{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DQIOLBSZ3DIFRCVG2R2AZ42ZKA","short_pith_number":"pith:DQIOLBSZ","canonical_record":{"source":{"id":"2502.10463","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-12T08:12:33Z","cross_cats_sorted":["cs.AI","cs.NI"],"title_canon_sha256":"5c2911062e00b2c93baadbf4f8218feca3def4a99fd410fd912a9e8a166e4fd0","abstract_canon_sha256":"81540e7ff62f42669dca5992b2bd559c1e9cfa3f4a68a237edfb568ac285b841"},"schema_version":"1.0"},"canonical_sha256":"1c10e58659d8d0588aa6d4740cf3595030293e6ceb98ff22659925118ca978be","source":{"kind":"arxiv","id":"2502.10463","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.10463","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.10463v1","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.10463","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"DQIOLBSZ3DIF","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"DQIOLBSZ3DIFRCVG","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"DQIOLBSZ","created_at":"2026-07-05T10:14:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DQIOLBSZ3DIFRCVG2R2AZ42ZKA","target":"record","payload":{"canonical_record":{"source":{"id":"2502.10463","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-12T08:12:33Z","cross_cats_sorted":["cs.AI","cs.NI"],"title_canon_sha256":"5c2911062e00b2c93baadbf4f8218feca3def4a99fd410fd912a9e8a166e4fd0","abstract_canon_sha256":"81540e7ff62f42669dca5992b2bd559c1e9cfa3f4a68a237edfb568ac285b841"},"schema_version":"1.0"},"canonical_sha256":"1c10e58659d8d0588aa6d4740cf3595030293e6ceb98ff22659925118ca978be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:14:53.097453Z","signature_b64":"BYUUSCUl4koTL0KtjfF4GrJmrQgf0A/iKFtqDuPE/WMMZWxalJ9I24nAVmPF8BFCRao/CCGBjlKqMo5ITBqYBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c10e58659d8d0588aa6d4740cf3595030293e6ceb98ff22659925118ca978be","last_reissued_at":"2026-07-05T10:14:53.096945Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:14:53.096945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.10463","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FSU9M158aE7BLeE8WOSWMs4H9FLEWEfkk7Ab1JvoR25seEAYsfs3oyiUwZ1PelANEvEW24QsbYahdNhKCFY5AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T00:43:29.584554Z"},"content_sha256":"a76f6520f911b49886a7f0f01bf871f42a75fd0d18acc55494aa79badd803eac","schema_version":"1.0","event_id":"sha256:a76f6520f911b49886a7f0f01bf871f42a75fd0d18acc55494aa79badd803eac"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DQIOLBSZ3DIFRCVG2R2AZ42ZKA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.NI"],"primary_cat":"cs.LG","authors_text":"Guodong Li, Lequan Yu, Qinshuo Liu, Wei Huang, Weiqin Zhao, Yanwen Fang","submitted_at":"2025-02-12T08:12:33Z","abstract_excerpt":"The depth of neural networks is a critical factor for their capability, with deeper models often demonstrating superior performance. Motivated by this, significant efforts have been made to enhance layer aggregation - reusing information from previous layers to better extract features at the current layer, to improve the representational power of deep neural networks. However, previous works have primarily addressed this problem from a discrete-state perspective which is not suitable as the number of network layers grows. This paper novelly treats the outputs from layers as states of a continu"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.10463","kind":"arxiv","version":1},"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/2502.10463/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":"2026-07-05T10:14:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2BbLmKUvsJqMUqF0DVwSDyOBeuk9P4S7ZtLD9E34j3f1gAXRmEW+fwGn9TgWIgP7ga2bZcIX8l7yfl/s8aAVAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T00:43:29.584932Z"},"content_sha256":"bf53095bdfadf0764077c7d1a0148c8f8d4197ec1d1fa5d0b57dc7bdc8896fd5","schema_version":"1.0","event_id":"sha256:bf53095bdfadf0764077c7d1a0148c8f8d4197ec1d1fa5d0b57dc7bdc8896fd5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/bundle.json","state_url":"https://pith.science/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/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":"2026-07-09T00:43:29Z","