{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XYKYDWUJ4X2ACJCDJMBHMGS2KG","short_pith_number":"pith:XYKYDWUJ","canonical_record":{"source":{"id":"2409.07589","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-09-11T19:39:58Z","cross_cats_sorted":["cs.LG","eess.SP"],"title_canon_sha256":"1cd2621fdcf5f520765b44bd48674f955be316d4df720e7876d86876b175d892","abstract_canon_sha256":"9c265d525683e0ca08ba46aec24da140bcdc38507fd5c0272af9e4911ddfcb15"},"schema_version":"1.0"},"canonical_sha256":"be1581da89e5f40124434b02761a5a5193735c588f4af4881da4818ba2c93a98","source":{"kind":"arxiv","id":"2409.07589","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07589","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07589v2","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07589","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_12","alias_value":"XYKYDWUJ4X2A","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_16","alias_value":"XYKYDWUJ4X2ACJCD","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_8","alias_value":"XYKYDWUJ","created_at":"2026-07-07T02:18:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XYKYDWUJ4X2ACJCDJMBHMGS2KG","target":"record","payload":{"canonical_record":{"source":{"id":"2409.07589","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-09-11T19:39:58Z","cross_cats_sorted":["cs.LG","eess.SP"],"title_canon_sha256":"1cd2621fdcf5f520765b44bd48674f955be316d4df720e7876d86876b175d892","abstract_canon_sha256":"9c265d525683e0ca08ba46aec24da140bcdc38507fd5c0272af9e4911ddfcb15"},"schema_version":"1.0"},"canonical_sha256":"be1581da89e5f40124434b02761a5a5193735c588f4af4881da4818ba2c93a98","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T02:18:22.781142Z","signature_b64":"9DyEaOwV2MqnINvMFaZX9W6Ghx4S8E62dSa+zXPNMOIBrE7rIYzNC7Ascvk84B7MDhvRXRWCJMIB+eJmjPRxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"be1581da89e5f40124434b02761a5a5193735c588f4af4881da4818ba2c93a98","last_reissued_at":"2026-07-07T02:18:22.777533Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T02:18:22.777533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.07589","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":"2026-07-07T02:18:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"siVffpK9Uq/2cn226UnurJlBWvZwPEZGuZZJHeocG4B78mIwI5GD6uRcKJ/f9GWe73UrAgsOutjom9siVowRDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:43:07.683652Z"},"content_sha256":"f72d5c4db1b907b0e01a85ee5d4a67a3c6cc0156ffc57966a902ba6923026a64","schema_version":"1.0","event_id":"sha256:f72d5c4db1b907b0e01a85ee5d4a67a3c6cc0156ffc57966a902ba6923026a64"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XYKYDWUJ4X2ACJCDJMBHMGS2KG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"miMamba: EEG-based Emotion Recognition with Multi-scale Inverted Mamba Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP"],"primary_cat":"cs.HC","authors_text":"Dawei Huang, Lijun Yin, Xiaojing Peng, Xin Zhou","submitted_at":"2024-09-11T19:39:58Z","abstract_excerpt":"EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative spatiotemporal features from electroencephalogram (EEG) signals. Existing studies often rely on domain-specific time-frequency features and analyze temporal dependencies and spatial characteristics separately, neglecting the interaction between local-global relationships and spatiotemporal dynamics. To address this, we propose a novel network called Multi-Scale Inverted Mamba (MS-iMamba), which consists of Multi-Scale Temporal Blocks (MSTB) and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07589","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/2409.07589/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":"2026-07-07T02:18:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dOexfc7tkmUzF9vVLoOooguEt+sx87qOBaottR1UBCtfOx5n3sd4pFxt+cQy1xwjU3FPKSpbrqwER1VHGzjXAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:43:07.684025Z"},"content_sha256":"ece1dc1d096a92474df2edb445e71dee599a3f35fd61c51f4c5f6a5808cf2d3f","schema_version":"1.0","event_id":"sha256:ece1dc1d096a92474df2edb445e71dee599a3f35fd61c51f4c5f6a5808cf2d3f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/bundle.json","state_url":"https://pith.science/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/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":"2026-07-08T19:43:07Z","links":{"resolver":"https://pith.science/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG","bundle":"https://pith.science/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/bundle.json","state":"https://pith.science/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XYKYDWUJ4X2ACJCDJMBHMGS2KG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XYKYDWUJ4X2ACJCDJMBHMGS2KG","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":"9c265d525683e0ca08ba46aec24da140bcdc38507fd5c0272af9e4911ddfcb15","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-09-11T19:39:58Z","title_canon_sha256":"1cd2621fdcf5f520765b44bd48674f955be316d4df720e7876d86876b175d892"},"schema_version":"1.0","source":{"id":"2409.07589","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07589","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07589v2","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07589","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_12","alias_value":"XYKYDWUJ4X2A","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_16","alias_value":"XYKYDWUJ4X2ACJCD","created_at":"2026-07-07T02:18:22Z"},{"alias_kind":"pith_short_8","alias_value":"XYKYDWUJ","created_at":"2026-07-07T02:18:22Z"}],"graph_snapshots":[{"event_id":"sha256:ece1dc1d096a92474df2edb445e71dee599a3f35fd61c51f4c5f6a5808cf2d3f","target":"graph","created_at":"2026-07-07T02:18:22Z","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/2409.07589/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative spatiotemporal features from electroencephalogram (EEG) signals. Existing studies often rely on domain-specific time-frequency features and analyze temporal dependencies and spatial characteristics separately, neglecting the interaction between local-global relationships and spatiotemporal dynamics. To address this, we propose a novel network called Multi-Scale Inverted Mamba (MS-iMamba), which consists of Multi-Scale Temporal Blocks (MSTB) and ","authors_text":"Dawei Huang, Lijun Yin, Xiaojing Peng, Xin Zhou","cross_cats":["cs.LG","eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-09-11T19:39:58Z","title":"miMamba: EEG-based Emotion Recognition with Multi-scale Inverted Mamba Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07589","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:f72d5c4db1b907b0e01a85ee5d4a67a3c6cc0156ffc57966a902ba6923026a64","target":"record","created_at":"2026-07-07T02:18:22Z","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":"9c265d525683e0ca08ba46aec24da140bcdc38507fd5c0272af9e4911ddfcb15","cross_cats_sorted":["cs.LG","eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2024-09-11T19:39:58Z","title_canon_sha256":"1cd2621fdcf5f520765b44bd48674f955be316d4df720e7876d86876b175d892"},"schema_version":"1.0","source":{"id":"2409.07589","kind":"arxiv","version":2}},"canonical_sha256":"be1581da89e5f40124434b02761a5a5193735c588f4af4881da4818ba2c93a98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"be1581da89e5f40124434b02761a5a5193735c588f4af4881da4818ba2c93a98","first_computed_at":"2026-07-07T02:18:22.777533Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T02:18:22.777533Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9DyEaOwV2MqnINvMFaZX9W6Ghx4S8E62dSa+zXPNMOIBrE7rIYzNC7Ascvk84B7MDhvRXRWCJMIB+eJmjPRxDQ==","signature_status":"signed_v1","signed_at":"2026-07-07T02:18:22.781142Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.07589","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f72d5c4db1b907b0e01a85ee5d4a67a3c6cc0156ffc57966a902ba6923026a64","sha256:ece1dc1d096a92474df2edb445e71dee599a3f35fd61c51f4c5f6a5808cf2d3f"],"state_sha256":"d6ac7150500ebcdfeff9250a61b46b8ee262a4c562953b203c02deaaed2a1841"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"axls89S5+c9zPYLMnUpoR167k1HTdvOAw8ApmgioEQrUn75b6rVlM42FP3QlPJto2uyj1NMNUuofWgYlImugCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T19:43:07.685935Z","bundle_sha256":"645a4454a08f24c31609431aad3f00953ab0d080e8272f24525ac20b350371e3"}}