{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:T6G2QFAQZJURXFOT3I6E3Z2Q2B","short_pith_number":"pith:T6G2QFAQ","canonical_record":{"source":{"id":"2606.20098","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2026-06-18T11:16:51Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"df5d69f57a3c8fad6caf75d89a6b82ff693abecca6f6cd3e39398a6105367621","abstract_canon_sha256":"fe701c92a80c1b6541195ced7c3484075de800d424897a9386aa210d5f9fd400"},"schema_version":"1.0"},"canonical_sha256":"9f8da81410ca691b95d3da3c4de750d05b1f42b90febc85f19f2a7f7ca87b2a5","source":{"kind":"arxiv","id":"2606.20098","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20098","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20098v1","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20098","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_12","alias_value":"T6G2QFAQZJUR","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_16","alias_value":"T6G2QFAQZJURXFOT","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_8","alias_value":"T6G2QFAQ","created_at":"2026-06-19T16:13:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:T6G2QFAQZJURXFOT3I6E3Z2Q2B","target":"record","payload":{"canonical_record":{"source":{"id":"2606.20098","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2026-06-18T11:16:51Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"df5d69f57a3c8fad6caf75d89a6b82ff693abecca6f6cd3e39398a6105367621","abstract_canon_sha256":"fe701c92a80c1b6541195ced7c3484075de800d424897a9386aa210d5f9fd400"},"schema_version":"1.0"},"canonical_sha256":"9f8da81410ca691b95d3da3c4de750d05b1f42b90febc85f19f2a7f7ca87b2a5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:13:02.823386Z","signature_b64":"3+02/ytdH33qs/ow2MDC8WtkfTm+suWqb1FVtzNlZ1RFgctt9WeFwWNZg3PQvDtTxMKpX+p6LBzve5SBj5CbDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f8da81410ca691b95d3da3c4de750d05b1f42b90febc85f19f2a7f7ca87b2a5","last_reissued_at":"2026-06-19T16:13:02.823027Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:13:02.823027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.20098","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":"2026-06-19T16:13:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G55TGeiAv86LaKpF/xysT10sQP3eBX4bxYh/mh2VDTH5GvaZfE9mw/O+FfCLnulUhXHPRJfxlZEw+xMOyvwKDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T12:16:27.318115Z"},"content_sha256":"90b395e50ff18aaabac9bc8708bd9d48f00c3ea4960f563b1b4fb35fd0df78e9","schema_version":"1.0","event_id":"sha256:90b395e50ff18aaabac9bc8708bd9d48f00c3ea4960f563b1b4fb35fd0df78e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:T6G2QFAQZJURXFOT3I6E3Z2Q2B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Site-Specific MIMO Channel Generation via Diffusion and Flow Matching: Fidelity, Efficiency, and Downstream Utility","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Angel Lozano, Firdous Bin Ismail, Giovanni Geraci, Masoud Sadeghian, Paul Almasan, Sina Beyraghi","submitted_at":"2026-06-18T11:16:51Z","abstract_excerpt":"This paper explores the use of generative models to synthesize high-quality, site-specific multiple-input multiple-output (MIMO) channel data, addressing the high cost of the extensive measurement campaigns required to acquire real-world data for AI-native wireless networks. Two location-conditioned generative paradigms are compared: a conditional denoising diffusion implicit model (cDDIM), and a conditional flow matching model (cFMM). Both these models generate MIMO channel matrices conditioned on user coordinates, to preserve the spatial structure of the deployment site. The approaches are e"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20098","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/2606.20098/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":"2026-06-19T16:13:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0QG2gZt9ebPD2K5saPzRDpWKoFLIEwI/pTjzuqMzKUSVYovhpLDapHA7uR7RJkRPZ688dCYmpwq1Akxr6kvQAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T12:16:27.318525Z"},"content_sha256":"62d953913750a1c3bfa22ef678015b233d0a71672a6d69dc51e0b28bd1735497","schema_version":"1.0","event_id":"sha256:62d953913750a1c3bfa22ef678015b233d0a71672a6d69dc51e0b28bd1735497"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/bundle.json","state_url":"https://pith.science/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