links":{"resolver":"https://pith.science/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA","bundle":"https://pith.science/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/bundle.json","state":"https://pith.science/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DQIOLBSZ3DIFRCVG2R2AZ42ZKA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DQIOLBSZ3DIFRCVG2R2AZ42ZKA","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":"81540e7ff62f42669dca5992b2bd559c1e9cfa3f4a68a237edfb568ac285b841","cross_cats_sorted":["cs.AI","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-12T08:12:33Z","title_canon_sha256":"5c2911062e00b2c93baadbf4f8218feca3def4a99fd410fd912a9e8a166e4fd0"},"schema_version":"1.0","source":{"id":"2502.10463","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.10463","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.10463v1","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.10463","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_12","alias_value":"DQIOLBSZ3DIF","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_16","alias_value":"DQIOLBSZ3DIFRCVG","created_at":"2026-07-05T10:14:53Z"},{"alias_kind":"pith_short_8","alias_value":"DQIOLBSZ","created_at":"2026-07-05T10:14:53Z"}],"graph_snapshots":[{"event_id":"sha256:bf53095bdfadf0764077c7d1a0148c8f8d4197ec1d1fa5d0b57dc7bdc8896fd5","target":"graph","created_at":"2026-07-05T10:14:53Z","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/2502.10463/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The depth of neural networks is a critical factor for their capability, with deeper models often demonstrating superior performance. Motivated by this, significant efforts have been made to enhance layer aggregation - reusing information from previous layers to better extract features at the current layer, to improve the representational power of deep neural networks. However, previous works have primarily addressed this problem from a discrete-state perspective which is not suitable as the number of network layers grows. This paper novelly treats the outputs from layers as states of a continu","authors_text":"Guodong Li, Lequan Yu, Qinshuo Liu, Wei Huang, Weiqin Zhao, Yanwen Fang","cross_cats":["cs.AI","cs.NI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-12T08:12:33Z","title":"From Layers to States: A State Space Model Perspective to Deep Neural Network Layer Dynamics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.10463","kind":"arxiv","version":1},"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:a76f6520f911b49886a7f0f01bf871f42a75fd0d18acc55494aa79badd803eac","target":"record","created_at":"2026-07-05T10:14:53Z","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":"81540e7ff62f42669dca5992b2bd559c1e9cfa3f4a68a237edfb568ac285b841","cross_cats_sorted":["cs.AI","cs.NI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-12T08:12:33Z","title_canon_sha256":"5c2911062e00b2c93baadbf4f8218feca3def4a99fd410fd912a9e8a166e4fd0"},"schema_version":"1.0","source":{"id":"2502.10463","kind":"arxiv","version":1}},"canonical_sha256":"1c10e58659d8d0588aa6d4740cf3595030293e6ceb98ff22659925118ca978be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c10e58659d8d0588aa6d4740cf3595030293e6ceb98ff22659925118ca978be","first_computed_at":"2026-07-05T10:14:53.096945Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:14:53.096945Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BYUUSCUl4koTL0KtjfF4GrJmrQgf0A/iKFtqDuPE/WMMZWxalJ9I24nAVmPF8BFCRao/CCGBjlKqMo5ITBqYBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:14:53.097453Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.10463","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a76f6520f911b49886a7f0f01bf871f42a75fd0d18acc55494aa79badd803eac","sha256:bf53095bdfadf0764077c7d1a0148c8f8d4197ec1d1fa5d0b57dc7bdc8896fd5"],"state_sha256":"6440e43d166a4044a6bb099dac587857f436bf26d2cdf54511140025f57a0075"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XKK/KXRwgDfjU8y5WKejV3Tml2xAdRCw8f2x2MRkddhzhRiMQ54pWnyYk+4+Q4ikVh6Szj1TEOsbFnsNrlayAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T00:43:29.587116Z","bundle_sha256":"407a1e150031e5a247e4df233008411e61a578c2194ca094f6ce5aef13e0df95"}}