{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WTN5SEGCKKIVDJ3OKLAT2AZH7K","short_pith_number":"pith:WTN5SEGC","canonical_record":{"source":{"id":"2307.07359","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2023-07-14T14:04:01Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"3df561f340aaaeb1adf61b81c0caaedf4c937c64a5b99a8ea7ebe54a543f52d2","abstract_canon_sha256":"63901d9ab0781946d8ffbdd34faf2f24c72c9cee94c1572cd36d74eaa2e1f0f1"},"schema_version":"1.0"},"canonical_sha256":"b4dbd910c2529151a76e52c13d0327fa9713af4717a383b0cec43299e8202aff","source":{"kind":"arxiv","id":"2307.07359","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.07359","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"arxiv_version","alias_value":"2307.07359v1","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07359","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_12","alias_value":"WTN5SEGCKKIV","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_16","alias_value":"WTN5SEGCKKIVDJ3O","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_8","alias_value":"WTN5SEGC","created_at":"2026-07-05T06:30:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WTN5SEGCKKIVDJ3OKLAT2AZH7K","target":"record","payload":{"canonical_record":{"source":{"id":"2307.07359","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2023-07-14T14:04:01Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"3df561f340aaaeb1adf61b81c0caaedf4c937c64a5b99a8ea7ebe54a543f52d2","abstract_canon_sha256":"63901d9ab0781946d8ffbdd34faf2f24c72c9cee94c1572cd36d74eaa2e1f0f1"},"schema_version":"1.0"},"canonical_sha256":"b4dbd910c2529151a76e52c13d0327fa9713af4717a383b0cec43299e8202aff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:30:54.542444Z","signature_b64":"Mu9sZsl1DQXbvFss34/PGmGkIxw4ZmDRF3ShrJWxb3kCqy1bYkapDAuCkO6AjljP7BNzH7z+k929s/gBYSV4AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4dbd910c2529151a76e52c13d0327fa9713af4717a383b0cec43299e8202aff","last_reissued_at":"2026-07-05T06:30:54.542012Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:30:54.542012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.07359","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":"2026-07-05T06:30:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DwLMi6CwuwVJGckkNW6xdDrLVCjjlkKnRjlqGgHYS3FFDL0Zt+cn/WGIzpZiJKYT501BF4u6NZLP5YVVUZqwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:44:20.560697Z"},"content_sha256":"e73f887c632affe9684b16a69abf8759db77d18e55144d3b57cc129175a64c5b","schema_version":"1.0","event_id":"sha256:e73f887c632affe9684b16a69abf8759db77d18e55144d3b57cc129175a64c5b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WTN5SEGCKKIVDJ3OKLAT2AZH7K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Multilayer Perceptron to GPT: A Reflection on Deep Learning Research for Wireless Physical Layer","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Amine Mezghani, Ekram Hossain, Faouzi Bellili, Mohamed Akrout, Robert W. Heath","submitted_at":"2023-07-14T14:04:01Z","abstract_excerpt":"Most research studies on deep learning (DL) applied to the physical layer of wireless communication do not put forward the critical role of the accuracy-generalization trade-off in developing and evaluating practical algorithms. To highlight the disadvantage of this common practice, we revisit a data decoding example from one of the first papers introducing DL-based end-to-end wireless communication systems to the research community and promoting the use of artificial intelligence (AI)/DL for the wireless physical layer. We then put forward two key trade-offs in designing DL models for communi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07359","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/2307.07359/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":"2026-07-05T06:30:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tnmluQK6dcJsZWFXjYkmd4vgxGCOdgYEQyJuxEIunz70orse6fU+yjGNurwMJoeQGYfWzcqEjlEGIJKp3MhZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T21:44:20.561224Z"},"content_sha256":"a7912746d2337fd31ca285fe29c0ed4daa5b23cd8a96df49e3d6ce92306bddf0","schema_version":"1.0","event_id":"sha256:a7912746d2337fd31ca285fe29c0ed4daa5b23cd8a96df49e3d6ce92306bddf0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/bundle.json","state_url":"https://pith.science/