{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:R4JMCX4XJ2VUDN6QXYMEZ5QNKU","short_pith_number":"pith:R4JMCX4X","canonical_record":{"source":{"id":"2301.03377","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2023-01-03T13:56:50Z","cross_cats_sorted":["cs.LG","cs.NI"],"title_canon_sha256":"7f0f59e52cad6c59ec0806461750c84c248d4efc3d0cdff179b117fb28539b32","abstract_canon_sha256":"9c0116b8ecca629a8d53fa2d19a204e467ac9d758f27b5ddaac9938014671c1c"},"schema_version":"1.0"},"canonical_sha256":"8f12c15f974eab41b7d0be184cf60d553a52ab33d729e65f853670f413a37045","source":{"kind":"arxiv","id":"2301.03377","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.03377","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"arxiv_version","alias_value":"2301.03377v1","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.03377","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_12","alias_value":"R4JMCX4XJ2VU","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"R4JMCX4XJ2VUDN6Q","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"R4JMCX4X","created_at":"2026-07-05T05:31:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:R4JMCX4XJ2VUDN6QXYMEZ5QNKU","target":"record","payload":{"canonical_record":{"source":{"id":"2301.03377","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2023-01-03T13:56:50Z","cross_cats_sorted":["cs.LG","cs.NI"],"title_canon_sha256":"7f0f59e52cad6c59ec0806461750c84c248d4efc3d0cdff179b117fb28539b32","abstract_canon_sha256":"9c0116b8ecca629a8d53fa2d19a204e467ac9d758f27b5ddaac9938014671c1c"},"schema_version":"1.0"},"canonical_sha256":"8f12c15f974eab41b7d0be184cf60d553a52ab33d729e65f853670f413a37045","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:31:28.906591Z","signature_b64":"IFPFPS8kGEtohl2hqM3PeZkhPdI51TSTkynvS8/u8eQHLVxBAU7sy6VxvCOakSayEHWjQLJmrjEDOG7FCVUrDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8f12c15f974eab41b7d0be184cf60d553a52ab33d729e65f853670f413a37045","last_reissued_at":"2026-07-05T05:31:28.906145Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:31:28.906145Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.03377","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":"2026-07-05T05:31:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lvb13jgJyobvVeBTDR+UBUOR2Kd/hcKzF5TZcZe6cqzjn7GI6tAhp9JLOiNKXsuy+fDA0/Ezx4ySfTzZRUu1Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:37:48.722445Z"},"content_sha256":"177e1ba702025fde77364bfd9e43198650a39df403f8e23b74feeb7a7748f3be","schema_version":"1.0","event_id":"sha256:177e1ba702025fde77364bfd9e43198650a39df403f8e23b74feeb7a7748f3be"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:R4JMCX4XJ2VUDN6QXYMEZ5QNKU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Machine Learning for Large-Scale Optimization in 6G Wireless Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NI"],"primary_cat":"eess.SP","authors_text":"Jun Zhang, Lin Bai, Liqun Fu, Lixiang Lian, Wei Zhang, Yandong Shi, Yong Zhou, Yuanming Shi, Zixin Wang","submitted_at":"2023-01-03T13:56:50Z","abstract_excerpt":"The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from \"connected things\" to \"connected intelligence\", featured by ultra high density, large-scale, dynamic heterogeneity, diversified functional requirements and machine learning capabilities, which leads to a growing need for highly efficient intelligent algorithms. The classic optimization-based algorithms usually require highly precise mathematical model of data links and suffer from poor performance with high computational cost in realistic 6G applications. Based on domain knowledge (e.g., optimization mo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.03377","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2301.03377/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":"2026-07-05T05:31:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Jgr5VBqT/ORXsyc0ag4+h73Lg6cSYHt8ql+Yw7lbFhLo1FFzhRrJKxi/vnuXMo8zXk/ZZfNFE9AzV0lr9yD1Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T15:37:48.723234Z"},"content_sha256":"f5ffde46fc9d8986cbe9c9ba87945a442526578e542e6a2cb8269d407f69be1f","schema_version":"1.0","event_id":"sha256:f5ffde46fc9d8986cbe9c9ba87945a442526578e542e6a2cb8269d407f69be1f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/bundle.json","state_url":"https://