{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:CCOR5OMKSMFUGVOPMZ6EKOSNKR","short_pith_number":"pith:CCOR5OMK","canonical_record":{"source":{"id":"2505.03806","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-02T09:08:07Z","cross_cats_sorted":["cs.AI","cs.NE"],"title_canon_sha256":"46d40be5d5653770afee4a65f755990130627dbc42a4140c9e7e1b109db55c3d","abstract_canon_sha256":"d5f38132eb4fa185b9cae6072619e5283f7a0682511151a8350d94e58131bcbc"},"schema_version":"1.0"},"canonical_sha256":"109d1eb98a930b4355cf667c453a4d54732fda73c3a03c101a39873e24dfebd2","source":{"kind":"arxiv","id":"2505.03806","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.03806","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"arxiv_version","alias_value":"2505.03806v2","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03806","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_12","alias_value":"CCOR5OMKSMFU","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_16","alias_value":"CCOR5OMKSMFUGVOP","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_8","alias_value":"CCOR5OMK","created_at":"2026-07-05T11:08:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:CCOR5OMKSMFUGVOPMZ6EKOSNKR","target":"record","payload":{"canonical_record":{"source":{"id":"2505.03806","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-02T09:08:07Z","cross_cats_sorted":["cs.AI","cs.NE"],"title_canon_sha256":"46d40be5d5653770afee4a65f755990130627dbc42a4140c9e7e1b109db55c3d","abstract_canon_sha256":"d5f38132eb4fa185b9cae6072619e5283f7a0682511151a8350d94e58131bcbc"},"schema_version":"1.0"},"canonical_sha256":"109d1eb98a930b4355cf667c453a4d54732fda73c3a03c101a39873e24dfebd2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:41.098123Z","signature_b64":"m5Yr+hiRDVCdDq5kr9XMV6IGIx87gYCpMTzzmA/vXkOGZh7/f0rxh0rSXqJmK1078242fZitcsnKsYzg0vGjCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"109d1eb98a930b4355cf667c453a4d54732fda73c3a03c101a39873e24dfebd2","last_reissued_at":"2026-07-05T11:08:41.097680Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:41.097680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.03806","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":"2026-07-05T11:08:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aXr9KaT23fTRtOCKMmMB4+ojpitTh5Zg6CM37pt1svfaGHIQNF7qwP5hG+aKh8fXUUKsr1hg2EFF7Rn5/TKkDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:22:12.015765Z"},"content_sha256":"8ea84cf0355fa157af12e37bce24e1c6bb24105c67ad3b2d369e0e7b998d32bc","schema_version":"1.0","event_id":"sha256:8ea84cf0355fa157af12e37bce24e1c6bb24105c67ad3b2d369e0e7b998d32bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:CCOR5OMKSMFUGVOPMZ6EKOSNKR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.NE"],"primary_cat":"cs.LG","authors_text":"Marzieh Najariyan, Mehran Mazandarani","submitted_at":"2025-05-02T09:08:07Z","abstract_excerpt":"This article introduces Perception-Informed Neural Networks (PrINNs), a framework designed to incorporate perception-based information into neural networks, addressing both systems with known and unknown physics laws or differential equations. Moreover, PrINNs extend the concept of Physics-Informed Neural Networks (PINNs) and their variants, offering a platform for the integration of diverse forms of perception precisiation, including singular, probability distribution, possibility distribution, interval, and fuzzy graph. In fact, PrINNs allow neural networks to model dynamical systems by inte"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03806","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/2505.03806/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":"2026-07-05T11:08:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ybOvzmfp732y+cxGMOF2NtHHKzxiAZmLUr4ZcUQXB1FmN53/Gzh5BYQDXavrnGEmo7uckzF+m7ahLz0SXxmlBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T13:22:12.016270Z"},"content_sha256":"eb0ce54cc18651e3ae0227e1a2041147d48e9185b9555f7f825dfbea115d3847","schema_version":"1.0","event_id":"sha256:eb0ce54cc18651e3ae0227e1a2041147d48e9185b9555f7f825dfbea115d3847"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/bundle.json","state_url":"https://pith.science/