{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4FJGE6TI5H35IPPA2CIH3KFOOC","short_pith_number":"pith:4FJGE6TI","canonical_record":{"source":{"id":"2503.20500","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2025-03-26T12:39:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9951cd9be5d7f7bafffe21929dd107761f396f78e9d1f8a3648ad55472d5afd8","abstract_canon_sha256":"160d4749908edf246ce6d0b911e58c0493d2cb5c0d9d033ad93d24aad712ddc0"},"schema_version":"1.0"},"canonical_sha256":"e152627a68e9f7d43de0d0907da8ae70a1a71da9eaacfd6f531756d75aa144ee","source":{"kind":"arxiv","id":"2503.20500","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.20500","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.20500v3","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.20500","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_12","alias_value":"4FJGE6TI5H35","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_16","alias_value":"4FJGE6TI5H35IPPA","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_8","alias_value":"4FJGE6TI","created_at":"2026-07-05T11:00:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4FJGE6TI5H35IPPA2CIH3KFOOC","target":"record","payload":{"canonical_record":{"source":{"id":"2503.20500","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2025-03-26T12:39:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9951cd9be5d7f7bafffe21929dd107761f396f78e9d1f8a3648ad55472d5afd8","abstract_canon_sha256":"160d4749908edf246ce6d0b911e58c0493d2cb5c0d9d033ad93d24aad712ddc0"},"schema_version":"1.0"},"canonical_sha256":"e152627a68e9f7d43de0d0907da8ae70a1a71da9eaacfd6f531756d75aa144ee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:00:05.876970Z","signature_b64":"ykpqih9SJ9qlfu41DBR3mco799pVVi3cleHoxAVnfyv6IuTyDIw3SFwTPoTp8ripHEFyVCKtAEMLbjJUFdG7CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e152627a68e9f7d43de0d0907da8ae70a1a71da9eaacfd6f531756d75aa144ee","last_reissued_at":"2026-07-05T11:00:05.876449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:00:05.876449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.20500","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:00:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IJ+GwzTttTemNvXuO3X3QoO/wqWINhFdWZBGFDYFdqCaHUYKPYe0tjmJS5Xa/tQJEf8gjXMhX8SU+sfr5J5bAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:33:18.282487Z"},"content_sha256":"d7b6ab1c32760f6b7475d60633ea5403317f5edccbd1f7258a7d7cd30b5cd006","schema_version":"1.0","event_id":"sha256:d7b6ab1c32760f6b7475d60633ea5403317f5edccbd1f7258a7d7cd30b5cd006"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4FJGE6TI5H35IPPA2CIH3KFOOC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Novel Deep Neural OFDM Receiver Architectures for LLR Estimation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"eess.SP","authors_text":"Ali G\\\"or\\c{c}in, Erhan Karakoca, H\\\"useyin \\c{C}evik, \\.Ibrahim H\\\"okelek","submitted_at":"2025-03-26T12:39:56Z","abstract_excerpt":"Neural receivers have recently become a popular topic, where the received signals can be directly decoded by data driven mechanisms such as machine learning and deep learning. In this paper, we propose two novel neural network based orthogonal frequency division multiplexing (OFDM) receivers performing channel estimation and equalization tasks and directly predicting log likelihood ratios (LLRs) from the received in phase and quadrature phase (IQ) signals. The first network, the Dual Attention Transformer (DAT), employs a state of the art (SOTA) transformer architecture with an attention mecha"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.20500","kind":"arxiv","version":3},"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/2503.20500/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":"2026-07-05T11:00:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ESYy2xs0C5h98kdU750vo9kTqANBKsp5BulzSpvuIS0HaiwHFn+a4wMjeQ8SfuH++FnjZmyOuxOQivgQhUOECw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T17:33:18.283057Z"},"content_sha256":"fc5cd1e779f50f98e8213dadf4fef2fc1d258b7e06900c6dc4f4ae2587bad22a","schema_version":"1.0","event_id":"sha256:fc5cd1e779f50f98e8213dadf4fef2fc1d258b7e06900c6dc4f4ae2587bad22a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/bundle.json","state_url