{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:6VQMFO2EGFC3LU4FBC7ME5KMZA","short_pith_number":"pith:6VQMFO2E","canonical_record":{"source":{"id":"2308.11339","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-08-22T10:36:56Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"e26be10684fbcaffcbe4e437f3fb8a8317709db2f4d6c5d28513c7a6f1020e9e","abstract_canon_sha256":"7ecd628c1f8fb1bf652f53c14a47f9dca6bcc6a800613f2def5ed7204491a954"},"schema_version":"1.0"},"canonical_sha256":"f560c2bb443145b5d38508bec2754cc82f7b9a29de1ce0383fb15316a315c780","source":{"kind":"arxiv","id":"2308.11339","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.11339","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"arxiv_version","alias_value":"2308.11339v3","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.11339","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_12","alias_value":"6VQMFO2EGFC3","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"6VQMFO2EGFC3LU4F","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"6VQMFO2E","created_at":"2026-07-05T07:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:6VQMFO2EGFC3LU4FBC7ME5KMZA","target":"record","payload":{"canonical_record":{"source":{"id":"2308.11339","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-08-22T10:36:56Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"e26be10684fbcaffcbe4e437f3fb8a8317709db2f4d6c5d28513c7a6f1020e9e","abstract_canon_sha256":"7ecd628c1f8fb1bf652f53c14a47f9dca6bcc6a800613f2def5ed7204491a954"},"schema_version":"1.0"},"canonical_sha256":"f560c2bb443145b5d38508bec2754cc82f7b9a29de1ce0383fb15316a315c780","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:32:22.005086Z","signature_b64":"MFdWeUI3/rBK3YTJabq/0H3pfXi1PeZ7O6UtaUgs0qyw88Il0FvarzL6WlBFfRvDaN+NaDbgg/nyEAxd17+xBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f560c2bb443145b5d38508bec2754cc82f7b9a29de1ce0383fb15316a315c780","last_reissued_at":"2026-07-05T07:32:22.004607Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:32:22.004607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.11339","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:32:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uORRF6v3N3U9+8mP5Un4jgTklJIl8pr4dpABf/P3jWK0kU55J8p719wXIuCvE2oepQC8n3QYZOIv9NTLLtNqCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T06:12:16.830708Z"},"content_sha256":"4852fc38dfb08f06c6dfa80a953d7bf2ad4bc1fc3a06a30879d90fdc59eada51","schema_version":"1.0","event_id":"sha256:4852fc38dfb08f06c6dfa80a953d7bf2ad4bc1fc3a06a30879d90fdc59eada51"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:6VQMFO2EGFC3LU4FBC7ME5KMZA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ProAgent: Building Proactive Cooperative Agents with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.MA"],"primary_cat":"cs.AI","authors_text":"Anji Liu, Ceyao Zhang, Cheng Zhang, Feng Yin, Guanghe Li, Junge Zhang, Kaijie Yang, Siyi Hu, Song-Chun Zhu, Xiaojun Chang, Yaodong Yang, Yihang Sun, Yitao Liang, Zhaowei Zhang, Zihao Wang","submitted_at":"2023-08-22T10:36:56Z","abstract_excerpt":"Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely primarily on learning-based methods, whose policy generalization depends heavily on the diversity of teammates they interact with during the training phase. Such reliance, however, constrains the agents' capacity for strategic adaptation when cooperating with unfamiliar teammates, which becomes a significant challenge in zero-shot coordination scenarios. To address this challenge, we propose ProAgent, a novel framew"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.11339","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2308.11339/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:32:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"C5qO/95wU65mVvCvZdOwOI1rbkd+PNSeTRRrOeOuM+TIZ2HK5W18MyTnXFp14xX/PTRprn3Sw+1Y2UyMSflOAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T06:12:16.831076Z"},"content_sha256":"de1817bbd632c99f77fb28dd749131e2a909dd0f80ac1c730dc73de1322af7a0","schema_version":"1.0","event_id":"sha256:de1817bbd632c99f77fb28dd749131e2a909dd0f80ac1c730dc73de1322af7a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/bundle.json","state_url":"https://pith.science/