{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:4MENCWEUMKTXTA2RCJG4APLIY4","short_pith_number":"pith:4MENCWEU","schema_version":"1.0","canonical_sha256":"e308d1589462a7798351124dc03d68c7158df2521a96204c63137c6629237d65","source":{"kind":"arxiv","id":"2302.13580","version":2},"attestation_state":"computed","paper":{"title":"Joint Task and Data Oriented Semantic Communications: A Deep Separate Source-channel Coding Scheme","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Chuan Huang, Dongxu Li, Jianhao Huang, Wei Zhang, Xiaoqi Qin","submitted_at":"2023-02-27T08:34:37Z","abstract_excerpt":"Semantic communications are expected to accomplish various semantic tasks with relatively less spectrum resource by exploiting the semantic feature of source data. To simultaneously serve both the data transmission and semantic tasks, joint data compression and semantic analysis has become pivotal issue in semantic communications. This paper proposes a deep separate source-channel coding (DSSCC) framework for the joint task and data oriented semantic communications (JTD-SC) and utilizes the variational autoencoder approach to solve the rate-distortion problem with semantic distortion. First, b"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2302.13580","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2023-02-27T08:34:37Z","cross_cats_sorted":["cs.LG","eess.SP","math.IT"],"title_canon_sha256":"18f977762fba12babd4f120e0d57ff2f437489758c08c76bfeb05a2457150a3a","abstract_canon_sha256":"6baa2cf9f77f5869a79c681776e57178a0e1d9a004f2f3918bb6d2a3bd0c4c66"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:40:32.003686Z","signature_b64":"ePKqo9OPDspXiMRHxxplGw0kUrstLp6p30tG7KTBIOmSwlG/bop2VLtvXWHsdhzO4cHxb12deF+seDogvpxmCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e308d1589462a7798351124dc03d68c7158df2521a96204c63137c6629237d65","last_reissued_at":"2026-07-05T06:40:32.003237Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:40:32.003237Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Joint Task and Data Oriented Semantic Communications: A Deep Separate Source-channel Coding Scheme","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Chuan Huang, Dongxu Li, Jianhao Huang, Wei Zhang, Xiaoqi Qin","submitted_at":"2023-02-27T08:34:37Z","abstract_excerpt":"Semantic communications are expected to accomplish various semantic tasks with relatively less spectrum resource by exploiting the semantic feature of source data. To simultaneously serve both the data transmission and semantic tasks, joint data compression and semantic analysis has become pivotal issue in semantic communications. This paper proposes a deep separate source-channel coding (DSSCC) framework for the joint task and data oriented semantic communications (JTD-SC) and utilizes the variational autoencoder approach to solve the rate-distortion problem with semantic distortion. First, b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.13580","kind":"arxiv","version":2},"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/2302.13580/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2302.13580","created_at":"2026-07-05T06:40:32.003302+00:00"},{"alias_kind":"arxiv_version","alias_value":"2302.13580v2","created_at":"2026-07-05T06:40:32.003302+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.13580","created_at":"2026-07-05T06:40:32.003302+00:00"},{"alias_kind":"pith_short_12","alias_value":"4MENCWEUMKTX","created_at":"2026-07-05T06:40:32.003302+00:00"},{"alias_kind":"pith_short_16","alias_value":"4MENCWEUMKTXTA2R","created_at":"2026-07-05T06:40:32.003302+00:00"},{"alias_kind":"pith_short_8","alias_value":"4MENCWEU","created_at":"2026-07-05T06:40:32.003302+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2306.04321","citing_title":"Generative Semantic Communication: Diffusion Models Beyond Bit Recovery","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2405.09866","citing_title":"Training-Free Multi-User Generative Semantic Communications via Null-Space Diffusion Sampling","ref_index":29,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4","json":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4.json","graph_json":"https://pith.science/api/pith-number/4MENCWEUMKTXTA2RCJG4APLIY4/graph.json","events_json":"https://pith.science/api/pith-number/4MENCWEUMKTXTA2RCJG4APLIY4/events.json","paper":"https://pith.science/paper/4MENCWEU"},"agent_actions":{"view_html":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4","download_json":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4.json","view_paper":"https://pith.science/paper/4MENCWEU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2302.13580&json=true","fetch_graph":"https://pith.science/api/pith-number/4MENCWEUMKTXTA2RCJG4APLIY4/graph.json","fetch_events":"https://pith.science/api/pith-number/4MENCWEUMKTXTA2RCJG4APLIY4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4/action/storage_attestation","attest_author":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4/action/author_attestation","sign_citation":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4/action/citation_signature","submit_replication":"https://pith.science/pith/4MENCWEUMKTXTA2RCJG4APLIY4/action/replication_record"}},"created_at":"2026-07-05T06:40:32.003302+00:00","updated_at":"2026-07-05T06:40:32.003302+00:00"}