{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:H7GPNCC6IX3ZDRPOVXQN4RSAQM","short_pith_number":"pith:H7GPNCC6","canonical_record":{"source":{"id":"2404.13281","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-04-20T05:54:40Z","cross_cats_sorted":[],"title_canon_sha256":"fe5d8ab9abd49054c95bc963ec48d9fa6c9315134bcc37f8fd4a3b3b757f62fe","abstract_canon_sha256":"8247d0b2fb6cdcee487bf6547eee87ba0ac51ead59d4a14ee6fc1e85b66fb079"},"schema_version":"1.0"},"canonical_sha256":"3fccf6885e45f791c5eeade0de464083318230f7a4a0c550adf9dfee36f94066","source":{"kind":"arxiv","id":"2404.13281","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13281","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13281v1","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13281","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_12","alias_value":"H7GPNCC6IX3Z","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_16","alias_value":"H7GPNCC6IX3ZDRPO","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_8","alias_value":"H7GPNCC6","created_at":"2026-07-05T08:10:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:H7GPNCC6IX3ZDRPOVXQN4RSAQM","target":"record","payload":{"canonical_record":{"source":{"id":"2404.13281","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-04-20T05:54:40Z","cross_cats_sorted":[],"title_canon_sha256":"fe5d8ab9abd49054c95bc963ec48d9fa6c9315134bcc37f8fd4a3b3b757f62fe","abstract_canon_sha256":"8247d0b2fb6cdcee487bf6547eee87ba0ac51ead59d4a14ee6fc1e85b66fb079"},"schema_version":"1.0"},"canonical_sha256":"3fccf6885e45f791c5eeade0de464083318230f7a4a0c550adf9dfee36f94066","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:10:30.013833Z","signature_b64":"Xm0lQbEuuia1LowkCznggQisKcgAIRK/sJHfJOitvV9PdIVfIUERortW4//8nWfQ/+K1rxND50ZnawHt5vAWAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3fccf6885e45f791c5eeade0de464083318230f7a4a0c550adf9dfee36f94066","last_reissued_at":"2026-07-05T08:10:30.013435Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:10:30.013435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.13281","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":"2026-07-05T08:10:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZYk3MNyBvchc5TdZGkccsdmj4nFFIua2MC4vKJpFXBP3cu1CXfQMtdRrunUAz8FuRes20BY5YGfCCPmyc7BPDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:30:20.694649Z"},"content_sha256":"4a52c8d317a95b04d7e676f80b150acd7559975671594dc684f87f4817f2f0e9","schema_version":"1.0","event_id":"sha256:4a52c8d317a95b04d7e676f80b150acd7559975671594dc684f87f4817f2f0e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:H7GPNCC6IX3ZDRPOVXQN4RSAQM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Massive MIMO Sampling Detection Strategy Based on Denoising Diffusion Model","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.SP","authors_text":"Lanxin He, Yongming Huang, Zheng Wang","submitted_at":"2024-04-20T05:54:40Z","abstract_excerpt":"The Langevin sampling method relies on an accurate score matching while the existing massive multiple-input multiple output (MIMO) Langevin detection involves an inevitable singular value decomposition (SVD) to calculate the posterior score. In this work, a massive MIMO sampling detection strategy that leverages the denoising diffusion model is proposed to narrow the gap between the given iterative detector and the maximum likelihood (ML) detection in an SVD-free manner. Specifically, the proposed score-based sampling detection strategy, denoted as approximate diffusion detection (ADD), is app"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13281","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/2404.13281/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":"2026-07-05T08:10:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Al581pY5tXOHGMB7heQq+Y2uoDLqSyjKF/SZ7AmRpue15leuZLnrUb8Ek25puMONMXXHU5f4huZg9L2j1XClCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:30:20.695724Z"},"content_sha256":"ee3c97af2baa16a03d610d17311c084dacd65e4a571739c166b40919f261c5c1","schema_version":"1.0","event_id":"sha256:ee3c97af2baa16a03d610d17311c084dacd65e4a571739c166b40919f261c5c1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/bundle.json","state_url":"https://pith.science