{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2AW4KWO4A3ETGPQ5LRQRFW4QNR","short_pith_number":"pith:2AW4KWO4","canonical_record":{"source":{"id":"2412.08642","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-12-11T18:59:50Z","cross_cats_sorted":["cs.LG","cs.NI","math.IT"],"title_canon_sha256":"4f2e79bb494c30b4675362e15b038fec4a1d9ded62a5aec263d54b8f1924668d","abstract_canon_sha256":"89e872befefda286a7c72e7666b85b4d5fa52caded4cdad1ddffa38590bf65a4"},"schema_version":"1.0"},"canonical_sha256":"d02dc559dc06c9333e1d5c6112db906c7a9117d37fb1301b9d765953b96e27dc","source":{"kind":"arxiv","id":"2412.08642","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08642","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08642v1","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08642","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"2AW4KWO4A3ET","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"2AW4KWO4A3ETGPQ5","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"2AW4KWO4","created_at":"2026-07-05T09:47:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2AW4KWO4A3ETGPQ5LRQRFW4QNR","target":"record","payload":{"canonical_record":{"source":{"id":"2412.08642","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-12-11T18:59:50Z","cross_cats_sorted":["cs.LG","cs.NI","math.IT"],"title_canon_sha256":"4f2e79bb494c30b4675362e15b038fec4a1d9ded62a5aec263d54b8f1924668d","abstract_canon_sha256":"89e872befefda286a7c72e7666b85b4d5fa52caded4cdad1ddffa38590bf65a4"},"schema_version":"1.0"},"canonical_sha256":"d02dc559dc06c9333e1d5c6112db906c7a9117d37fb1301b9d765953b96e27dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:47:52.807778Z","signature_b64":"dQ34wZzZSq/Ahh8ZrUB500bXfIA1QVliK7RFJA+BZHQTSpTKU8MXRkylH3VlPUx/QnK8h5sNyqexB3TwmTYdDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d02dc559dc06c9333e1d5c6112db906c7a9117d37fb1301b9d765953b96e27dc","last_reissued_at":"2026-07-05T09:47:52.807298Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:47:52.807298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.08642","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":"2026-07-05T09:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ODjiQcwRaNUI4LmKf9MUt6RUpdhWy/98ZTlpy/wsTnaVzy61Tohf0wJmhuHmw7oxKGRwnJzkJgoe2RlYmyDaAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:50:57.722343Z"},"content_sha256":"05707d5cd2eb477eee7ca4dbbcc3c89f5a56ef5adf4ae27eec31f27e174a4c60","schema_version":"1.0","event_id":"sha256:05707d5cd2eb477eee7ca4dbbcc3c89f5a56ef5adf4ae27eec31f27e174a4c60"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2AW4KWO4A3ETGPQ5LRQRFW4QNR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generative Semantic Communication: Architectures, Technologies, and Applications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NI","math.IT"],"primary_cat":"cs.IT","authors_text":"Chongjie Wang, Fangxin Wang, Hongyang Du, Jinke Ren, Shuguang Cui, Weiwen Yuan, Xianda Wang, Yaping Sun, Yingbin Zhou, Ziwei Zhu","submitted_at":"2024-12-11T18:59:50Z","abstract_excerpt":"This paper delves into the applications of generative artificial intelligence (GAI) in semantic communication (SemCom) and presents a thorough study. Three popular SemCom systems enabled by classical GAI models are first introduced, including variational autoencoders, generative adversarial networks, and diffusion models. For each system, the fundamental concept of the GAI model, the corresponding SemCom architecture, and the associated literature review of recent efforts are elucidated. Then, a novel generative SemCom system is proposed by incorporating the cutting-edge GAI technology-large l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08642","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/2412.08642/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":"2026-07-05T09:47:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ea0I/fRa5xidQCXNEgSKSH44fOwbBLH8P5QoZnCkrdR7/kb/U++c0tIhaL6IHDXnXnPu+TFQ7ayeO6hJTdPUDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:50:57.722891Z"},"content_sha256":"621252fd411fca957f13b39a61449ebe070b75ec84dc21bbb4e611a2e3e0aa1a","schema_version":"1.0","event_id":"sha256:621252fd411fca957f13b39a61449ebe070b75ec84dc21bbb4e611a2e3e0aa1a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/bundle.json","state_url":"https://pith.science/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