{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SKBKCNR23TDUTWJ34BQHWTAAAA","short_pith_number":"pith:SKBKCNR2","canonical_record":{"source":{"id":"2505.18637","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-05-24T10:52:01Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"1fbdf3bc78097915be3b652d8e9c39c32ae8444a7a6c54a838d36aa30a00652e","abstract_canon_sha256":"4eaaeac526ea94ee2a9344c43167ca45170c40fad89a221b068e6446c9063572"},"schema_version":"1.0"},"canonical_sha256":"9282a1363adcc749d93be0607b4c000039678b2e42161e664a1e0525a366af09","source":{"kind":"arxiv","id":"2505.18637","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.18637","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2505.18637v3","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18637","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"SKBKCNR23TDU","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"SKBKCNR23TDUTWJ3","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"SKBKCNR2","created_at":"2026-07-05T11:55:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SKBKCNR23TDUTWJ34BQHWTAAAA","target":"record","payload":{"canonical_record":{"source":{"id":"2505.18637","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-05-24T10:52:01Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"1fbdf3bc78097915be3b652d8e9c39c32ae8444a7a6c54a838d36aa30a00652e","abstract_canon_sha256":"4eaaeac526ea94ee2a9344c43167ca45170c40fad89a221b068e6446c9063572"},"schema_version":"1.0"},"canonical_sha256":"9282a1363adcc749d93be0607b4c000039678b2e42161e664a1e0525a366af09","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:55:40.196451Z","signature_b64":"H2d2A8+7FsfWLmYxkpr03yvbST9Q2zSvWrD1dtnDQxGn6muhzGC8ZS5Z4/RxRmCXPZBtD23AfyVcH+39Gbh1DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9282a1363adcc749d93be0607b4c000039678b2e42161e664a1e0525a366af09","last_reissued_at":"2026-07-05T11:55:40.196005Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:55:40.196005Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.18637","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":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zBsBBx/adUF9d4RT6UGMdrdNXcVnvcneqqkXGp9SZeb9hdaCQqkEZUqfDV+0dW43UmECv0ZHj8MzZg0rrprRDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:28:12.131691Z"},"content_sha256":"8c26d13377e9eebadc52ca1ba21ec4e61508cbd0b5f45831ac23615f98ac6644","schema_version":"1.0","event_id":"sha256:8c26d13377e9eebadc52ca1ba21ec4e61508cbd0b5f45831ac23615f98ac6644"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SKBKCNR23TDUTWJ34BQHWTAAAA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Neural Coding Is Not Always Semantic: Toward the Standardized Coding Workflow in Semantic Communications","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Hai-Long Qin, Jincheng Dai, Kai Niu, Ping Zhang, Shuo Shao, Sixian Wang, Wenjun Xu, Xiaoqi Qin","submitted_at":"2025-05-24T10:52:01Z","abstract_excerpt":"Semantic communication, leveraging advanced deep learning techniques, emerges as a new paradigm that meets the requirements of next-generation wireless networks. However, current semantic communication systems, which employ neural coding for feature extraction from raw data, have not adequately addressed the fundamental question: Is general feature extraction through deep neural networks sufficient for understanding semantic meaning within raw data in semantic communication? This article is thus motivated to clarify two critical aspects: semantic understanding and general semantic representati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18637","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/2505.18637/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":"2026-07-05T11:55:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VmnRnsnFh6qj/2Zcv/8gfVML0CQHbpgTr68AcBsYsUueav0FoAY2q3zrlF9k4gc7i9CSXxVIOuH752n3K2jSDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:28:12.132345Z"},"content_sha256":"b80145324eb3d6885572f2d2eb81c4e9a8b3d09f44c7bca881307a96cdbf070f","schema_version":"1.0","event_id":"sha256:b80145324eb3d6885572f2d2eb81c4e9a8b3d09f44c7bca881307a96cdbf070f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/bundle.json","state_url":"https://pith.science/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