/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":"2026-07-01T12:16:27Z","links":{"resolver":"https://pith.science/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B","bundle":"https://pith.science/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/bundle.json","state":"https://pith.science/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T6G2QFAQZJURXFOT3I6E3Z2Q2B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:T6G2QFAQZJURXFOT3I6E3Z2Q2B","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":"fe701c92a80c1b6541195ced7c3484075de800d424897a9386aa210d5f9fd400","cross_cats_sorted":["eess.SP","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2026-06-18T11:16:51Z","title_canon_sha256":"df5d69f57a3c8fad6caf75d89a6b82ff693abecca6f6cd3e39398a6105367621"},"schema_version":"1.0","source":{"id":"2606.20098","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20098","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20098v1","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20098","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_12","alias_value":"T6G2QFAQZJUR","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_16","alias_value":"T6G2QFAQZJURXFOT","created_at":"2026-06-19T16:13:02Z"},{"alias_kind":"pith_short_8","alias_value":"T6G2QFAQ","created_at":"2026-06-19T16:13:02Z"}],"graph_snapshots":[{"event_id":"sha256:62d953913750a1c3bfa22ef678015b233d0a71672a6d69dc51e0b28bd1735497","target":"graph","created_at":"2026-06-19T16:13:02Z","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/2606.20098/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper explores the use of generative models to synthesize high-quality, site-specific multiple-input multiple-output (MIMO) channel data, addressing the high cost of the extensive measurement campaigns required to acquire real-world data for AI-native wireless networks. Two location-conditioned generative paradigms are compared: a conditional denoising diffusion implicit model (cDDIM), and a conditional flow matching model (cFMM). Both these models generate MIMO channel matrices conditioned on user coordinates, to preserve the spatial structure of the deployment site. The approaches are e","authors_text":"Angel Lozano, Firdous Bin Ismail, Giovanni Geraci, Masoud Sadeghian, Paul Almasan, Sina Beyraghi","cross_cats":["eess.SP","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2026-06-18T11:16:51Z","title":"Site-Specific MIMO Channel Generation via Diffusion and Flow Matching: Fidelity, Efficiency, and Downstream Utility"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20098","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":"sha256:90b395e50ff18aaabac9bc8708bd9d48f00c3ea4960f563b1b4fb35fd0df78e9","target":"record","created_at":"2026-06-19T16:13:02Z","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":"fe701c92a80c1b6541195ced7c3484075de800d424897a9386aa210d5f9fd400","cross_cats_sorted":["eess.SP","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2026-06-18T11:16:51Z","title_canon_sha256":"df5d69f57a3c8fad6caf75d89a6b82ff693abecca6f6cd3e39398a6105367621"},"schema_version":"1.0","source":{"id":"2606.20098","kind":"arxiv","version":1}},"canonical_sha256":"9f8da81410ca691b95d3da3c4de750d05b1f42b90febc85f19f2a7f7ca87b2a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f8da81410ca691b95d3da3c4de750d05b1f42b90febc85f19f2a7f7ca87b2a5","first_computed_at":"2026-06-19T16:13:02.823027Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:13:02.823027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3+02/ytdH33qs/ow2MDC8WtkfTm+suWqb1FVtzNlZ1RFgctt9WeFwWNZg3PQvDtTxMKpX+p6LBzve5SBj5CbDQ==","signature_status":"signed_v1","signed_at":"2026-06-19T16:13:02.823386Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.20098","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90b395e50ff18aaabac9bc8708bd9d48f00c3ea4960f563b1b4fb35fd0df78e9","sha256:62d953913750a1c3bfa22ef678015b233d0a71672a6d69dc51e0b28bd1735497"],"state_sha256":"46d8bea387260369d412d5943b6493dc40543061f9099267ced357d4a474dadb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nMKerBH0IEkEZYXLXdQBSb5Qvv0iRqfZXDmLX4drPTC1swj5BqG9+f+y4cO8Xiy0izpwu7In5SxxqF35b8pVDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T12:16:27.320953Z","bundle_sha256":"deb95c16e9a1083c29f718a5f9bc3f990285e60f9fba973971eae42e1238d093"}}