{"as_of":"2026-08-04T09:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8091d7b366bf0cdae59ad345bda1664fbf4f074ec11978f25d5996708b2c9be5","coverage":[{"denominator":50,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":50,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T10:43:25.025812Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.04972/citation-record","integrity":"/paper/2607.04972/integrity","json":"/paper/2607.04972/citation-record.json","paper":"/paper/2607.04972"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Search and pursuit-evasion in mobile robotics: A survey,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:374595ce01c7c3f6285cc0a93d67709625cce304f2ebfae53cf0e31c53840754","observation_id":"e16b5a42-9148-45b4-a6b8-847fc45ab41b","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"DACOOP-A: Decentralized adaptive cooperative pursuit via attention,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:c9d987ecdbe1c93c67d1b07a0b065f25dcae4aa14532a5327988c0b90201fe29","observation_id":"e6b597ba-1823-4804-b67f-bbcdd8ab5a7b","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Collaborative multi-robot search and rescue: Planning, coordination, perception, and active vision,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:63677be8278f2d3515c85c5eb36ab36b754c783e75af1632f68554a351f5f18e","observation_id":"658df48c-05c3-424e-976b-15b3e2c2ab28","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Multi- agent actor-critic for mixed cooperative-competitive environments,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:319c003c47a5453dd34651e4aa6875e4b27cfbe89897c8f0bff57d8f6d85aead","observation_id":"068f9b89-4aab-49a6-b9d0-b9beaa34c791","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"QMIX: Monotonic value function factorisation for decen- tralised multi-agent reinforcement learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:c23658497aaa08772b959adbe0fe1781d976d27dc62d9e9c0e5740421069b284","observation_id":"b972f860-77a4-4378-b02a-efe1a972f6a0","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"The surprising effectiveness of PPO in cooperative multi-agent games,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:723df5d6ac34eb0f8ebd4d7ba70ab39aa2bf4020143b0614dc7af88d584f6ec4","observation_id":"8966e508-54c3-4200-820c-04af4c3d03f3","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"“Other-Play","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:140bae7803496b1f24c9f5c7132ab60f61cb4eb34b9aca229ad4c3a2fbca58ee","observation_id":"9bc2f9d1-4151-489f-90ba-1c9bb418fc0b","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Towards optimally decentralized multi-robot collision avoidance via deep rein- forcement learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:db0e5e3f512373d3e19f07a6d300324626693d55a77ba9bb120f44dcfeebd524","observation_id":"d42ea6f5-831b-4822-afdd-6e89383ead2d","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Graph neural networks for decentralized multi-robot path planning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:a3f9c554228f49dc09056da3961c75e5fd992d684938c1112d014be2cf6ec087","observation_id":"8066fd78-7603-4823-8191-6b671d70c045","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Coop- erative open-ended learning framework for zero-shot coordination,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:841ce5afe8f8059c035b385112ffb598809529b82cac9179787d40cef87a0007","observation_id":"7a3056d5-8f8d-47f8-9ce3-ed145dee2c58","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Ad hoc autonomous agent teams: Collaboration without pre-coordination,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:5cf0f11026115f66395824a012ca6b19e243d1e0faa2592a58c8038afef4e394","observation_id":"3cee92f4-6fa1-4d9f-a813-54e29727511d","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Open ad hoc teamwork with cooperative game theory,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:7ef3e4eb5a12f68b81cac42b3d2b25caf37ede68e130550dfc2c6cc05b9166b0","observation_id":"8be13f83-bff0-4236-9093-824d8976b4e6","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Domain randomization for transferring deep neural networks from simulation to the real world,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:90ae950aed51d772e527c1bcbbab429d18ef6983ecb510ba869bb20816943f17","observation_id":"b7ceaaaa-bda8-4b16-aa3f-e9a61e21d6e1","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"The surprising effectiveness of ppo in cooperative, multi-agent