/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":"2026-08-19T04:28:12Z","links":{"resolver":"https://pith.science/pith/SKBKCNR23TDUTWJ34BQHWTAAAA","bundle":"https://pith.science/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/bundle.json","state":"https://pith.science/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SKBKCNR23TDUTWJ34BQHWTAAAA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SKBKCNR23TDUTWJ34BQHWTAAAA","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":"4eaaeac526ea94ee2a9344c43167ca45170c40fad89a221b068e6446c9063572","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-05-24T10:52:01Z","title_canon_sha256":"1fbdf3bc78097915be3b652d8e9c39c32ae8444a7a6c54a838d36aa30a00652e"},"schema_version":"1.0","source":{"id":"2505.18637","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.18637","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"arxiv_version","alias_value":"2505.18637v3","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18637","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_12","alias_value":"SKBKCNR23TDU","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_16","alias_value":"SKBKCNR23TDUTWJ3","created_at":"2026-07-05T11:55:40Z"},{"alias_kind":"pith_short_8","alias_value":"SKBKCNR2","created_at":"2026-07-05T11:55:40Z"}],"graph_snapshots":[{"event_id":"sha256:b80145324eb3d6885572f2d2eb81c4e9a8b3d09f44c7bca881307a96cdbf070f","target":"graph","created_at":"2026-07-05T11:55:40Z","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/2505.18637/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Semantic communication, leveraging advanced deep learning techniques, emerges as a new paradigm that meets the requirements of next-generation wireless networks. However, current semantic communication systems, which employ neural coding for feature extraction from raw data, have not adequately addressed the fundamental question: Is general feature extraction through deep neural networks sufficient for understanding semantic meaning within raw data in semantic communication? This article is thus motivated to clarify two critical aspects: semantic understanding and general semantic representati","authors_text":"Hai-Long Qin, Jincheng Dai, Kai Niu, Ping Zhang, Shuo Shao, Sixian Wang, Wenjun Xu, Xiaoqi Qin","cross_cats":["math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-05-24T10:52:01Z","title":"Neural Coding Is Not Always Semantic: Toward the Standardized Coding Workflow in Semantic Communications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18637","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":"sha256:8c26d13377e9eebadc52ca1ba21ec4e61508cbd0b5f45831ac23615f98ac6644","target":"record","created_at":"2026-07-05T11:55:40Z","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":"4eaaeac526ea94ee2a9344c43167ca45170c40fad89a221b068e6446c9063572","cross_cats_sorted":["math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2025-05-24T10:52:01Z","title_canon_sha256":"1fbdf3bc78097915be3b652d8e9c39c32ae8444a7a6c54a838d36aa30a00652e"},"schema_version":"1.0","source":{"id":"2505.18637","kind":"arxiv","version":3}},"canonical_sha256":"9282a1363adcc749d93be0607b4c000039678b2e42161e664a1e0525a366af09","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9282a1363adcc749d93be0607b4c000039678b2e42161e664a1e0525a366af09","first_computed_at":"2026-07-05T11:55:40.196005Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:55:40.196005Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H2d2A8+7FsfWLmYxkpr03yvbST9Q2zSvWrD1dtnDQxGn6muhzGC8ZS5Z4/RxRmCXPZBtD23AfyVcH+39Gbh1DA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:55:40.196451Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.18637","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c26d13377e9eebadc52ca1ba21ec4e61508cbd0b5f45831ac23615f98ac6644","sha256:b80145324eb3d6885572f2d2eb81c4e9a8b3d09f44c7bca881307a96cdbf070f"],"state_sha256":"a81c95b50f3932244ed15d8e9e472739d79b981267f301e0c1ab81dfd2940bbc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jG2OA9BGiDn9Yq4vjTN1b5FyIRqnAY0UGdDJqeg38TU9UlULFsG/lmGr2N6XRYDHWxVt4zACkXfbDUvLTcESBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T04:28:12.136446Z","bundle_sha256":"acf460f3cdcd60eb8d3219ff8b6dffd812256bb7614b66c46b3ee757cbd9d7b5"}}