{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:JESONGUVRAMSWG64GADSRO6MXR","short_pith_number":"pith:JESONGUV","canonical_record":{"source":{"id":"2605.29153","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-27T22:33:03Z","cross_cats_sorted":["cs.AI","physics.comp-ph"],"title_canon_sha256":"056ac46726c11081c2f362c115e7f5aa98815e4444200100f7b3c053b4703ef5","abstract_canon_sha256":"02f34889040167f194ebd34b08f081305f6132aafdcf4bba7414b4b322f07575"},"schema_version":"1.0"},"canonical_sha256":"4924e69a9588192b1bdc300728bbccbc6780a075075ea1e72611dbbd783075c1","source":{"kind":"arxiv","id":"2605.29153","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29153","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29153v1","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29153","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_12","alias_value":"JESONGUVRAMS","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_16","alias_value":"JESONGUVRAMSWG64","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_8","alias_value":"JESONGUV","created_at":"2026-05-29T01:05:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:JESONGUVRAMSWG64GADSRO6MXR","target":"record","payload":{"canonical_record":{"source":{"id":"2605.29153","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-27T22:33:03Z","cross_cats_sorted":["cs.AI","physics.comp-ph"],"title_canon_sha256":"056ac46726c11081c2f362c115e7f5aa98815e4444200100f7b3c053b4703ef5","abstract_canon_sha256":"02f34889040167f194ebd34b08f081305f6132aafdcf4bba7414b4b322f07575"},"schema_version":"1.0"},"canonical_sha256":"4924e69a9588192b1bdc300728bbccbc6780a075075ea1e72611dbbd783075c1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:05:21.208444Z","signature_b64":"3KD2g1jK2IZ+VOIJfWOTrArDbmkOjsvbVyQU+HxNvaede4L4zM4YxjGpj3MJUipgT1bNlQEEjPE+RH2RNgAPBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4924e69a9588192b1bdc300728bbccbc6780a075075ea1e72611dbbd783075c1","last_reissued_at":"2026-05-29T01:05:21.207518Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:05:21.207518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.29153","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":"2026-05-29T01:05:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"o5/bGJLqbXXpoNXzlsYPDuEJIWjcN200q0/v2WTuMRRgiGW8b0bwSxkBYf7DxH/eH8/Ti++ezzSAB0QgRRhPBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:49:42.879979Z"},"content_sha256":"f1c71cac53ee10b6d6266a86edf20df6e6b280f94a520319e4b0d8cbdfa80890","schema_version":"1.0","event_id":"sha256:f1c71cac53ee10b6d6266a86edf20df6e6b280f94a520319e4b0d8cbdfa80890"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:JESONGUVRAMSWG64GADSRO6MXR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","physics.comp-ph"],"primary_cat":"cs.LG","authors_text":"Haiquan Lu, Michael W. Mahoney, Pu Ren, Tianyu Pang, Xiaokun Zhong, Xiaopeng Wang, Yaoqing Yang, Yuanzhe Hu, Yujun Yan, Yuxin Wang","submitted_at":"2026-05-27T22:33:03Z","abstract_excerpt":"Neural networks trained under different hyperparameter settings can fall into distinct training \"regimes,\" with consistent behavior within regimes and qualitative differences across regimes. In this paper, we study such multi-regime behavior in scientific machine learning (SciML) models through a regime-aware diagnostic framework that jointly analyzes performance, training dynamics, and loss-landscape geometry. We identify three key findings: (i) a consistent three-regime structure emerges across many standard SciML models, different constraint enforcements, and various optimizer designs; (ii)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29153","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/2605.29153/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":"2026-05-29T01:05:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OVjor7qqPZPVLzu+uWyH1gzOf4SWBzZh4dj2JeX3eqBDidINzeYmylAWXvPVLVK8TgOf4Qeqm4Jw2cqdBAVbAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T13:49:42.880768Z"},"content_sha256":"3041165f6590b8b2ec98dad62996066549fc00145158b32f479e878e0bc696f2","schema_version":"1.0","event_id":"sha256:3041165f6590b8b2ec98dad62996066549fc00145158b32f479e878e0bc696f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JESONGUVRAMSWG64GADSRO6MXR/bundle.json","state_url":"https://pith.science/pith/JESONGUVRAMSWG64GADSRO