games,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:b4d309b0ee4f98fd8b7de7bd6c9572dc9f07f0192a217c1972839eabbc7fc4b8","observation_id":"36aa577c-951d-4439-94fe-850bac33fd20","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.09846","last_updated":"2017-11-28T16:16:21Z","snapshot_observed_at":"2026-07-06T06:11:24.949724Z","submitted_at":"2017-11-27T17:33:27Z","title":"Population Based Training of Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.09846","snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Population based training of neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"cited_paper":"/paper/1711.09846","citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:153f20ef14011152f2595a68dfb3cefa4549ef5624138ff41e3c6d51c6b3354d","observation_id":"efea5242-a4aa-4762-bd80-0e4856c97610","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Collaborating with humans without human data,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:8a25bd95aaa09be88438e0dc436c7edfe8a998b4b38e59450f7229b82e7635e9","observation_id":"08f7a635-8574-415b-bb63-d7d8e3ff8852","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Multi-robot system based on model of wolf hunting behavior to emulate wolf and elk interactions,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:11f7f29826b4d89982b1a3bb6dce8908d1157b10bc40513f2ec8c617434a9cce","observation_id":"550ce070-6e7f-4ece-87b1-c7e89f93f2d5","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computa- tional simulations,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:32cdb500f67a6ebd080f9b91f7eb188462dba0580e62e23a5aae1a58b2df5609","observation_id":"603f533d-3c9a-4659-88d5-3465b6bfb963","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Collective Predation and Escape Strategies,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:0818c0ad1029620ae0931c87d61e0859b052a272883425854c217a8761ee120a","observation_id":"37f6392c-b160-4a89-890a-022e20ea6777","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Group chasing tactics: how to catch a faster prey,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:4f4d98052546077fc079ed25ebcd528632197febe96901c081df099cf508c10c","observation_id":"45eb46a6-0001-4eae-bdb0-49c0e5971678","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Intercepting Rogue Robots: An Algorithm for Capturing Multiple Evaders With Multiple Pursuers,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:74b0a56ec9f13e2172f5c50d6df730752e357c9f5fc3f22f04a77a795bafedcb","observation_id":"ea5de664-cdc8-48f0-918c-104f7c497e39","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"A survey of the pursuit–evasion problem in swarm intelligence,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:662f524418edeb2f66439742293e506791449b3fc623033cacf6e96f7a0f8095","observation_id":"8917f5b7-706a-48a4-b174-61408c92ccdc","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"A Geometric Approach for the Cooperative Two-Pursuer One-Evader Differential Game,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:29baacb798b3e420f020b9e277fe967578539ebeefe53b8526101453b715574a","observation_id":"485e35e6-9e26-424b-b68e-b4417c19d9db","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Cooperative Multiple Pursuers against a Single Evader,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:1b04c6cfa16d065c84e7e903f177793dacdd8d352bdefbf739dcd97491d37ae6","observation_id":"f19bd83d-bec5-4225-b671-77369679f958","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"A Two-on-One Linear Pursuit–Evasion Game with Bounded Controls,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:6cc9ba513668c57234612ad77fede95ba3d87e2c7528d6deb4abb45d0c7ba181","observation_id":"2e16f37e-4997-4e0c-bf0d-b7f62ba7ff4b","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Hysteretic Q-learning : an algorithm for Decentralized Reinforcement Learning in Cooperative Multi-Agent Teams,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:f6aafce704e29cc1c665f75f123ae4d560ee3adc966362159e3d902d4de3f3cc","observation_id":"6a88b778-fa21-48f1-8082-bbf49f84073a","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Robust Multi- Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:92f06f679b96269f7a338ca4bc292e3859913e245718d6c09c1f1167d20a69ce","observation_id":"5c59a256-f9ad-4336-9828-0dc80d7db62f","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Cascaded Attention: Adaptive and Gated Graph Attention Network for Multiagent Reinforcement Learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:a1fc253e459f8d0fa8acc64d3e7125e1454f6ccd56706fbc4eea8a574edbae22","observation_id":"39fd1405-0a90-4419-8d67-375674012ab4","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Decentralized Multi-Agent Pursuit Using Deep Rein- forcement Learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:b12569ba118ebbd9c3b2f19893929de253d9c62e9051fefc1821e4b826bae073","observation_id":"ea714f4b-4ec8-482e-ace8-5a814c2fa01d","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Multi-agent rein- forcement learning by the actor-critic model with an attention interface,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:5483ab9ae95a6a3f9c9ff20e4780456d5bbd7f3997a55c6fdb6b212b862bf4a4","observation_id":"f650c2ed-1757-4344-8510-da5066023312","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.12255","last_updated":"2024-04-30T06:18:21Z","snapshot_observed_at":"2026-07-06T17:05:22.992895Z","submitted_at":"2023-12-19T15:39:09Z","title":"A Dual Curriculum Learning Framework for Multi-UAV Pursuit-Evasion in Diverse Environments","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.12255","snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Taskflex solver for multi-agent pursuit via automatic curriculum learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"cited_paper":"/paper/2312.12255","citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:a5b7d3052131d72f7c1db35322d6dc07cffa4fee1fc180035435be683a55d543","observation_id":"6daddc6f-0865-4a17-a974-66497b5a79c1","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.15866","last_updated":"2025-07-08T16:34:36Z","snapshot_observed_at":"2026-07-06T19:21:03.775247Z","submitted_at":"2024-09-24T08:40:04Z","title":"Online Planning for Multi-UAV Pursuit-Evasion in Unknown Environments Using Deep Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.15866","snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Multi-uav pursuit-evasion with online planning in un- known environments by deep reinforcement learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"cited_paper":"/paper/2409.15866","citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:40a0172fe354019dc525adb092e6df44c17abbd012f686ef47bcc8ead0eaf8d6","observation_id":"abd6e735-0cfb-4475-9079-3d3640f4aae8","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Making friends on the fly: Cooperating with new teammates,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:532f3468da606eba084eb12705911d66914ae17f54c5b6ec9d8276190d29b548","observation_id":"24d2343c-1ccf-4250-a835-6e40bda9ecae","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"A general learning framework for open ad hoc teamwork using graph- based policy learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:8ca9fc0e8b6f6896faa5cf9024e32fda5ef6987fc414270b198813d1c05416e3","observation_id":"bb979082-79ad-4365-ba17-8af37b6f12e2","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Open ad hoc teamwork with cooperative game theory,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:f57f24172779573970471c0e81e3907fd9b8a54bc8e88528798b6175db2aea72","observation_id":"a6674543-afef-4fff-ba81-4c617c245a0e","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.11285","last_updated":"2025-06-12T20:44:09Z","snapshot_observed_at":"2026-07-06T21:41:24.021272Z","submitted_at":"2025-06-12T20:44:09Z","title":"Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.11285","snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Shapley machine: A game- theoretic framework for n-agent ad hoc teamwork,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"cited_paper":"/paper/2506.11285","citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:66898fd4e6f0ab9945341b452e67c89ae51b2f4d1e4554bf90afc0bbe764ca86","observation_id":"243a752d-4cb7-4358-9456-1a5ffc95d7a7","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Off-belief learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:563a4728f90df08a5666651af74268a6d3109b9afed550859ebb6df7e5074779","observation_id":"50cc09fc-89e0-4aa5-b321-6570eebc6381","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Maximum entropy population-based training for zero- shot human-AI coordination,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:c7dc07ae48215f160419dc0fd51c5fdc2b1b3fcb7057c5e405ef605c33069c0b","observation_id":"d162599a-35f9-4d1f-943e-7155abebc5fa","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Coop- erative open-ended learning framework for zero-shot