{"as_of":"2026-08-13T12:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:690786f595df855901c189dab7dcb600ff816df4b05770e88ba01b97745cd946","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":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":16,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T18:48:16.441432Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-12T18:48:16.441432Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization.arXiv preprint arXiv:2402.11453, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.11916","last_updated":"2024-11-18T02:58:37Z","snapshot_observed_at":"2026-08-12T23:07:50.168981Z","submitted_at":"2024-11-18T02:58:37Z","title":"From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T18:48:16.441432Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2411.11916"},"observation_digest":"sha256:004cd8bc0677d7d19187cd9d68a251fbe12f39cc9bd873ae652aaf37b191d534","observation_id":"a000bd1d-6f89-457e-8299-e053cd9b7560","resolution":{"observed_at":"2026-08-12T18:48:16.441432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-12T16:42:08.135002Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.14491","last_updated":"2024-12-01T08:37:51Z","snapshot_observed_at":"2026-08-12T16:36:01.837561Z","submitted_at":"2024-11-20T12:34:44Z","title":"A Survey on Human-Centric LLMs","version":3},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-12T16:42:08.135002Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2411.14491"},"observation_digest":"sha256:a80428a814e1f8bc7ac30139fcf8e4a9d96776e71eb6c577425ad10b0ff0d3a8","observation_id":"77a5562c-bc70-4120-90f0-4f7543e14890","resolution":{"observed_at":"2026-08-12T16:42:08.135002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-11T23:11:05.689917Z","title":"MatPlotAgent: Method and evaluation for LLM-based agentic scientiﬁc data visualization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02764","last_updated":"2025-02-26T16:52:21Z","snapshot_observed_at":"2026-08-13T08:56:42.127396Z","submitted_at":"2024-12-03T19:05:37Z","title":"Drawing Pandas: A Benchmark for LLMs in Generating Plotting Code","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T23:11:05.689917Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2412.02764"},"observation_digest":"sha256:2656dfad13309b17b5ae435ae7df51553efe481af6e3571e1cf0c95bb4eed169","observation_id":"f38cbc8b-4cae-4158-a8b9-8ea39c86bacf","resolution":{"observed_at":"2026-08-11T23:11:05.689917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-10T21:03:45.374853Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.06598","last_updated":"2025-07-02T04:47:37Z","snapshot_observed_at":"2026-08-11T16:18:12.169514Z","submitted_at":"2025-01-11T17:52:22Z","title":"ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T21:03:45.374853Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2501.06598"},"observation_digest":"sha256:edb569b2edc24191c6e41d39e97be0335e0c303d9574be84866b84d9f55380c8","observation_id":"e31c5d7f-490c-4406-8db7-6d269e548ed6","resolution":{"observed_at":"2026-08-10T21:03:45.374853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-09T17:04:03.706582Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00988","last_updated":"2025-02-03T02:00:29Z","snapshot_observed_at":"2026-08-13T07:39:38.322230Z","submitted_at":"2025-02-03T02:00:29Z","title":"PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-09T17:04:03.706582Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2502.00988"},"observation_digest":"sha256:c6686620ac5393fd8facaa31b3231d82c5fe26433148c36c82631e5f1631db50","observation_id":"3f649658-550c-41c6-801e-b0f4b22412e3","resolution":{"observed_at":"2026-08-09T17:04:03.706582Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-08T11:03:44.876313Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.08056","last_updated":"2025-02-12T01:36:27Z","snapshot_observed_at":"2026-08-10T16:04:47.629517Z","submitted_at":"2025-02-12T01:36:27Z","title":"Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T11:03:44.876313Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2502.08056"},"observation_digest":"sha256:478060b1a7cb49c5b080bc913495d2e4c2b14d245ef4b5d192f4b1e801c3717b","observation_id":"24088200-221f-4961-87f7-234a220f2f79","resolution":{"observed_at":"2026-08-08T11:03:44.876313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-07T14:57:43.263104Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.16832","last_updated":"2025-05-27T23:23:45Z","snapshot_observed_at":"2026-08-10T20:31:54.568347Z","submitted_at":"2025-05-22T16:02:18Z","title":"From EduVisBench to EduVisAgent: A Benchmark and Multi-Agent Framework for Reasoning-Driven Pedagogical Visualization","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-07T14:57:43.263104Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2505.16832"},"observation_digest":"sha256:7f7b72de5833319089e7dc9f4110f47b47798b092710b3cce4671a27b7a5936f","observation_id":"71a36ada-9aed-4f86-af4b-c2d528887aa8","resolution":{"observed_at":"2026-08-07T14:57:43.263104Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-06T18:19:58.361239Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.08719","last_updated":"2025-07-11T16:19:53Z","snapshot_observed_at":"2026-08-07T04:09:15.037517Z","submitted_at":"2025-07-11T16:19:53Z","title":"Multilingual Multimodal Software Developer for Code Generation","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T18:19:58.361239Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2507.08719"},"observation_digest":"sha256:fd83c92b57071b7d46f4c044b19d8388a80af416dd9a223fbe7a5a1e75cc3e61","observation_id":"cb1620c4-8ec1-46b1-b303-d7a45d076fb0","resolution":{"observed_at":"2026-08-06T18:19:58.361239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-06T05:46:52.784111Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.01279","last_updated":"2025-08-02T09:19:16Z","snapshot_observed_at":"2026-08-10T22:15:02.971681Z","submitted_at":"2025-08-02T09:19:16Z","title":"ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User