{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HN2Y2YZYZLSRY6SLSCCMKKR42O","short_pith_number":"pith:HN2Y2YZY","canonical_record":{"source":{"id":"2412.09023","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T07:38:10Z","cross_cats_sorted":[],"title_canon_sha256":"0ea48da221848893b619d466309b720a992e49c0c79ae4318abf9a70dee2ef3f","abstract_canon_sha256":"868576a821c9cd0419686ea48861c4d9d24ee668c9ac959340cc893d71a8026a"},"schema_version":"1.0"},"canonical_sha256":"3b758d6338cae51c7a4b9084c52a3cd3bde8dede93ea485543977d233d9c4791","source":{"kind":"arxiv","id":"2412.09023","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.09023","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.09023v2","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.09023","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_12","alias_value":"HN2Y2YZYZLSR","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_16","alias_value":"HN2Y2YZYZLSRY6SL","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_8","alias_value":"HN2Y2YZY","created_at":"2026-05-26T01:03:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HN2Y2YZYZLSRY6SLSCCMKKR42O","target":"record","payload":{"canonical_record":{"source":{"id":"2412.09023","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T07:38:10Z","cross_cats_sorted":[],"title_canon_sha256":"0ea48da221848893b619d466309b720a992e49c0c79ae4318abf9a70dee2ef3f","abstract_canon_sha256":"868576a821c9cd0419686ea48861c4d9d24ee668c9ac959340cc893d71a8026a"},"schema_version":"1.0"},"canonical_sha256":"3b758d6338cae51c7a4b9084c52a3cd3bde8dede93ea485543977d233d9c4791","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:03:09.854492Z","signature_b64":"ofju/EihIJbjA/fJHfbbvNQ7k4R8cQhbPY4q3fRlF4WCAhdPXzBiZf+19COadCiSZUVXy3omPkTtCpxetYzlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b758d6338cae51c7a4b9084c52a3cd3bde8dede93ea485543977d233d9c4791","last_reissued_at":"2026-05-26T01:03:09.853564Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:03:09.853564Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.09023","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-26T01:03:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9EgPvVEInRQis07ZnIEZCnabOr8zTAtKh+mp9zs6kO1xt9beWLOdWim8xRkm3K4hA8GKr5jN6BB23Q29EJCyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T17:08:16.732046Z"},"content_sha256":"93f352f740d85238d0e8fbd33b1011e3585778cb97b8f35a9bd154b6b4a2fc20","schema_version":"1.0","event_id":"sha256:93f352f740d85238d0e8fbd33b1011e3585778cb97b8f35a9bd154b6b4a2fc20"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HN2Y2YZYZLSRY6SLSCCMKKR42O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"STEAM: Squeeze and Transform Enhanced Attention Module","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Parikshit Singh Rathore, Punit Rathore, Ram Samarth B B, Rishabh Sabharwal","submitted_at":"2024-12-12T07:38:10Z","abstract_excerpt":"Channel and spatial attention mechanisms introduced by earlier works enhance the representation abilities of deep convolutional neural networks (CNNs) but often lead to increased parameter and computation costs. While recent approaches focus solely on efficient feature context modeling for channel attention, we aim to model both channel and spatial attention comprehensively with minimal parameters and reduced computation. Leveraging the principles of relational modeling in graphs, we introduce a constant-parameter module, STEAM: Squeeze and Transform Enhanced Attention Module, which integrates"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.09023","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/2412.09023/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":"2026-05-26T01:03:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OlLH6ZARp5+l7qYOT672mjFBr3ftqSnieYEUkPGzIXTtwr1/dLLejxGRfhmi8cMctSZAg4vvBC7HavKkbsNmCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T17:08:16.732456Z"},"content_sha256":"8e119ebfd08f221a02426c3065c7690e15d82cb502c612620bc0fe0ad5091870","schema_version":"1.0","event_id":"sha256:8e119ebfd08f221a02426c3065c7690e15d82cb502c612620bc0fe0ad5091870"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/bundle.json","state_url":"https://pith.science/