{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:N32QNYINSRJBWHIZKE6SYYMAGO","short_pith_number":"pith:N32QNYIN","canonical_record":{"source":{"id":"2408.01224","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-02T12:27:15Z","cross_cats_sorted":[],"title_canon_sha256":"1edacfe995213f00a6ad1b91033a9333e22b100716fa64ba8ec780d25d619f76","abstract_canon_sha256":"e15c33a9690a89dde3e1a33d26858669cf0b26f2ebd054d2d9f3642622148393"},"schema_version":"1.0"},"canonical_sha256":"6ef506e10d94521b1d19513d2c618033b01b889807529293721de338f30cd6cf","source":{"kind":"arxiv","id":"2408.01224","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01224","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01224v3","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01224","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"N32QNYINSRJB","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"N32QNYINSRJBWHIZ","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"N32QNYIN","created_at":"2026-07-05T10:10:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:N32QNYINSRJBWHIZKE6SYYMAGO","target":"record","payload":{"canonical_record":{"source":{"id":"2408.01224","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-02T12:27:15Z","cross_cats_sorted":[],"title_canon_sha256":"1edacfe995213f00a6ad1b91033a9333e22b100716fa64ba8ec780d25d619f76","abstract_canon_sha256":"e15c33a9690a89dde3e1a33d26858669cf0b26f2ebd054d2d9f3642622148393"},"schema_version":"1.0"},"canonical_sha256":"6ef506e10d94521b1d19513d2c618033b01b889807529293721de338f30cd6cf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:10:27.390983Z","signature_b64":"LfNzcLLPoHbCc4GnNR7feXoI9kq2cYCsjvYaTYdL2jjxr8gAE+oETN+Mj6mLjmmOzt9L3a+VmdgfslquotkZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ef506e10d94521b1d19513d2c618033b01b889807529293721de338f30cd6cf","last_reissued_at":"2026-07-05T10:10:27.390512Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:10:27.390512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.01224","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":"2026-07-05T10:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lSzdJIY7GlhL8O8C1YspzxVpRWsPwBbCCLEPy3UQN8fLrRiX1Vg7IgD4YgGetdVpURF4eX0dNMQaOb/0h6LCAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T18:04:41.302927Z"},"content_sha256":"2f650789c49cb0f2a65c04daca08ae8a47c1cf9b2aed2d3a93472ffd99b4379f","schema_version":"1.0","event_id":"sha256:2f650789c49cb0f2a65c04daca08ae8a47c1cf9b2aed2d3a93472ffd99b4379f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:N32QNYINSRJBWHIZKE6SYYMAGO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-head Spatial-Spectral Mamba for Hyperspectral Image Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hamad Ahmed Altuwaijri, Manuel Mazzara, Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama, Salvatore Distefano","submitted_at":"2024-08-02T12:27:15Z","abstract_excerpt":"Spatial-Spectral Mamba (SSM) improves computational efficiency and captures long-range dependencies, addressing Transformer limitations. However, traditional Mamba models overlook rich spectral information in HSIs and struggle with high dimensionality and sequential data. To address these issues, we propose the SSM with multi-head self-attention and token enhancement (MHSSMamba). This model integrates spectral and spatial information by enhancing spectral tokens and using multi-head attention to capture complex relationships between spectral bands and spatial locations. It also manages long-ra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01224","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/2408.01224/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":"2026-07-05T10:10:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F/DpB0r9cEwCv2ly93Z81qQlJ4jDt/GHrtWfBuE38YSV+RvsMNr40+LlL8AatAS84dXhZ37Qf9VgISI5qN7RBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T18:04:41.303993Z"},"content_sha256":"2e7b9e86533eab53f2b2404d64acab0a8f66b8d4d3484e560c5e719a35fcee6b","schema_version":"1.0","event_id":"sha256:2e7b9e86533eab53f2b2404d64acab0a8f66b8d4d3484e560c5e719a35fcee6b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/N32QNYINSRJBWHIZKE6SYYMAGO/bundle.json","state_url":"https://pith.science/pith/N32QNYINSRJBWHIZKE6SYYMAGO