coordination,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:27def412be81d8818b41f7bf3e16fcbc1e2119fc4a3d3179ebd86cfd5ec097f2","observation_id":"bd941b0a-8b51-4733-bb9f-6b10a470bfe2","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Tackling cooperative incompatibility for zero-shot human- ai coordination,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:73023a7575d0f4fd7fb133720aa27367c03a5086da7c9e82fa6fe4d9e86639c5","observation_id":"e00960ba-7a93-48ed-b16d-62f5f08aa7f4","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"UPDeT: Universal multi- agent reinforcement learning via policy decoupling with transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:44db184135f4b8db61736b1aba3b2fa9a787b94ee3ff8dbcd3f6eb728859d517","observation_id":"8a8aba52-83ff-44f9-a575-360923521f8a","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Multi-agent reinforcement learning is a sequence modeling problem,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:c799485752494a978cf4bc93f785df4b99cdb8ab233890c1e5b5f067ce2adf10","observation_id":"bcc3eae6-147c-43b5-be8a-b5fe43e1bf4b","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Evo- lutionary population curriculum for scaling multi-agent reinforcement learning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:7cb89c4c5ed21da6f69dfeb424cc4beecc783902ba1f60e77ad1cd085e81b55b","observation_id":"3c0dd14f-fee9-4c99-9938-2938f493f2d8","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Skilled population curriculum for multi-agent reinforcement learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:f40dd865d97ef5e8b70932eb662b58a2c95d4cfb77f92da7279bd12f73c2d18f","observation_id":"68903f1b-e3a3-4a74-a6b1-225164f68707","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Maximum entropy population-based training for zero-shot human-ai coordination,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:92002b520a5613a68e458f5e284553719647697de1f1f795f6e498e9c8180056","observation_id":"b36fd69c-5302-4fdd-ab64-62ad9b9c7bdb","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Group chasing tactics: How to catch a faster prey,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:a9b8d90266e2dca17e9e5e8c5899b34d5d4aec23d52c24704452b85973e96744","observation_id":"53cb1858-cad6-4585-b6d9-e24c9404ac91","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Dueling network architectures for deep reinforcement learning,","venue":null,"work_id":null,"year":1995},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:dade7ba5cad45bd495ef7b811fcd62cdfab6f391db3e13b1c9f62d905e066221","observation_id":"ae318e2c-0644-40fa-b990-9f95f795e37c","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1704.06440","last_updated":"2018-10-14T22:54:38Z","snapshot_observed_at":"2026-07-06T05:38:40.783917Z","submitted_at":"2017-04-21T08:33:59Z","title":"Equivalence Between Policy Gradients and Soft Q-Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.06440","snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Equivalence between policy gradients and soft q-learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"cited_paper":"/paper/1704.06440","citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:3b47173562c76546c39b658caa6b8d02b769b5282babeaa29607571045f52332","observation_id":"d057c6bf-4ce2-48b1-bd94-6a90aab82750","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"On the utility of learning about humans for human- ai coordination,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:aa9041b14e40c174fd99202b505f614bee99604bf085983acac6e66e2b6c26a1","observation_id":"1d59b69a-f06b-4e63-80ae-62c5a20b383a","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T10:43:25.025812Z","title":"Collaborating with humans without human data,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-07-11T10:43:25.025812Z"},"links":{"citing_paper":"/paper/2607.04972"},"observation_digest":"sha256:e1b5be2f68fb8d4e630503425b83e6a140d67ac2041ba1df47e3af81b83de33b","observation_id":"1f0c71be-012c-4587-a940-bb79cea49dc4","resolution":{"observed_at":"2026-07-11T10:43:25.025812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.04972","last_updated":"2026-07-06T12:02:02Z","latest_version":1,"primary_category":"cs.RO","snapshot_observed_at":"2026-08-03T01:01:54.245570Z","submitted_at":"2026-07-06T12:02:02Z","title":"Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales"},"reference_resolution":{"displayed":50,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":50,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":50},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2607.04972."}