/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/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":"2026-08-06T15:30:20Z","links":{"resolver":"https://pith.science/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM","bundle":"https://pith.science/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/bundle.json","state":"https://pith.science/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H7GPNCC6IX3ZDRPOVXQN4RSAQM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:H7GPNCC6IX3ZDRPOVXQN4RSAQM","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":"8247d0b2fb6cdcee487bf6547eee87ba0ac51ead59d4a14ee6fc1e85b66fb079","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-04-20T05:54:40Z","title_canon_sha256":"fe5d8ab9abd49054c95bc963ec48d9fa6c9315134bcc37f8fd4a3b3b757f62fe"},"schema_version":"1.0","source":{"id":"2404.13281","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.13281","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"arxiv_version","alias_value":"2404.13281v1","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.13281","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_12","alias_value":"H7GPNCC6IX3Z","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_16","alias_value":"H7GPNCC6IX3ZDRPO","created_at":"2026-07-05T08:10:30Z"},{"alias_kind":"pith_short_8","alias_value":"H7GPNCC6","created_at":"2026-07-05T08:10:30Z"}],"graph_snapshots":[{"event_id":"sha256:ee3c97af2baa16a03d610d17311c084dacd65e4a571739c166b40919f261c5c1","target":"graph","created_at":"2026-07-05T08:10:30Z","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/2404.13281/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Langevin sampling method relies on an accurate score matching while the existing massive multiple-input multiple output (MIMO) Langevin detection involves an inevitable singular value decomposition (SVD) to calculate the posterior score. In this work, a massive MIMO sampling detection strategy that leverages the denoising diffusion model is proposed to narrow the gap between the given iterative detector and the maximum likelihood (ML) detection in an SVD-free manner. Specifically, the proposed score-based sampling detection strategy, denoted as approximate diffusion detection (ADD), is app","authors_text":"Lanxin He, Yongming Huang, Zheng Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-04-20T05:54:40Z","title":"A Massive MIMO Sampling Detection Strategy Based on Denoising Diffusion Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.13281","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":"sha256:4a52c8d317a95b04d7e676f80b150acd7559975671594dc684f87f4817f2f0e9","target":"record","created_at":"2026-07-05T08:10:30Z","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":"8247d0b2fb6cdcee487bf6547eee87ba0ac51ead59d4a14ee6fc1e85b66fb079","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2024-04-20T05:54:40Z","title_canon_sha256":"fe5d8ab9abd49054c95bc963ec48d9fa6c9315134bcc37f8fd4a3b3b757f62fe"},"schema_version":"1.0","source":{"id":"2404.13281","kind":"arxiv","version":1}},"canonical_sha256":"3fccf6885e45f791c5eeade0de464083318230f7a4a0c550adf9dfee36f94066","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3fccf6885e45f791c5eeade0de464083318230f7a4a0c550adf9dfee36f94066","first_computed_at":"2026-07-05T08:10:30.013435Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:10:30.013435Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Xm0lQbEuuia1LowkCznggQisKcgAIRK/sJHfJOitvV9PdIVfIUERortW4//8nWfQ/+K1rxND50ZnawHt5vAWAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:10:30.013833Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.13281","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a52c8d317a95b04d7e676f80b150acd7559975671594dc684f87f4817f2f0e9","sha256:ee3c97af2baa16a03d610d17311c084dacd65e4a571739c166b40919f261c5c1"],"state_sha256":"5c6b60973cac61ded8d13cbb515c58f8dca0a38491c8fe28456e075fb4c065cf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HoT0YEkViL4IgJoXUIkKIUY7lLamZgNoMSdBXwcw34OsIC0odIN+dNA0bidKLALWbcqjUSDivBpoDCdYTQb/Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T15:30:20.700972Z","bundle_sha256":"b0da8822d211bba6c9e6dae64c3d106a6749efed2677897f44577c3f1108e9d9"}}