/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":"2026-08-09T22:50:57Z","links":{"resolver":"https://pith.science/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR","bundle":"https://pith.science/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/bundle.json","state":"https://pith.science/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2AW4KWO4A3ETGPQ5LRQRFW4QNR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2AW4KWO4A3ETGPQ5LRQRFW4QNR","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":"89e872befefda286a7c72e7666b85b4d5fa52caded4cdad1ddffa38590bf65a4","cross_cats_sorted":["cs.LG","cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-12-11T18:59:50Z","title_canon_sha256":"4f2e79bb494c30b4675362e15b038fec4a1d9ded62a5aec263d54b8f1924668d"},"schema_version":"1.0","source":{"id":"2412.08642","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.08642","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"arxiv_version","alias_value":"2412.08642v1","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08642","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_12","alias_value":"2AW4KWO4A3ET","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_16","alias_value":"2AW4KWO4A3ETGPQ5","created_at":"2026-07-05T09:47:52Z"},{"alias_kind":"pith_short_8","alias_value":"2AW4KWO4","created_at":"2026-07-05T09:47:52Z"}],"graph_snapshots":[{"event_id":"sha256:621252fd411fca957f13b39a61449ebe070b75ec84dc21bbb4e611a2e3e0aa1a","target":"graph","created_at":"2026-07-05T09:47:52Z","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/2412.08642/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper delves into the applications of generative artificial intelligence (GAI) in semantic communication (SemCom) and presents a thorough study. Three popular SemCom systems enabled by classical GAI models are first introduced, including variational autoencoders, generative adversarial networks, and diffusion models. For each system, the fundamental concept of the GAI model, the corresponding SemCom architecture, and the associated literature review of recent efforts are elucidated. Then, a novel generative SemCom system is proposed by incorporating the cutting-edge GAI technology-large l","authors_text":"Chongjie Wang, Fangxin Wang, Hongyang Du, Jinke Ren, Shuguang Cui, Weiwen Yuan, Xianda Wang, Yaping Sun, Yingbin Zhou, Ziwei Zhu","cross_cats":["cs.LG","cs.NI","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-12-11T18:59:50Z","title":"Generative Semantic Communication: Architectures, Technologies, and Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08642","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":"sha256:05707d5cd2eb477eee7ca4dbbcc3c89f5a56ef5adf4ae27eec31f27e174a4c60","target":"record","created_at":"2026-07-05T09:47:52Z","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":"89e872befefda286a7c72e7666b85b4d5fa52caded4cdad1ddffa38590bf65a4","cross_cats_sorted":["cs.LG","cs.NI","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-12-11T18:59:50Z","title_canon_sha256":"4f2e79bb494c30b4675362e15b038fec4a1d9ded62a5aec263d54b8f1924668d"},"schema_version":"1.0","source":{"id":"2412.08642","kind":"arxiv","version":1}},"canonical_sha256":"d02dc559dc06c9333e1d5c6112db906c7a9117d37fb1301b9d765953b96e27dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d02dc559dc06c9333e1d5c6112db906c7a9117d37fb1301b9d765953b96e27dc","first_computed_at":"2026-07-05T09:47:52.807298Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:47:52.807298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dQ34wZzZSq/Ahh8ZrUB500bXfIA1QVliK7RFJA+BZHQTSpTKU8MXRkylH3VlPUx/QnK8h5sNyqexB3TwmTYdDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:47:52.807778Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.08642","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:05707d5cd2eb477eee7ca4dbbcc3c89f5a56ef5adf4ae27eec31f27e174a4c60","sha256:621252fd411fca957f13b39a61449ebe070b75ec84dc21bbb4e611a2e3e0aa1a"],"state_sha256":"ebaba897355614835bb8bb07e175730d343b5d3f496ee402a73045145ad72370"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3IC2Hpga8LBPZ+ujr0qYmfXI8vMxUrVKfBnjZxC2MbqBc9lSx5zvQ2CrJFs6hg0w9WO8JAsuGWi4ovHTVUzeCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T22:50:57.726991Z","bundle_sha256":"5942d6cfd62aadb0abece9026986689f3545a9375772cead68065737123786d4"}}