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/N32QNYINSRJBWHIZKE6SYYMAGO/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":"2026-08-15T18:04:41Z","links":{"resolver":"https://pith.science/pith/N32QNYINSRJBWHIZKE6SYYMAGO","bundle":"https://pith.science/pith/N32QNYINSRJBWHIZKE6SYYMAGO/bundle.json","state":"https://pith.science/pith/N32QNYINSRJBWHIZKE6SYYMAGO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/N32QNYINSRJBWHIZKE6SYYMAGO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:N32QNYINSRJBWHIZKE6SYYMAGO","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":"e15c33a9690a89dde3e1a33d26858669cf0b26f2ebd054d2d9f3642622148393","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-02T12:27:15Z","title_canon_sha256":"1edacfe995213f00a6ad1b91033a9333e22b100716fa64ba8ec780d25d619f76"},"schema_version":"1.0","source":{"id":"2408.01224","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.01224","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"arxiv_version","alias_value":"2408.01224v3","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.01224","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_12","alias_value":"N32QNYINSRJB","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_16","alias_value":"N32QNYINSRJBWHIZ","created_at":"2026-07-05T10:10:27Z"},{"alias_kind":"pith_short_8","alias_value":"N32QNYIN","created_at":"2026-07-05T10:10:27Z"}],"graph_snapshots":[{"event_id":"sha256:2e7b9e86533eab53f2b2404d64acab0a8f66b8d4d3484e560c5e719a35fcee6b","target":"graph","created_at":"2026-07-05T10:10:27Z","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/2408.01224/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spatial-Spectral Mamba (SSM) improves computational efficiency and captures long-range dependencies, addressing Transformer limitations. However, traditional Mamba models overlook rich spectral information in HSIs and struggle with high dimensionality and sequential data. To address these issues, we propose the SSM with multi-head self-attention and token enhancement (MHSSMamba). This model integrates spectral and spatial information by enhancing spectral tokens and using multi-head attention to capture complex relationships between spectral bands and spatial locations. It also manages long-ra","authors_text":"Hamad Ahmed Altuwaijri, Manuel Mazzara, Muhammad Ahmad, Muhammad Hassaan Farooq Butt, Muhammad Usama, Salvatore Distefano","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-02T12:27:15Z","title":"Multi-head Spatial-Spectral Mamba for Hyperspectral Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.01224","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":"sha256:2f650789c49cb0f2a65c04daca08ae8a47c1cf9b2aed2d3a93472ffd99b4379f","target":"record","created_at":"2026-07-05T10:10:27Z","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":"e15c33a9690a89dde3e1a33d26858669cf0b26f2ebd054d2d9f3642622148393","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-08-02T12:27:15Z","title_canon_sha256":"1edacfe995213f00a6ad1b91033a9333e22b100716fa64ba8ec780d25d619f76"},"schema_version":"1.0","source":{"id":"2408.01224","kind":"arxiv","version":3}},"canonical_sha256":"6ef506e10d94521b1d19513d2c618033b01b889807529293721de338f30cd6cf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ef506e10d94521b1d19513d2c618033b01b889807529293721de338f30cd6cf","first_computed_at":"2026-07-05T10:10:27.390512Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:10:27.390512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LfNzcLLPoHbCc4GnNR7feXoI9kq2cYCsjvYaTYdL2jjxr8gAE+oETN+Mj6mLjmmOzt9L3a+VmdgfslquotkZDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:10:27.390983Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.01224","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f650789c49cb0f2a65c04daca08ae8a47c1cf9b2aed2d3a93472ffd99b4379f","sha256:2e7b9e86533eab53f2b2404d64acab0a8f66b8d4d3484e560c5e719a35fcee6b"],"state_sha256":"832eaa93834a24569dde0948311c078f499fe977b4fff83721ae5e33ddf9755f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5tHOO0NkDCMctnZ5822X4XKTgLZBzIAg0QUV5lgGHHLQ3Y+kzQAouzTUZUU9hynK7ANsvZz6SFW8mcLIpm90Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T18:04:41.310399Z","bundle_sha256":"1497343e951b0e05a4553ce7f06e8abf3ecfd6b119d22f7bdf583fef8733d015"}}