{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5LALXY6XXXUZS5FNDBM3MTVNLT","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":"2bb05476bbdd42fc86cc0ead2d83750e4c8542808daf421dde0c2f1734f4ffc0","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2022-08-03T15:45:02Z","title_canon_sha256":"cbf18afd04d4f30fae71cce4188b5f2da86b9947c7fd33bb598ba05e4ab44bb1"},"schema_version":"1.0","source":{"id":"2208.02157","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.02157","created_at":"2026-07-05T05:28:08Z"},{"alias_kind":"arxiv_version","alias_value":"2208.02157v4","created_at":"2026-07-05T05:28:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.02157","created_at":"2026-07-05T05:28:08Z"},{"alias_kind":"pith_short_12","alias_value":"5LALXY6XXXUZ","created_at":"2026-07-05T05:28:08Z"},{"alias_kind":"pith_short_16","alias_value":"5LALXY6XXXUZS5FN","created_at":"2026-07-05T05:28:08Z"},{"alias_kind":"pith_short_8","alias_value":"5LALXY6X","created_at":"2026-07-05T05:28:08Z"}],"graph_snapshots":[{"event_id":"sha256:4473699bbb5b353ef26d32dd5d4a72f169c16d497af6db72b1eb97beacdcf830","target":"graph","created_at":"2026-07-05T05:28:08Z","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/2208.02157/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Integrating sensing and communication is a defining theme for future wireless systems. This is motivated by the promising performance gains, especially as they assist each other, and by the better utilization of the wireless and hardware resources. Realizing these gains in practice, however, is subject to several challenges where leveraging machine learning can provide a potential solution. This article focuses on ten key machine learning roles for joint sensing and communication, sensing-aided communication, and communication-aided sensing systems, explains why and how machine learning can be","authors_text":"Ahmed Alkhateeb, Umut Demirhan","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2022-08-03T15:45:02Z","title":"Integrated Sensing and Communication for 6G: Ten Key Machine Learning Roles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.02157","kind":"arxiv","version":4},"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:ab6246a67fb65ef37cae0de3e08cf2ba0de73380d841ab7cf8c1b738886e314b","target":"record","created_at":"2026-07-05T05:28:08Z","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":"2bb05476bbdd42fc86cc0ead2d83750e4c8542808daf421dde0c2f1734f4ffc0","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2022-08-03T15:45:02Z","title_canon_sha256":"cbf18afd04d4f30fae71cce4188b5f2da86b9947c7fd33bb598ba05e4ab44bb1"},"schema_version":"1.0","source":{"id":"2208.02157","kind":"arxiv","version":4}},"canonical_sha256":"eac0bbe3d7bde99974ad1859b64ead5cfdfddd7e6013295d523df1122c938f27","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eac0bbe3d7bde99974ad1859b64ead5cfdfddd7e6013295d523df1122c938f27","first_computed_at":"2026-07-05T05:28:08.483705Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:28:08.483705Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"91KFlAudJBsqx0kC3vlkd2TBvMUhTFl6SBlYlyjIKmS/FA1sn+BepUeprRqdiJvE2dlZOA3X1vaK3Y+HvQCKBw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:28:08.484074Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.02157","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab6246a67fb65ef37cae0de3e08cf2ba0de73380d841ab7cf8c1b738886e314b","sha256:4473699bbb5b353ef26d32dd5d4a72f169c16d497af6db72b1eb97beacdcf830"],"state_sha256":"8ee44f9d1e233c35d6b736194bc403c6c8f166bd15247c3b3b37548a4ac9c174"}