{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:OXCH4EYA25LC7S33JI6FF5FAP3","short_pith_number":"pith:OXCH4EYA","canonical_record":{"source":{"id":"2508.01586","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-03T04:59:58Z","cross_cats_sorted":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"title_canon_sha256":"05e05aefa8c78fa95092ec42ec99cb809ac3cb2106ef00107a7be16480411ce9","abstract_canon_sha256":"8923bd67f7070adcab265a137f911f6cd03257eaefd544ab952e29aa7231cdea"},"schema_version":"1.0"},"canonical_sha256":"75c47e1300d7562fcb7b4a3c52f4a07ec83da13a84288a2fc8c4651cb247715f","source":{"kind":"arxiv","id":"2508.01586","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01586","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01586v1","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01586","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_12","alias_value":"OXCH4EYA25LC","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_16","alias_value":"OXCH4EYA25LC7S33","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_8","alias_value":"OXCH4EYA","created_at":"2026-07-05T11:47:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:OXCH4EYA25LC7S33JI6FF5FAP3","target":"record","payload":{"canonical_record":{"source":{"id":"2508.01586","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-03T04:59:58Z","cross_cats_sorted":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"title_canon_sha256":"05e05aefa8c78fa95092ec42ec99cb809ac3cb2106ef00107a7be16480411ce9","abstract_canon_sha256":"8923bd67f7070adcab265a137f911f6cd03257eaefd544ab952e29aa7231cdea"},"schema_version":"1.0"},"canonical_sha256":"75c47e1300d7562fcb7b4a3c52f4a07ec83da13a84288a2fc8c4651cb247715f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:47:41.757327Z","signature_b64":"B+UvYOiuxHfrhJVdYNo0/gILIBCk9HBomEWx6Jn8+2LN+PAx7f3eugGIjgxxiitrPZ6Yqa1EYpbalSGlItCtAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"75c47e1300d7562fcb7b4a3c52f4a07ec83da13a84288a2fc8c4651cb247715f","last_reissued_at":"2026-07-05T11:47:41.756801Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:47:41.756801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.01586","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":"2026-07-05T11:47:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AtCEVfw8XZc0Pv9YRQRPsS1e87gcY0rImqsRT1aWZ3iwgt6b6DBZeA2mnGasfT/DpFT2cEoM9JLkvhKRDbZnCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T09:13:48.766184Z"},"content_sha256":"9adda6a1621a842570f5c94d765593c4dec134c17fad62801ee9dce79527cef1","schema_version":"1.0","event_id":"sha256:9adda6a1621a842570f5c94d765593c4dec134c17fad62801ee9dce79527cef1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:OXCH4EYA25LC7S33JI6FF5FAP3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Diffusion Models for Future Networks and Communications: A Comprehensive Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"primary_cat":"cs.LG","authors_text":"Dong In Kim, Duc Van Le, Dusit Niyato, Huy T. Nguyen, Marco Di Renzo, Nguyen Cong Luong, Nguyen Duc Duy Anh, Nguyen Duc Hai, Quoc-Viet Pham, Ruichen Zhang, Thai-Hoc Vu, Thien Huynh-The","submitted_at":"2025-08-03T04:59:58Z","abstract_excerpt":"The rise of Generative AI (GenAI) in recent years has catalyzed transformative advances in wireless communications and networks. Among the members of the GenAI family, Diffusion Models (DMs) have risen to prominence as a powerful option, capable of handling complex, high-dimensional data distribution, as well as consistent, noise-robust performance. In this survey, we aim to provide a comprehensive overview of the theoretical foundations and practical applications of DMs across future communication systems. We first provide an extensive tutorial of DMs and demonstrate how they can be applied t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01586","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/2508.01586/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":"2026-07-05T11:47:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gpg5beBOm/UiILvuygt9Rkm35X2U50C1HWiWXnF20/wLTJatgDzxE0uWaltu88FfomSJu6qyi7QLYliZAXYfAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T09:13:48.767271Z"},"content_sha256":"3e30dc5edc0e0aa59ab5911d636407d5bff6966115669f059429efaec681d52c","schema_version":"1.0","event_id":"sha256:3e30dc5edc0e0aa59ab5911d636407d5bff6966115669f059429efaec681d52c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OXCH4EYA25LC7S33JI6FF5FAP3/bundle.json","state_url":"https://