6MXR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JESONGUVRAMSWG64GADSRO6MXR/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":"2026-05-31T13:49:42Z","links":{"resolver":"https://pith.science/pith/JESONGUVRAMSWG64GADSRO6MXR","bundle":"https://pith.science/pith/JESONGUVRAMSWG64GADSRO6MXR/bundle.json","state":"https://pith.science/pith/JESONGUVRAMSWG64GADSRO6MXR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JESONGUVRAMSWG64GADSRO6MXR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JESONGUVRAMSWG64GADSRO6MXR","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":"02f34889040167f194ebd34b08f081305f6132aafdcf4bba7414b4b322f07575","cross_cats_sorted":["cs.AI","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-27T22:33:03Z","title_canon_sha256":"056ac46726c11081c2f362c115e7f5aa98815e4444200100f7b3c053b4703ef5"},"schema_version":"1.0","source":{"id":"2605.29153","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29153","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29153v1","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29153","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_12","alias_value":"JESONGUVRAMS","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_16","alias_value":"JESONGUVRAMSWG64","created_at":"2026-05-29T01:05:21Z"},{"alias_kind":"pith_short_8","alias_value":"JESONGUV","created_at":"2026-05-29T01:05:21Z"}],"graph_snapshots":[{"event_id":"sha256:3041165f6590b8b2ec98dad62996066549fc00145158b32f479e878e0bc696f2","target":"graph","created_at":"2026-05-29T01:05:21Z","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/2605.29153/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Neural networks trained under different hyperparameter settings can fall into distinct training \"regimes,\" with consistent behavior within regimes and qualitative differences across regimes. In this paper, we study such multi-regime behavior in scientific machine learning (SciML) models through a regime-aware diagnostic framework that jointly analyzes performance, training dynamics, and loss-landscape geometry. We identify three key findings: (i) a consistent three-regime structure emerges across many standard SciML models, different constraint enforcements, and various optimizer designs; (ii)","authors_text":"Haiquan Lu, Michael W. Mahoney, Pu Ren, Tianyu Pang, Xiaokun Zhong, Xiaopeng Wang, Yaoqing Yang, Yuanzhe Hu, Yujun Yan, Yuxin Wang","cross_cats":["cs.AI","physics.comp-ph"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-27T22:33:03Z","title":"Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29153","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:f1c71cac53ee10b6d6266a86edf20df6e6b280f94a520319e4b0d8cbdfa80890","target":"record","created_at":"2026-05-29T01:05:21Z","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":"02f34889040167f194ebd34b08f081305f6132aafdcf4bba7414b4b322f07575","cross_cats_sorted":["cs.AI","physics.comp-ph"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-27T22:33:03Z","title_canon_sha256":"056ac46726c11081c2f362c115e7f5aa98815e4444200100f7b3c053b4703ef5"},"schema_version":"1.0","source":{"id":"2605.29153","kind":"arxiv","version":1}},"canonical_sha256":"4924e69a9588192b1bdc300728bbccbc6780a075075ea1e72611dbbd783075c1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4924e69a9588192b1bdc300728bbccbc6780a075075ea1e72611dbbd783075c1","first_computed_at":"2026-05-29T01:05:21.207518Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:05:21.207518Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3KD2g1jK2IZ+VOIJfWOTrArDbmkOjsvbVyQU+HxNvaede4L4zM4YxjGpj3MJUipgT1bNlQEEjPE+RH2RNgAPBw==","signature_status":"signed_v1","signed_at":"2026-05-29T01:05:21.208444Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.29153","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f1c71cac53ee10b6d6266a86edf20df6e6b280f94a520319e4b0d8cbdfa80890","sha256:3041165f6590b8b2ec98dad62996066549fc00145158b32f479e878e0bc696f2"],"state_sha256":"a8ffccd4b3ae370433d7e722fe029a5dd1edef85c110f9449fe376c775b428fd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lAyw73BQ43kSti7ynGWze5WUwhNXZsb+PU47FhxemMC8SPvrwL+fvSJ+pszDTDAgnR4HDkeLmMb05/Fo9ztvDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T13:49:42.884677Z","bundle_sha256":"a9bdf44e8107572304cabf08c41d363281d489e0aee3759fa87e82dc70d4fc27"}}