{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:T5OUYQT7OXLBLTY4M4PVK2SRVW","short_pith_number":"pith:T5OUYQT7","canonical_record":{"source":{"id":"1702.05573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T06:00:45Z","cross_cats_sorted":[],"title_canon_sha256":"f7709d08e795dae72c36fd0ffc54ed1831f4b770e72d80fd8f3f5b3edfd1d19f","abstract_canon_sha256":"2ac439d6dbf46c9296727ccabbf71cf7b3b188e7619403b13a5e576e641cc8f2"},"schema_version":"1.0"},"canonical_sha256":"9f5d4c427f75d615cf1c671f556a51ada2a103a55f4983a26de758439c8f453b","source":{"kind":"arxiv","id":"1702.05573","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.05573","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"arxiv_version","alias_value":"1702.05573v1","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.05573","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"pith_short_12","alias_value":"T5OUYQT7OXLB","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"T5OUYQT7OXLBLTY4","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"T5OUYQT7","created_at":"2026-05-18T12:31:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:T5OUYQT7OXLBLTY4M4PVK2SRVW","target":"record","payload":{"canonical_record":{"source":{"id":"1702.05573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T06:00:45Z","cross_cats_sorted":[],"title_canon_sha256":"f7709d08e795dae72c36fd0ffc54ed1831f4b770e72d80fd8f3f5b3edfd1d19f","abstract_canon_sha256":"2ac439d6dbf46c9296727ccabbf71cf7b3b188e7619403b13a5e576e641cc8f2"},"schema_version":"1.0"},"canonical_sha256":"9f5d4c427f75d615cf1c671f556a51ada2a103a55f4983a26de758439c8f453b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:50:30.412670Z","signature_b64":"x4sAE5eDZkcFBkMMgHWxz3VlXmNDNjiQ398KfRNFEQA/TT2NPLgCghb2sFpa0uiIvdln8Geu8lgTMqMZ8S+SAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f5d4c427f75d615cf1c671f556a51ada2a103a55f4983a26de758439c8f453b","last_reissued_at":"2026-05-18T00:50:30.412002Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:50:30.412002Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1702.05573","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:50:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4jvS8LGsgJt7A3RZu72jiknPIUfdjnxPtAksjM7S+Mn/Ff8R/RwNLIx6JO89KEtKQTFk5xV4CPkp98ftBtq0DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T09:08:16.655464Z"},"content_sha256":"171beb1b10f65b52fa302396f3dc0d70573e2b4e3647b0de62e06220aab4b3a3","schema_version":"1.0","event_id":"sha256:171beb1b10f65b52fa302396f3dc0d70573e2b4e3647b0de62e06220aab4b3a3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:T5OUYQT7OXLBLTY4M4PVK2SRVW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Collaborative Deep Reinforcement Learning for Joint Object Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Xin, Gang Hua, Xiangyu Kong, Yizhou Wang","submitted_at":"2017-02-18T06:00:45Z","abstract_excerpt":"We examine the problem of joint top-down active search of multiple objects under interaction, e.g., person riding a bicycle, cups held by the table, etc.. Such objects under interaction often can provide contextual cues to each other to facilitate more efficient search. By treating each detector as an agent, we present the first collaborative multi-agent deep reinforcement learning algorithm to learn the optimal policy for joint active object localization, which effectively exploits such beneficial contextual information. We learn inter-agent communication through cross connections with gates "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.05573","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:50:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bFdGd/yLaaZw6hBQr1aZlimHnmuqHo2F/IPgNrg2BM/tm9k5Q4iXGTE1DAbmuA6e0JAiu2/R+UHqmds9N5HtBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T09:08:16.655813Z"},"content_sha256":"81280ebce718994f3f57f010471587efcbeb79f388ed9487d6965ab0a0eecc72","schema_version":"1.0","event_id":"sha256:81280ebce718994f3f57f010471587efcbeb79f388ed9487d6965ab0a0eecc72"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/bundle.json","state_url":"https://pith.science/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