pith.science/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/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":"2026-08-05T15:37:48Z","links":{"resolver":"https://pith.science/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU","bundle":"https://pith.science/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/bundle.json","state":"https://pith.science/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R4JMCX4XJ2VUDN6QXYMEZ5QNKU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:R4JMCX4XJ2VUDN6QXYMEZ5QNKU","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":"9c0116b8ecca629a8d53fa2d19a204e467ac9d758f27b5ddaac9938014671c1c","cross_cats_sorted":["cs.LG","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2023-01-03T13:56:50Z","title_canon_sha256":"7f0f59e52cad6c59ec0806461750c84c248d4efc3d0cdff179b117fb28539b32"},"schema_version":"1.0","source":{"id":"2301.03377","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.03377","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"arxiv_version","alias_value":"2301.03377v1","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.03377","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_12","alias_value":"R4JMCX4XJ2VU","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"R4JMCX4XJ2VUDN6Q","created_at":"2026-07-05T05:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"R4JMCX4X","created_at":"2026-07-05T05:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:f5ffde46fc9d8986cbe9c9ba87945a442526578e542e6a2cb8269d407f69be1f","target":"graph","created_at":"2026-07-05T05:31:28Z","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/2301.03377/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from \"connected things\" to \"connected intelligence\", featured by ultra high density, large-scale, dynamic heterogeneity, diversified functional requirements and machine learning capabilities, which leads to a growing need for highly efficient intelligent algorithms. The classic optimization-based algorithms usually require highly precise mathematical model of data links and suffer from poor performance with high computational cost in realistic 6G applications. Based on domain knowledge (e.g., optimization mo","authors_text":"Jun Zhang, Lin Bai, Liqun Fu, Lixiang Lian, Wei Zhang, Yandong Shi, Yong Zhou, Yuanming Shi, Zixin Wang","cross_cats":["cs.LG","cs.NI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2023-01-03T13:56:50Z","title":"Machine Learning for Large-Scale Optimization in 6G Wireless Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.03377","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":"sha256:177e1ba702025fde77364bfd9e43198650a39df403f8e23b74feeb7a7748f3be","target":"record","created_at":"2026-07-05T05:31:28Z","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":"9c0116b8ecca629a8d53fa2d19a204e467ac9d758f27b5ddaac9938014671c1c","cross_cats_sorted":["cs.LG","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2023-01-03T13:56:50Z","title_canon_sha256":"7f0f59e52cad6c59ec0806461750c84c248d4efc3d0cdff179b117fb28539b32"},"schema_version":"1.0","source":{"id":"2301.03377","kind":"arxiv","version":1}},"canonical_sha256":"8f12c15f974eab41b7d0be184cf60d553a52ab33d729e65f853670f413a37045","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8f12c15f974eab41b7d0be184cf60d553a52ab33d729e65f853670f413a37045","first_computed_at":"2026-07-05T05:31:28.906145Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:31:28.906145Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IFPFPS8kGEtohl2hqM3PeZkhPdI51TSTkynvS8/u8eQHLVxBAU7sy6VxvCOakSayEHWjQLJmrjEDOG7FCVUrDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:31:28.906591Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.03377","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:177e1ba702025fde77364bfd9e43198650a39df403f8e23b74feeb7a7748f3be","sha256:f5ffde46fc9d8986cbe9c9ba87945a442526578e542e6a2cb8269d407f69be1f"],"state_sha256":"0d5194636f9f95458e14948644d06c193234bdfd2501ba0f44de467f3c71f65d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JcSMqEvtAvFeFcxT/i7k0587u4wHvb82+Fk6HMlwtAnhDOBVNPLObboKy2ifmlwwFJNvMvrPMSyDX9ClX+e7Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T15:37:48.727631Z","bundle_sha256":"cf093f87585f2535a5c160d46250ce57f4d674a4d322a0b4a1c6e6c53d9348b8"}}