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/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":"2026-08-03T21:44:20Z","links":{"resolver":"https://pith.science/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K","bundle":"https://pith.science/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/bundle.json","state":"https://pith.science/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WTN5SEGCKKIVDJ3OKLAT2AZH7K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WTN5SEGCKKIVDJ3OKLAT2AZH7K","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":"63901d9ab0781946d8ffbdd34faf2f24c72c9cee94c1572cd36d74eaa2e1f0f1","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2023-07-14T14:04:01Z","title_canon_sha256":"3df561f340aaaeb1adf61b81c0caaedf4c937c64a5b99a8ea7ebe54a543f52d2"},"schema_version":"1.0","source":{"id":"2307.07359","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.07359","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"arxiv_version","alias_value":"2307.07359v1","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.07359","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_12","alias_value":"WTN5SEGCKKIV","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_16","alias_value":"WTN5SEGCKKIVDJ3O","created_at":"2026-07-05T06:30:54Z"},{"alias_kind":"pith_short_8","alias_value":"WTN5SEGC","created_at":"2026-07-05T06:30:54Z"}],"graph_snapshots":[{"event_id":"sha256:a7912746d2337fd31ca285fe29c0ed4daa5b23cd8a96df49e3d6ce92306bddf0","target":"graph","created_at":"2026-07-05T06:30:54Z","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/2307.07359/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most research studies on deep learning (DL) applied to the physical layer of wireless communication do not put forward the critical role of the accuracy-generalization trade-off in developing and evaluating practical algorithms. To highlight the disadvantage of this common practice, we revisit a data decoding example from one of the first papers introducing DL-based end-to-end wireless communication systems to the research community and promoting the use of artificial intelligence (AI)/DL for the wireless physical layer. We then put forward two key trade-offs in designing DL models for communi","authors_text":"Amine Mezghani, Ekram Hossain, Faouzi Bellili, Mohamed Akrout, Robert W. Heath","cross_cats":["math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2023-07-14T14:04:01Z","title":"From Multilayer Perceptron to GPT: A Reflection on Deep Learning Research for Wireless Physical Layer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.07359","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:e73f887c632affe9684b16a69abf8759db77d18e55144d3b57cc129175a64c5b","target":"record","created_at":"2026-07-05T06:30:54Z","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":"63901d9ab0781946d8ffbdd34faf2f24c72c9cee94c1572cd36d74eaa2e1f0f1","cross_cats_sorted":["math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IT","submitted_at":"2023-07-14T14:04:01Z","title_canon_sha256":"3df561f340aaaeb1adf61b81c0caaedf4c937c64a5b99a8ea7ebe54a543f52d2"},"schema_version":"1.0","source":{"id":"2307.07359","kind":"arxiv","version":1}},"canonical_sha256":"b4dbd910c2529151a76e52c13d0327fa9713af4717a383b0cec43299e8202aff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b4dbd910c2529151a76e52c13d0327fa9713af4717a383b0cec43299e8202aff","first_computed_at":"2026-07-05T06:30:54.542012Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:30:54.542012Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Mu9sZsl1DQXbvFss34/PGmGkIxw4ZmDRF3ShrJWxb3kCqy1bYkapDAuCkO6AjljP7BNzH7z+k929s/gBYSV4AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:30:54.542444Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.07359","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e73f887c632affe9684b16a69abf8759db77d18e55144d3b57cc129175a64c5b","sha256:a7912746d2337fd31ca285fe29c0ed4daa5b23cd8a96df49e3d6ce92306bddf0"],"state_sha256":"df737bc489a2ebab562ccebf72fa140c8e37e21c8710e5b15f7ff348f3fefedf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5o6FvvajeQpzihKu2p3pDvsnC9wFaTUYKWOx/zNCH+71t9cUYkp5NUCWQQBfVVOyR/B3ouoO6TrqPwfg7rdVAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T21:44:20.566827Z","bundle_sha256":"b969d2e2afc9694da3b168d00c989016b75d9b5a19aac9dbfa87caa5cd3672bd"}}