":"https://pith.science/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/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":"2026-08-08T17:33:18Z","links":{"resolver":"https://pith.science/pith/4FJGE6TI5H35IPPA2CIH3KFOOC","bundle":"https://pith.science/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/bundle.json","state":"https://pith.science/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4FJGE6TI5H35IPPA2CIH3KFOOC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4FJGE6TI5H35IPPA2CIH3KFOOC","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":"160d4749908edf246ce6d0b911e58c0493d2cb5c0d9d033ad93d24aad712ddc0","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2025-03-26T12:39:56Z","title_canon_sha256":"9951cd9be5d7f7bafffe21929dd107761f396f78e9d1f8a3648ad55472d5afd8"},"schema_version":"1.0","source":{"id":"2503.20500","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.20500","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.20500v3","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.20500","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_12","alias_value":"4FJGE6TI5H35","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_16","alias_value":"4FJGE6TI5H35IPPA","created_at":"2026-07-05T11:00:05Z"},{"alias_kind":"pith_short_8","alias_value":"4FJGE6TI","created_at":"2026-07-05T11:00:05Z"}],"graph_snapshots":[{"event_id":"sha256:fc5cd1e779f50f98e8213dadf4fef2fc1d258b7e06900c6dc4f4ae2587bad22a","target":"graph","created_at":"2026-07-05T11:00:05Z","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/2503.20500/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural receivers have recently become a popular topic, where the received signals can be directly decoded by data driven mechanisms such as machine learning and deep learning. In this paper, we propose two novel neural network based orthogonal frequency division multiplexing (OFDM) receivers performing channel estimation and equalization tasks and directly predicting log likelihood ratios (LLRs) from the received in phase and quadrature phase (IQ) signals. The first network, the Dual Attention Transformer (DAT), employs a state of the art (SOTA) transformer architecture with an attention mecha","authors_text":"Ali G\\\"or\\c{c}in, Erhan Karakoca, H\\\"useyin \\c{C}evik, \\.Ibrahim H\\\"okelek","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2025-03-26T12:39:56Z","title":"Novel Deep Neural OFDM Receiver Architectures for LLR Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.20500","kind":"arxiv","version":3},"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:d7b6ab1c32760f6b7475d60633ea5403317f5edccbd1f7258a7d7cd30b5cd006","target":"record","created_at":"2026-07-05T11:00:05Z","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":"160d4749908edf246ce6d0b911e58c0493d2cb5c0d9d033ad93d24aad712ddc0","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.SP","submitted_at":"2025-03-26T12:39:56Z","title_canon_sha256":"9951cd9be5d7f7bafffe21929dd107761f396f78e9d1f8a3648ad55472d5afd8"},"schema_version":"1.0","source":{"id":"2503.20500","kind":"arxiv","version":3}},"canonical_sha256":"e152627a68e9f7d43de0d0907da8ae70a1a71da9eaacfd6f531756d75aa144ee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e152627a68e9f7d43de0d0907da8ae70a1a71da9eaacfd6f531756d75aa144ee","first_computed_at":"2026-07-05T11:00:05.876449Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:00:05.876449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ykpqih9SJ9qlfu41DBR3mco799pVVi3cleHoxAVnfyv6IuTyDIw3SFwTPoTp8ripHEFyVCKtAEMLbjJUFdG7CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:00:05.876970Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.20500","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7b6ab1c32760f6b7475d60633ea5403317f5edccbd1f7258a7d7cd30b5cd006","sha256:fc5cd1e779f50f98e8213dadf4fef2fc1d258b7e06900c6dc4f4ae2587bad22a"],"state_sha256":"d40f959d050bb12a904d8ea23fcee3bff76aec85d0c7fc800ec803c41df7139c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"49R/h1ZVsnDMnB9X6njMcI9T5aA7bSVNUt+iBgAnoXDWyT/WK2D4Uqqgd78iF/ff6lGTB4lwRqjQwbWLXZwdAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T17:33:18.288358Z","bundle_sha256":"8315cc7c47d4227b122257a2e304501355ae3dad3e0dba9182718a566ce3a604"}}