Prompts","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T05:46:52.784111Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2508.01279"},"observation_digest":"sha256:58e792dc290771b2154b4c236c5199366eb925144b0b7495b6e6fc33115666b2","observation_id":"8f87e654-d63a-4648-aa64-a12741b05432","resolution":{"observed_at":"2026-08-06T05:46:52.784111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2602.05353","last_updated":"2026-05-03T14:07:13Z","snapshot_observed_at":"2026-08-11T12:44:32.949413Z","submitted_at":"2026-02-05T06:24:15Z","title":"AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-16T07:38:37.818623Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2602.05353"},"observation_digest":"sha256:10788a287c71d3d460c6885f20420fc2507109e5462110ddcb334802ae1653cd","observation_id":"aff17f77-318e-4abf-9531-70778a5e2f46","resolution":{"observed_at":"2026-05-16T07:40:44.020554Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2604.06079","last_updated":"2026-04-07T16:58:14Z","snapshot_observed_at":"2026-08-11T03:08:18.490238Z","submitted_at":"2026-04-07T16:58:14Z","title":"Scientific Graphics Program Synthesis via Dual Self-Consistency Reinforcement Learning","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-10T19:45:40.915428Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2604.06079"},"observation_digest":"sha256:98c164910ec49c91768f78c8a877af452c0bc513e665ec1f788f3c037b3f46eb","observation_id":"d4718168-dd91-4d13-a030-0a555a83a673","resolution":{"observed_at":"2026-05-10T22:30:53.399343Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2605.18661","last_updated":"2026-07-20T17:24:03Z","snapshot_observed_at":"2026-08-02T13:43:29.187658Z","submitted_at":"2026-05-18T17:08:26Z","title":"AI for Auto-Research: Roadmap & User Guide","version":1},"reference_index":236,"source":"pdf_text","source_observed_at":"2026-05-20T10:30:50.256635Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2605.18661"},"observation_digest":"sha256:17090aa875b9b9bb9d3b42aa4bcebbccab0a1e1cdb567dfdc6f9b9173727dfac","observation_id":"e8d60ae9-10a5-47da-a9df-492fa353b208","resolution":{"observed_at":"2026-05-20T10:33:12.732622Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-02T13:43:51.789163Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2605.18661","last_updated":"2026-07-20T17:24:03Z","snapshot_observed_at":"2026-08-02T13:43:29.187658Z","submitted_at":"2026-05-18T17:08:26Z","title":"AI for Auto-Research: Roadmap & User Guide","version":2},"reference_index":235,"source":"pdf_text","source_observed_at":"2026-08-02T13:43:51.789163Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2605.18661"},"observation_digest":"sha256:0c986578a823632137fe63d5967899e0da47deb5cd34c0cfcfaa76dab233bf5a","observation_id":"356da03b-c220-4228-a487-dfd9d7ab6563","resolution":{"observed_at":"2026-08-02T13:43:51.789163Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2606.00370","last_updated":"2026-05-29T21:22:16Z","snapshot_observed_at":"2026-08-12T16:19:25.833445Z","submitted_at":"2026-05-29T21:22:16Z","title":"Agentic Authoring of Interactive Multiview Visualizations in Genomics","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-28T20:40:28.892338Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2606.00370"},"observation_digest":"sha256:37d77cf787ec752e67084a47fdbc3615ec4aef59cb475a715b1aee7cf0e52197","observation_id":"728b00ca-00ba-42a7-9e4d-d39b00d2d6c5","resolution":{"observed_at":"2026-06-28T20:42:36.861661Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2606.09174","last_updated":"2026-06-10T04:07:30Z","snapshot_observed_at":"2026-08-07T16:22:37.320724Z","submitted_at":"2026-06-08T08:09:27Z","title":"Demonstrating chart-plot: Closing the Last Mile of Academic Chart Generation","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T15:24:11.732604Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2606.09174"},"observation_digest":"sha256:b911450ed2b2a95e0163f6ba12e8cc830530f6e6334a3a40447f7f46695e96d1","observation_id":"8e77614c-ccdd-4648-8dbd-f7f30fb1afb2","resolution":{"observed_at":"2026-07-03T03:17:35.474513Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization","version":3},"cited_work":{"arxiv_id":"2402.11453","doi":"10.48550/arxiv.2402.11453","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.11453","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Matplotagent: Method and evaluation for llm-based agentic scientific data visualization","venue":"arXiv (Cornell University)","work_id":"3542d4e0-9b5f-424c-96e3-ace3797b52eb","year":2025},"citing_paper":{"arxiv_id":"2606.15932","last_updated":"2026-06-16T15:28:03Z","snapshot_observed_at":"2026-07-06T23:52:37.922109Z","submitted_at":"2026-06-14T17:21:43Z","title":"Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-06-27T03:57:19.028507Z"},"links":{"cited_paper":"/paper/2402.11453","citing_paper":"/paper/2606.15932"},"observation_digest":"sha256:779913b374aa9913955980865a8095ce3db6f237069af546326a1ea1892ac6c5","observation_id":"ac720a3d-490a-404b-9454-549d9763f525","resolution":{"observed_at":"2026-07-03T17:38:44.196951Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.11453/citation-record","integrity":"/paper/2402.11453/integrity","json":"/paper/2402.11453/citation-record.json","paper":"/paper/2402.11453"},"outbound":[],"paper":{"arxiv_id":"2402.11453","last_updated":"2024-03-19T14:44:22Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T04:16:51.355695Z","submitted_at":"2024-02-18T04:28:28Z","title":"MatPlotAgent: Method and Evaluation for LLM-Based Agentic Scientific Data Visualization"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2402.11453."}