{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:OKCDUG7LMCDLIPMFNHJL5RAYNU","short_pith_number":"pith:OKCDUG7L","schema_version":"1.0","canonical_sha256":"72843a1beb6086b43d8569d2bec4186d2dac44bd33bbd79fd4b144ac1b7a187e","source":{"kind":"arxiv","id":"2502.00700","version":3},"attestation_state":"computed","paper":{"title":"S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Bing He, Donghui Feng, Guo Lu, Li Song, Qian Li, Qi Wang, Ronghua Wu, Wenjun Zhang, Yunuo Chen","submitted_at":"2025-02-02T07:15:51Z","abstract_excerpt":"Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of the FeedForward Network (FFN)-based channel aggregation module has been largely overlooked. Our research reveals that efficient channel aggregation-rather than complex and time-consuming spatial operations-is the key to achieving competitive LIC models. Based on this insight, we initiate the ``S2CFormer'' paradigm, a general architecture that simplifies spatial operations and enhances channel operations to overcome "},"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":"2502.00700","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-02T07:15:51Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"6c82c4c885d83f784d04a3797d595ab8205481f5d80d65800b18fa394e6a0160","abstract_canon_sha256":"f698ba4a85bba26298c21eeb0fe35486d497e61c0fa005b1fdb7199521ac6a9e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:37:43.847605Z","signature_b64":"TwFUhmDuDLyHTsLM8bTecVsQaUiCBUVv5e/hXttY2ugclzlM86vI9qj5Z+HaNXss8cNT1WcCCOOFSCQbdlIOCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72843a1beb6086b43d8569d2bec4186d2dac44bd33bbd79fd4b144ac1b7a187e","last_reissued_at":"2026-07-05T10:37:43.847099Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:37:43.847099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"S2CFormer: Revisiting the RD-Latency Trade-off in Transformer-based Learned Image Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Bing He, Donghui Feng, Guo Lu, Li Song, Qian Li, Qi Wang, Ronghua Wu, Wenjun Zhang, Yunuo Chen","submitted_at":"2025-02-02T07:15:51Z","abstract_excerpt":"Transformer-based Learned Image Compression (LIC) suffers from a suboptimal trade-off between decoding latency and rate-distortion (R-D) performance. Moreover, the critical role of the FeedForward Network (FFN)-based channel aggregation module has been largely overlooked. Our research reveals that efficient channel aggregation-rather than complex and time-consuming spatial operations-is the key to achieving competitive LIC models. Based on this insight, we initiate the ``S2CFormer'' paradigm, a general architecture that simplifies spatial operations and enhances channel operations to overcome "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.00700","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/2502.00700/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":"2502.00700","created_at":"2026-07-05T10:37:43.847153+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.00700v3","created_at":"2026-07-05T10:37:43.847153+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.00700","created_at":"2026-07-05T10:37:43.847153+00:00"},{"alias_kind":"pith_short_12","alias_value":"OKCDUG7LMCDL","created_at":"2026-07-05T10:37:43.847153+00:00"},{"alias_kind":"pith_short_16","alias_value":"OKCDUG7LMCDLIPMF","created_at":"2026-07-05T10:37:43.847153+00:00"},{"alias_kind":"pith_short_8","alias_value":"OKCDUG7L","created_at":"2026-07-05T10:37:43.847153+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2603.13864","citing_title":"Inevitable Encounters: Backdoor Attacks Involving Lossy Compression","ref_index":38,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU","json":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU.json","graph_json":"https://pith.science/api/pith-number/OKCDUG7LMCDLIPMFNHJL5RAYNU/graph.json","events_json":"https://pith.science/api/pith-number/OKCDUG7LMCDLIPMFNHJL5RAYNU/events.json","paper":"https://pith.science/paper/OKCDUG7L"},"agent_actions":{"view_html":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU","download_json":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU.json","view_paper":"https://pith.science/paper/OKCDUG7L","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.00700&json=true","fetch_graph":"https://pith.science/api/pith-number/OKCDUG7LMCDLIPMFNHJL5RAYNU/graph.json","fetch_events":"https://pith.science/api/pith-number/OKCDUG7LMCDLIPMFNHJL5RAYNU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU/action/storage_attestation","attest_author":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU/action/author_attestation","sign_citation":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU/action/citation_signature","submit_replication":"https://pith.science/pith/OKCDUG7LMCDLIPMFNHJL5RAYNU/action/replication_record"}},"created_at":"2026-07-05T10:37:43.847153+00:00","updated_at":"2026-07-05T10:37:43.847153+00:00"}