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/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":"2026-07-04T17:08:16Z","links":{"resolver":"https://pith.science/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O","bundle":"https://pith.science/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/bundle.json","state":"https://pith.science/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HN2Y2YZYZLSRY6SLSCCMKKR42O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HN2Y2YZYZLSRY6SLSCCMKKR42O","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":"868576a821c9cd0419686ea48861c4d9d24ee668c9ac959340cc893d71a8026a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T07:38:10Z","title_canon_sha256":"0ea48da221848893b619d466309b720a992e49c0c79ae4318abf9a70dee2ef3f"},"schema_version":"1.0","source":{"id":"2412.09023","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.09023","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.09023v2","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.09023","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_12","alias_value":"HN2Y2YZYZLSR","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_16","alias_value":"HN2Y2YZYZLSRY6SL","created_at":"2026-05-26T01:03:09Z"},{"alias_kind":"pith_short_8","alias_value":"HN2Y2YZY","created_at":"2026-05-26T01:03:09Z"}],"graph_snapshots":[{"event_id":"sha256:8e119ebfd08f221a02426c3065c7690e15d82cb502c612620bc0fe0ad5091870","target":"graph","created_at":"2026-05-26T01:03:09Z","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/2412.09023/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Channel and spatial attention mechanisms introduced by earlier works enhance the representation abilities of deep convolutional neural networks (CNNs) but often lead to increased parameter and computation costs. While recent approaches focus solely on efficient feature context modeling for channel attention, we aim to model both channel and spatial attention comprehensively with minimal parameters and reduced computation. Leveraging the principles of relational modeling in graphs, we introduce a constant-parameter module, STEAM: Squeeze and Transform Enhanced Attention Module, which integrates","authors_text":"Parikshit Singh Rathore, Punit Rathore, Ram Samarth B B, Rishabh Sabharwal","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T07:38:10Z","title":"STEAM: Squeeze and Transform Enhanced Attention Module"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.09023","kind":"arxiv","version":2},"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":"sha256:93f352f740d85238d0e8fbd33b1011e3585778cb97b8f35a9bd154b6b4a2fc20","target":"record","created_at":"2026-05-26T01:03:09Z","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":"868576a821c9cd0419686ea48861c4d9d24ee668c9ac959340cc893d71a8026a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-12T07:38:10Z","title_canon_sha256":"0ea48da221848893b619d466309b720a992e49c0c79ae4318abf9a70dee2ef3f"},"schema_version":"1.0","source":{"id":"2412.09023","kind":"arxiv","version":2}},"canonical_sha256":"3b758d6338cae51c7a4b9084c52a3cd3bde8dede93ea485543977d233d9c4791","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b758d6338cae51c7a4b9084c52a3cd3bde8dede93ea485543977d233d9c4791","first_computed_at":"2026-05-26T01:03:09.853564Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:03:09.853564Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ofju/EihIJbjA/fJHfbbvNQ7k4R8cQhbPY4q3fRlF4WCAhdPXzBiZf+19COadCiSZUVXy3omPkTtCpxetYzlDA==","signature_status":"signed_v1","signed_at":"2026-05-26T01:03:09.854492Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.09023","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:93f352f740d85238d0e8fbd33b1011e3585778cb97b8f35a9bd154b6b4a2fc20","sha256:8e119ebfd08f221a02426c3065c7690e15d82cb502c612620bc0fe0ad5091870"],"state_sha256":"bac266e5d52cc9b68bf830ad3a85c5ce1eff6e021fc8eb35e88a14528dba3f66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TpMsHmJshPgj+q4WWXI76jPnojvR2d+wDQYJcprkamALwNbFIfwvFUEg3MljB6PzTMzmwt6rVGOnOehgHUCBAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T17:08:16.734463Z","bundle_sha256":"52fc8d0b4b819e15e7ce60296692fa0c390efb9e38d735636469621957cfbbbc"}}