pith.science/pith/OXCH4EYA25LC7S33JI6FF5FAP3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OXCH4EYA25LC7S33JI6FF5FAP3/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":"2026-08-12T09:13:48Z","links":{"resolver":"https://pith.science/pith/OXCH4EYA25LC7S33JI6FF5FAP3","bundle":"https://pith.science/pith/OXCH4EYA25LC7S33JI6FF5FAP3/bundle.json","state":"https://pith.science/pith/OXCH4EYA25LC7S33JI6FF5FAP3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OXCH4EYA25LC7S33JI6FF5FAP3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:OXCH4EYA25LC7S33JI6FF5FAP3","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":"8923bd67f7070adcab265a137f911f6cd03257eaefd544ab952e29aa7231cdea","cross_cats_sorted":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-03T04:59:58Z","title_canon_sha256":"05e05aefa8c78fa95092ec42ec99cb809ac3cb2106ef00107a7be16480411ce9"},"schema_version":"1.0","source":{"id":"2508.01586","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.01586","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"arxiv_version","alias_value":"2508.01586v1","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.01586","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_12","alias_value":"OXCH4EYA25LC","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_16","alias_value":"OXCH4EYA25LC7S33","created_at":"2026-07-05T11:47:41Z"},{"alias_kind":"pith_short_8","alias_value":"OXCH4EYA","created_at":"2026-07-05T11:47:41Z"}],"graph_snapshots":[{"event_id":"sha256:3e30dc5edc0e0aa59ab5911d636407d5bff6966115669f059429efaec681d52c","target":"graph","created_at":"2026-07-05T11:47:41Z","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/2508.01586/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rise of Generative AI (GenAI) in recent years has catalyzed transformative advances in wireless communications and networks. Among the members of the GenAI family, Diffusion Models (DMs) have risen to prominence as a powerful option, capable of handling complex, high-dimensional data distribution, as well as consistent, noise-robust performance. In this survey, we aim to provide a comprehensive overview of the theoretical foundations and practical applications of DMs across future communication systems. We first provide an extensive tutorial of DMs and demonstrate how they can be applied t","authors_text":"Dong In Kim, Duc Van Le, Dusit Niyato, Huy T. Nguyen, Marco Di Renzo, Nguyen Cong Luong, Nguyen Duc Duy Anh, Nguyen Duc Hai, Quoc-Viet Pham, Ruichen Zhang, Thai-Hoc Vu, Thien Huynh-The","cross_cats":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-03T04:59:58Z","title":"Diffusion Models for Future Networks and Communications: A Comprehensive Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.01586","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":"sha256:9adda6a1621a842570f5c94d765593c4dec134c17fad62801ee9dce79527cef1","target":"record","created_at":"2026-07-05T11:47:41Z","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":"8923bd67f7070adcab265a137f911f6cd03257eaefd544ab952e29aa7231cdea","cross_cats_sorted":["cs.AI","cs.ET","cs.IT","cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-03T04:59:58Z","title_canon_sha256":"05e05aefa8c78fa95092ec42ec99cb809ac3cb2106ef00107a7be16480411ce9"},"schema_version":"1.0","source":{"id":"2508.01586","kind":"arxiv","version":1}},"canonical_sha256":"75c47e1300d7562fcb7b4a3c52f4a07ec83da13a84288a2fc8c4651cb247715f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"75c47e1300d7562fcb7b4a3c52f4a07ec83da13a84288a2fc8c4651cb247715f","first_computed_at":"2026-07-05T11:47:41.756801Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:47:41.756801Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"B+UvYOiuxHfrhJVdYNo0/gILIBCk9HBomEWx6Jn8+2LN+PAx7f3eugGIjgxxiitrPZ6Yqa1EYpbalSGlItCtAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:47:41.757327Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.01586","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9adda6a1621a842570f5c94d765593c4dec134c17fad62801ee9dce79527cef1","sha256:3e30dc5edc0e0aa59ab5911d636407d5bff6966115669f059429efaec681d52c"],"state_sha256":"4f5b0876ba425668b368353e6a8cac4c43a924d7de21d54842b6dca274f542bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d//R5yXyHrjazlaGHp2dtDKqjmn/Kk3oXNbcDgkWu2YZFoLc1a3ETmn3xrXABkJ6K+iPOUWpgpfI8ZwicNb9AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T09:13:48.772627Z","bundle_sha256":"288fc448a35f65799399d99d516a66d2327c6eeef424836a9263240f7176dd95"}}