topology and Text Matter: Revisiting LLM-guided Out-of-Distribution Detection on Text-attributed Graphs","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T00:07:39.878803Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2602.11641"},"observation_digest":"sha256:e550fd67bcd9308cac0fecd1f2303456336276aac4bc07ef9a19d3f2237d932e","observation_id":"75ad69d0-77ed-4082-8608-4a13d5ae1915","resolution":{"observed_at":"2026-08-03T00:07:39.878803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2605.13021","last_updated":"2026-05-13T05:24:35Z","snapshot_observed_at":"2026-07-06T23:24:37.915639Z","submitted_at":"2026-05-13T05:24:35Z","title":"Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-14T19:31:41.045648Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2605.13021"},"observation_digest":"sha256:bc52b355beb6a626c2cd90ae63126800dabb230b3fcba750c3b7c09f09647a53","observation_id":"3583e508-6d15-416c-a8d3-ef5e7332d4a4","resolution":{"observed_at":"2026-05-14T19:32:52.036169Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2605.18579","last_updated":"2026-05-20T03:15:37Z","snapshot_observed_at":"2026-08-02T23:11:13.880944Z","submitted_at":"2026-05-18T15:56:19Z","title":"S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-20T12:49:18.671971Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2605.18579"},"observation_digest":"sha256:ab63fb45cb456ad22e97e9224c633df2f476c6b8b9f5ce8e219ab99301446aab","observation_id":"bd7787eb-d7e6-4cd7-b01c-18fb4d8591b2","resolution":{"observed_at":"2026-05-20T12:53:17.636480Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2605.18579","last_updated":"2026-05-20T03:15:37Z","snapshot_observed_at":"2026-08-02T23:11:13.880944Z","submitted_at":"2026-05-18T15:56:19Z","title":"S2Aligner: Pair-Efficient and Transferable Pre-Training for Sparse Text-Attributed Graphs","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T07:55:11.088587Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2605.18579"},"observation_digest":"sha256:0bf019adcf8afd6d410f2f8ca04df0a8772c04f3d4ec8299ae8f075c3fe5b943","observation_id":"87779dad-e61e-49dc-91b6-7bf6c37530b4","resolution":{"observed_at":"2026-05-21T07:59:50.879709Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":"2406.14683","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-06-30T07:34:21.243055Z","title":"Taglas: An atlas of text-attributed graph datasets in the era of large graph and language models","venue":null,"work_id":"d4e0e2c3-4991-4fdf-85cf-80f77ddc7f39","year":2024},"citing_paper":{"arxiv_id":"2606.29773","last_updated":"2026-06-29T04:30:45Z","snapshot_observed_at":"2026-07-31T06:33:27.649714Z","submitted_at":"2026-06-29T04:30:45Z","title":"GLIP: Graph and LLM Joint Pretraining for Graph-Level Tasks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-30T07:33:27.135616Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2606.29773"},"observation_digest":"sha256:a77fa14b6952f3a3f149ec6caa85390ac15c1a35d60c11049c6bfb889d96eb13","observation_id":"5bc6a684-5f9c-4d0f-83e4-0e2f34f92eb5","resolution":{"observed_at":"2026-06-30T07:34:21.244657Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14683","snapshot_observed_at":"2026-08-02T12:58:07.779285Z","title":"arXiv preprint arXiv:2406.14683(2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20477","last_updated":"2026-05-27T14:52:24Z","snapshot_observed_at":"2026-08-07T14:34:45.953978Z","submitted_at":"2026-05-27T14:52:24Z","title":"Semi-Supervised Text-Attributed Graph Distillation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T12:58:07.779285Z"},"links":{"cited_paper":"/paper/2406.14683","citing_paper":"/paper/2607.20477"},"observation_digest":"sha256:52a7062fdfd376480744def22cce0d2157df332a6b396e72a2edb513a262b74b","observation_id":"370dc6fe-26de-40de-9823-6bb8eed672a4","resolution":{"observed_at":"2026-08-02T12:58:07.779285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.14683/citation-record","integrity":"/paper/2406.14683/integrity","json":"/paper/2406.14683/citation-record.json","paper":"/paper/2406.14683"},"outbound":[],"paper":{"arxiv_id":"2406.14683","last_updated":"2024-10-19T18:47:33Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T18:34:33.717998Z","submitted_at":"2024-06-20T19:11:35Z","title":"TAGLAS: An atlas of text-attributed graph datasets in the era of large graph and language models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2406.14683."}