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-10T06:12:16Z","links":{"resolver":"https://pith.science/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA","bundle":"https://pith.science/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/bundle.json","state":"https://pith.science/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6VQMFO2EGFC3LU4FBC7ME5KMZA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:6VQMFO2EGFC3LU4FBC7ME5KMZA","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7ecd628c1f8fb1bf652f53c14a47f9dca6bcc6a800613f2def5ed7204491a954","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-08-22T10:36:56Z","title_canon_sha256":"e26be10684fbcaffcbe4e437f3fb8a8317709db2f4d6c5d28513c7a6f1020e9e"},"schema_version":"1.0","source":{"id":"2308.11339","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.11339","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"arxiv_version","alias_value":"2308.11339v3","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.11339","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_12","alias_value":"6VQMFO2EGFC3","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"6VQMFO2EGFC3LU4F","created_at":"2026-07-05T07:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"6VQMFO2E","created_at":"2026-07-05T07:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:de1817bbd632c99f77fb28dd749131e2a909dd0f80ac1c730dc73de1322af7a0","target":"graph","created_at":"2026-07-05T07:32:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2308.11339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Building agents with adaptive behavior in cooperative tasks stands as a paramount goal in the realm of multi-agent systems. Current approaches to developing cooperative agents rely primarily on learning-based methods, whose policy generalization depends heavily on the diversity of teammates they interact with during the training phase. Such reliance, however, constrains the agents' capacity for strategic adaptation when cooperating with unfamiliar teammates, which becomes a significant challenge in zero-shot coordination scenarios. To address this challenge, we propose ProAgent, a novel framew","authors_text":"Anji Liu, Ceyao Zhang, Cheng Zhang, Feng Yin, Guanghe Li, Junge Zhang, Kaijie Yang, Siyi Hu, Song-Chun Zhu, Xiaojun Chang, Yaodong Yang, Yihang Sun, Yitao Liang, Zhaowei Zhang, Zihao Wang","cross_cats":["cs.LG","cs.MA"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-08-22T10:36:56Z","title":"ProAgent: Building Proactive Cooperative Agents with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.11339","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:4852fc38dfb08f06c6dfa80a953d7bf2ad4bc1fc3a06a30879d90fdc59eada51","target":"record","created_at":"2026-07-05T07:32:22Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7ecd628c1f8fb1bf652f53c14a47f9dca6bcc6a800613f2def5ed7204491a954","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-08-22T10:36:56Z","title_canon_sha256":"e26be10684fbcaffcbe4e437f3fb8a8317709db2f4d6c5d28513c7a6f1020e9e"},"schema_version":"1.0","source":{"id":"2308.11339","kind":"arxiv","version":3}},"canonical_sha256":"f560c2bb443145b5d38508bec2754cc82f7b9a29de1ce0383fb15316a315c780","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f560c2bb443145b5d38508bec2754cc82f7b9a29de1ce0383fb15316a315c780","first_computed_at":"2026-07-05T07:32:22.004607Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:32:22.004607Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MFdWeUI3/rBK3YTJabq/0H3pfXi1PeZ7O6UtaUgs0qyw88Il0FvarzL6WlBFfRvDaN+NaDbgg/nyEAxd17+xBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:32:22.005086Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.11339","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4852fc38dfb08f06c6dfa80a953d7bf2ad4bc1fc3a06a30879d90fdc59eada51","sha256:de1817bbd632c99f77fb28dd749131e2a909dd0f80ac1c730dc73de1322af7a0"],"state_sha256":"d6ce4901fa0346274f7de4c5747551bba5a5264b2d955720da7f6f5be37b752c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M/MQ3FxZpUH6J4crRF9qtr1tUOB5nZNLeK38UNW6umaXGqEao6ZwVvUoob+QwaY4J3g3hVMjJtCgb2jsW/QoCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T06:12:16.833194Z","bundle_sha256":"6bea273d93c31a708425b84f87faf1e26f0b76d466f5fdfafccdc65faab07f05"}}