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/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":"2026-08-20T13:22:12Z","links":{"resolver":"https://pith.science/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR","bundle":"https://pith.science/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/bundle.json","state":"https://pith.science/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CCOR5OMKSMFUGVOPMZ6EKOSNKR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CCOR5OMKSMFUGVOPMZ6EKOSNKR","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":"d5f38132eb4fa185b9cae6072619e5283f7a0682511151a8350d94e58131bcbc","cross_cats_sorted":["cs.AI","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-02T09:08:07Z","title_canon_sha256":"46d40be5d5653770afee4a65f755990130627dbc42a4140c9e7e1b109db55c3d"},"schema_version":"1.0","source":{"id":"2505.03806","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.03806","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"arxiv_version","alias_value":"2505.03806v2","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03806","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_12","alias_value":"CCOR5OMKSMFU","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_16","alias_value":"CCOR5OMKSMFUGVOP","created_at":"2026-07-05T11:08:41Z"},{"alias_kind":"pith_short_8","alias_value":"CCOR5OMK","created_at":"2026-07-05T11:08:41Z"}],"graph_snapshots":[{"event_id":"sha256:eb0ce54cc18651e3ae0227e1a2041147d48e9185b9555f7f825dfbea115d3847","target":"graph","created_at":"2026-07-05T11:08:41Z","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/2505.03806/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This article introduces Perception-Informed Neural Networks (PrINNs), a framework designed to incorporate perception-based information into neural networks, addressing both systems with known and unknown physics laws or differential equations. Moreover, PrINNs extend the concept of Physics-Informed Neural Networks (PINNs) and their variants, offering a platform for the integration of diverse forms of perception precisiation, including singular, probability distribution, possibility distribution, interval, and fuzzy graph. In fact, PrINNs allow neural networks to model dynamical systems by inte","authors_text":"Marzieh Najariyan, Mehran Mazandarani","cross_cats":["cs.AI","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-02T09:08:07Z","title":"Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03806","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":"sha256:8ea84cf0355fa157af12e37bce24e1c6bb24105c67ad3b2d369e0e7b998d32bc","target":"record","created_at":"2026-07-05T11:08:41Z","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":"d5f38132eb4fa185b9cae6072619e5283f7a0682511151a8350d94e58131bcbc","cross_cats_sorted":["cs.AI","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-02T09:08:07Z","title_canon_sha256":"46d40be5d5653770afee4a65f755990130627dbc42a4140c9e7e1b109db55c3d"},"schema_version":"1.0","source":{"id":"2505.03806","kind":"arxiv","version":2}},"canonical_sha256":"109d1eb98a930b4355cf667c453a4d54732fda73c3a03c101a39873e24dfebd2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"109d1eb98a930b4355cf667c453a4d54732fda73c3a03c101a39873e24dfebd2","first_computed_at":"2026-07-05T11:08:41.097680Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:41.097680Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"m5Yr+hiRDVCdDq5kr9XMV6IGIx87gYCpMTzzmA/vXkOGZh7/f0rxh0rSXqJmK1078242fZitcsnKsYzg0vGjCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:41.098123Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.03806","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8ea84cf0355fa157af12e37bce24e1c6bb24105c67ad3b2d369e0e7b998d32bc","sha256:eb0ce54cc18651e3ae0227e1a2041147d48e9185b9555f7f825dfbea115d3847"],"state_sha256":"c766e2e7c6aa4655cf089277b6ea973373e7f6ef16604ad7b56f015f7d67aa94"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HshRhUTXjKlAMiNqgE2fYGtmXd/sg38BMgn4Z9dHyvkhD3li4w9Tk2TqLeoFFrbT2BWwV6kgUludLHXSH3tMAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T13:22:12.021441Z","bundle_sha256":"881a7e0adbf14575f501fc000d0020edfef01cb439817a6af9cde69d67368d55"}}