/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":"2026-05-28T09:08:16Z","links":{"resolver":"https://pith.science/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW","bundle":"https://pith.science/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/bundle.json","state":"https://pith.science/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T5OUYQT7OXLBLTY4M4PVK2SRVW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:T5OUYQT7OXLBLTY4M4PVK2SRVW","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":"2ac439d6dbf46c9296727ccabbf71cf7b3b188e7619403b13a5e576e641cc8f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T06:00:45Z","title_canon_sha256":"f7709d08e795dae72c36fd0ffc54ed1831f4b770e72d80fd8f3f5b3edfd1d19f"},"schema_version":"1.0","source":{"id":"1702.05573","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.05573","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"arxiv_version","alias_value":"1702.05573v1","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.05573","created_at":"2026-05-18T00:50:30Z"},{"alias_kind":"pith_short_12","alias_value":"T5OUYQT7OXLB","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_16","alias_value":"T5OUYQT7OXLBLTY4","created_at":"2026-05-18T12:31:43Z"},{"alias_kind":"pith_short_8","alias_value":"T5OUYQT7","created_at":"2026-05-18T12:31:43Z"}],"graph_snapshots":[{"event_id":"sha256:81280ebce718994f3f57f010471587efcbeb79f388ed9487d6965ab0a0eecc72","target":"graph","created_at":"2026-05-18T00:50:30Z","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"},"paper":{"abstract_excerpt":"We examine the problem of joint top-down active search of multiple objects under interaction, e.g., person riding a bicycle, cups held by the table, etc.. Such objects under interaction often can provide contextual cues to each other to facilitate more efficient search. By treating each detector as an agent, we present the first collaborative multi-agent deep reinforcement learning algorithm to learn the optimal policy for joint active object localization, which effectively exploits such beneficial contextual information. We learn inter-agent communication through cross connections with gates ","authors_text":"Bo Xin, Gang Hua, Xiangyu Kong, Yizhou Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T06:00:45Z","title":"Collaborative Deep Reinforcement Learning for Joint Object Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.05573","kind":"arxiv","version":1},"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":"sha256:171beb1b10f65b52fa302396f3dc0d70573e2b4e3647b0de62e06220aab4b3a3","target":"record","created_at":"2026-05-18T00:50:30Z","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":"2ac439d6dbf46c9296727ccabbf71cf7b3b188e7619403b13a5e576e641cc8f2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-02-18T06:00:45Z","title_canon_sha256":"f7709d08e795dae72c36fd0ffc54ed1831f4b770e72d80fd8f3f5b3edfd1d19f"},"schema_version":"1.0","source":{"id":"1702.05573","kind":"arxiv","version":1}},"canonical_sha256":"9f5d4c427f75d615cf1c671f556a51ada2a103a55f4983a26de758439c8f453b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f5d4c427f75d615cf1c671f556a51ada2a103a55f4983a26de758439c8f453b","first_computed_at":"2026-05-18T00:50:30.412002Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:50:30.412002Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x4sAE5eDZkcFBkMMgHWxz3VlXmNDNjiQ398KfRNFEQA/TT2NPLgCghb2sFpa0uiIvdln8Geu8lgTMqMZ8S+SAg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:50:30.412670Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.05573","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:171beb1b10f65b52fa302396f3dc0d70573e2b4e3647b0de62e06220aab4b3a3","sha256:81280ebce718994f3f57f010471587efcbeb79f388ed9487d6965ab0a0eecc72"],"state_sha256":"93a4e9c0480fe46ed5735072c526f55d66e68d3dbef85a9c7f002cf2d31907d3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MghiInmA45nurchw05QHAlO4ZlzD9RpEqLW0jHsb2XG9rXBgzxKeXUgbEZaRggkVrCnUd1s4V0C+F4s66nE5Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T09:08:16.657795Z","bundle_sha256":"80eb6b12ba5f1d27b52dda6b770d6502f333728d2ec7ffeac6700989a0317324"}}