{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:3TNDUXXOY2LZ6JA577T6MFISCN","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":"17f22f653ad44d9933d4196d246e2e4b9bc8c333a37d0665fee420d16ea67d97","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-13T14:53:01Z","title_canon_sha256":"d79a6a0cfe06375839938cfc2c683de6c984b8726e5678ac07280b5b5beb4e07"},"schema_version":"1.0","source":{"id":"2009.06010","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.06010","created_at":"2026-07-05T02:08:19Z"},{"alias_kind":"arxiv_version","alias_value":"2009.06010v2","created_at":"2026-07-05T02:08:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.06010","created_at":"2026-07-05T02:08:19Z"},{"alias_kind":"pith_short_12","alias_value":"3TNDUXXOY2LZ","created_at":"2026-07-05T02:08:19Z"},{"alias_kind":"pith_short_16","alias_value":"3TNDUXXOY2LZ6JA5","created_at":"2026-07-05T02:08:19Z"},{"alias_kind":"pith_short_8","alias_value":"3TNDUXXO","created_at":"2026-07-05T02:08:19Z"}],"graph_snapshots":[{"event_id":"sha256:4a68168227fceff784c8dcb63fe81fc050a895cc519bc35193eb26d5bf9f00a1","target":"graph","created_at":"2026-07-05T02:08:19Z","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/2009.06010/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As one of the key communication scenarios in the 5th and also the 6th generation (6G) of mobile communication networks, ultra-reliable and low-latency communications (URLLC) will be central for the development of various emerging mission-critical applications. State-of-the-art mobile communication systems do not fulfill the end-to-end delay and overall reliability requirements of URLLC. In particular, a holistic framework that takes into account latency, reliability, availability, scalability, and decision making under uncertainty is lacking. Driven by recent breakthroughs in deep neural netwo","authors_text":"Branka Vucetic, Changyang She, Chengjian Sun, Chenyang Yang, H. Vincent Poor, Yonghui Li, Zhouyou Gu","cross_cats":["cs.IT","cs.LG","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-13T14:53:01Z","title":"A Tutorial on Ultra-Reliable and Low-Latency Communications in 6G: Integrating Domain Knowledge into Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.06010","kind":"arxiv","version":2},"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":"sha256:5eb5aeff9813ce7f2d5340f605c56571006c4d7bf018d003989770773cb10f68","target":"record","created_at":"2026-07-05T02:08:19Z","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":"17f22f653ad44d9933d4196d246e2e4b9bc8c333a37d0665fee420d16ea67d97","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-13T14:53:01Z","title_canon_sha256":"d79a6a0cfe06375839938cfc2c683de6c984b8726e5678ac07280b5b5beb4e07"},"schema_version":"1.0","source":{"id":"2009.06010","kind":"arxiv","version":2}},"canonical_sha256":"dcda3a5eeec6979f241dffe7e6151213463ac595de31eb9ac3a1491aebd2a18b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dcda3a5eeec6979f241dffe7e6151213463ac595de31eb9ac3a1491aebd2a18b","first_computed_at":"2026-07-05T02:08:19.979967Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:08:19.979967Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BrRnb0gXe+Cms2Z2ji6SitVnjW43BOP1DybGIznjc4jDtmbCouuWrH2EnPEEs3oO57UypF0VQEpHcr6XZHRRBg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:08:19.980408Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.06010","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5eb5aeff9813ce7f2d5340f605c56571006c4d7bf018d003989770773cb10f68","sha256:4a68168227fceff784c8dcb63fe81fc050a895cc519bc35193eb26d5bf9f00a1"],"state_sha256":"43ad55b79fc0f8937be5f88d7e8937a57b47f568fa84fd9a977a1fc9d12374ca"}