{"as_of":"2026-08-11T07:54:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:39a3645224524366157877f28220f936c7ca73706d70dc6aa43cb6303b33fff8","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:16:45.461411Z","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":"2026-05-24T18:36:19.057719Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground","version":2},"cited_work":{"arxiv_id":"1809.07124","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1809.07124","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pommerman: A multi- agent playground","venue":null,"work_id":"a3d3f509-6547-41a8-93d2-8f5bbad4f43d","year":2018},"citing_paper":{"arxiv_id":"1907.09467","last_updated":"2019-07-20T05:13:53Z","snapshot_observed_at":"2026-07-06T08:09:23.168454Z","submitted_at":"2019-07-20T05:13:53Z","title":"Arena: a toolkit for Multi-Agent Reinforcement Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-24T18:35:31.633881Z"},"links":{"cited_paper":"/paper/1809.07124","citing_paper":"/paper/1907.09467"},"observation_digest":"sha256:68c402069c9570041fe6f39f7eb45b65095fcf5e4606ff68ace771f81f408bc0","observation_id":"b8a86c9c-2c43-4378-8284-b9a330def60c","resolution":{"observed_at":"2026-05-24T18:36:19.060697Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground","version":2},"cited_work":{"arxiv_id":"1809.07124","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1809.07124","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pommerman: A multi- agent playground","venue":null,"work_id":"a3d3f509-6547-41a8-93d2-8f5bbad4f43d","year":2018},"citing_paper":{"arxiv_id":"2506.07548","last_updated":"2026-05-06T13:16:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-09T08:38:18Z","title":"Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-19T11:08:51.426575Z"},"links":{"cited_paper":"/paper/1809.07124","citing_paper":"/paper/2506.07548"},"observation_digest":"sha256:aafa41116f235d4ad970982f57ba724021e6082115884d5898a2dbd77003db9c","observation_id":"069fb439-390c-4f54-8954-76a4daa4e3b9","resolution":{"observed_at":"2026-05-19T11:12:15.530792Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.07124","snapshot_observed_at":"2026-08-07T00:16:45.461411Z","title":"Pommerman: A multi-agent playground.arXiv preprint arXiv:1809.07124, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.14990","last_updated":"2026-06-18T15:11:38Z","snapshot_observed_at":"2026-08-07T11:55:17.356594Z","submitted_at":"2025-06-17T21:50:04Z","title":"MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T00:16:45.461411Z"},"links":{"cited_paper":"/paper/1809.07124","citing_paper":"/paper/2506.14990"},"observation_digest":"sha256:12b67d71cbc9751ab5237cd515c314a8456ec3450b1ed598fe86f45e73d4185d","observation_id":"22fcfb96-40c9-4ba5-9ac4-fd45487958bd","resolution":{"observed_at":"2026-08-07T00:16:45.461411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.07124","snapshot_observed_at":"2026-08-06T17:42:58.987731Z","title":"Pommerman: A multi-agent playground.arXiv preprint arXiv:1809.07124, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.10142","last_updated":"2026-07-22T04:23:01Z","snapshot_observed_at":"2026-08-11T04:46:06.732267Z","submitted_at":"2025-07-14T10:39:17Z","title":"Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review","version":2},"reference_index":152,"source":"pdf_text","source_observed_at":"2026-08-06T17:42:58.987731Z"},"links":{"cited_paper":"/paper/1809.07124","citing_paper":"/paper/2507.10142"},"observation_digest":"sha256:310e845c5004805d64a1a55df952d6f9c9d38f296db066850d0e26198febf3aa","observation_id":"3dc2dbc8-5bb2-4a4e-9955-dd7cf440b543","resolution":{"observed_at":"2026-08-06T17:42:58.987731Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground","version":2},"cited_work":{"arxiv_id":"1809.07124","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1809.07124","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pommerman: A multi- agent playground","venue":null,"work_id":"a3d3f509-6547-41a8-93d2-8f5bbad4f43d","year":2018},"citing_paper":{"arxiv_id":"2511.20857","last_updated":"2026-05-18T16:18:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-25T21:08:07Z","title":"Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory","version":1},"reference_index":104,"source":"arxiv_source","source_observed_at":"2026-05-14T23:13:15.016486Z"},"links":{"cited_paper":"/paper/1809.07124","citing_paper":"/paper/2511.20857"},"observation_digest":"sha256:023081090e4fea709cd5ca831d988ad98a5fa836132634dfd31dbbb9933fbefd","observation_id":"0738223e-d30a-4c24-a6ae-9ad6e44faa3f","resolution":{"observed_at":"2026-05-14T23:13:15.696441Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1809.07124/citation-record","integrity":"/paper/1809.07124/integrity","json":"/paper/1809.07124/citation-record.json","paper":"/paper/1809.07124"},"outbound":[],"paper":{"arxiv_id":"1809.07124","last_updated":"2022-04-21T13:52:02Z","latest_version":2,"primary_category":"cs.MA","snapshot_observed_at":"2026-07-06T07:03:04.423446Z","submitted_at":"2018-09-19T11:27:25Z","title":"Pommerman: A Multi-Agent Playground"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1809.07124."}