{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:DFO7FX5VSZPXZZ33JBCMUBRPSZ","short_pith_number":"pith:DFO7FX5V","canonical_record":{"source":{"id":"2602.15021","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-02-16T18:58:47Z","cross_cats_sorted":["astro-ph.GA","cs.LG"],"title_canon_sha256":"ca8bff0433e07a85d408f9be39f45d0c0256cf193f564a7ae8c7335f08e6c12b","abstract_canon_sha256":"b3c2b140fc109fa72aa9a89d81b2254cd40e83065b98d7c28dba5a433cbf6037"},"schema_version":"1.0"},"canonical_sha256":"195df2dfb5965f7ce77b4844ca062f966207df557c854ebd6edae291853292a4","source":{"kind":"arxiv","id":"2602.15021","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.15021","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"arxiv_version","alias_value":"2602.15021v2","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.15021","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_12","alias_value":"DFO7FX5VSZPX","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_16","alias_value":"DFO7FX5VSZPXZZ33","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_8","alias_value":"DFO7FX5V","created_at":"2026-07-29T01:25:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:DFO7FX5VSZPXZZ33JBCMUBRPSZ","target":"record","payload":{"canonical_record":{"source":{"id":"2602.15021","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-02-16T18:58:47Z","cross_cats_sorted":["astro-ph.GA","cs.LG"],"title_canon_sha256":"ca8bff0433e07a85d408f9be39f45d0c0256cf193f564a7ae8c7335f08e6c12b","abstract_canon_sha256":"b3c2b140fc109fa72aa9a89d81b2254cd40e83065b98d7c28dba5a433cbf6037"},"schema_version":"1.0"},"canonical_sha256":"195df2dfb5965f7ce77b4844ca062f966207df557c854ebd6edae291853292a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-29T01:25:34.895509Z","signature_b64":"MqHmHdu5biyxj+15Kgn/+Fr812G/I8Gks8sOUZTUM0tsCWW8T95wHNQiT7XUUXOQwSIGo0eK8a6t/9hWSeS4AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"195df2dfb5965f7ce77b4844ca062f966207df557c854ebd6edae291853292a4","last_reissued_at":"2026-07-29T01:25:34.894542Z","signature_status":"signed_v1","first_computed_at":"2026-07-29T01:25:34.894542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.15021","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":"2026-07-29T01:25:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JijYEOpNqLFm1Y9Fairck7EhHRyH3piTbwiH0PMKJ7V8z6FQKbqx8GvydV4bRXknhe3OOKc7iU4vbfMJFUnLCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:03:59.741303Z"},"content_sha256":"740b1dba95fca745118ff20445863588f9fae1ecb700fa1895f4321dee236ec2","schema_version":"1.0","event_id":"sha256:740b1dba95fca745118ff20445863588f9fae1ecb700fa1895f4321dee236ec2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:DFO7FX5VSZPXZZ33JBCMUBRPSZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["astro-ph.GA","cs.LG"],"primary_cat":"astro-ph.SR","authors_text":"Alexander S. Szalay, L\\'aszl\\'o Dobos, Rosemary F.G. Wyse, Tam\\'as Budav\\'ari, Viska Wei, Xiaosheng Zhao, Yang Huang, Yuan-Sen Ting","submitted_at":"2026-02-16T18:58:47Z","abstract_excerpt":"Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to moderate-resolution surveys. We investigate this problem using pre-trained models, focusing on simple neural networks such as multilayer perceptrons (MLPs), with a case study transferring from LAMOST low-resolution spectra (LRS) to DESI medium-resolution spectra (MRS). Specifically, we pre-train MLPs on either LRS or their embeddings and fine-tune them for application to DESI stellar spectra. We compare MLPs trained directly on spectra with those trained on "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.15021","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/2602.15021/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":"2026-07-29T01:25:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z0r4KtHjT15d2TaspE2nQhavb2buiLBvtvgSPWXvEiCYKw0wK0YS9LRX976+DzLQ6wpNrnCdg0/H82EU6xwzDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T12:03:59.741937Z"},"content_sha256":"5dff12ca887eed8650e111f1d995d528d64d32c71e4a8e2e802d61c4764585d0","schema_version":"1.0","event_id":"sha256:5dff12ca887eed8650e111f1d995d528d64d32c71e4a8e2e802d61c4764585d0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/bundle.json","state_url":"https://pith.science/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/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":"2026-08-05T12:03:59Z","links":{"resolver":"https://pith.science/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ","bundle":"https://pith.science/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/bundle.json","state":"https://pith.science/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DFO7FX5VSZPXZZ33JBCMUBRPSZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:DFO7FX5VSZPXZZ33JBCMUBRPSZ","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":"b3c2b140fc109fa72aa9a89d81b2254cd40e83065b98d7c28dba5a433cbf6037","cross_cats_sorted":["astro-ph.GA","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-02-16T18:58:47Z","title_canon_sha256":"ca8bff0433e07a85d408f9be39f45d0c0256cf193f564a7ae8c7335f08e6c12b"},"schema_version":"1.0","source":{"id":"2602.15021","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.15021","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"arxiv_version","alias_value":"2602.15021v2","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.15021","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_12","alias_value":"DFO7FX5VSZPX","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_16","alias_value":"DFO7FX5VSZPXZZ33","created_at":"2026-07-29T01:25:34Z"},{"alias_kind":"pith_short_8","alias_value":"DFO7FX5V","created_at":"2026-07-29T01:25:34Z"}],"graph_snapshots":[{"event_id":"sha256:5dff12ca887eed8650e111f1d995d528d64d32c71e4a8e2e802d61c4764585d0","target":"graph","created_at":"2026-07-29T01:25:34Z","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/2602.15021/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cross-survey generalization is a critical challenge in stellar spectral analysis, particularly in cases such as transferring from low- to moderate-resolution surveys. We investigate this problem using pre-trained models, focusing on simple neural networks such as multilayer perceptrons (MLPs), with a case study transferring from LAMOST low-resolution spectra (LRS) to DESI medium-resolution spectra (MRS). Specifically, we pre-train MLPs on either LRS or their embeddings and fine-tune them for application to DESI stellar spectra. We compare MLPs trained directly on spectra with those trained on ","authors_text":"Alexander S. Szalay, L\\'aszl\\'o Dobos, Rosemary F.G. Wyse, Tam\\'as Budav\\'ari, Viska Wei, Xiaosheng Zhao, Yang Huang, Yuan-Sen Ting","cross_cats":["astro-ph.GA","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-02-16T18:58:47Z","title":"Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.15021","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":"sha256:740b1dba95fca745118ff20445863588f9fae1ecb700fa1895f4321dee236ec2","target":"record","created_at":"2026-07-29T01:25:34Z","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":"b3c2b140fc109fa72aa9a89d81b2254cd40e83065b98d7c28dba5a433cbf6037","cross_cats_sorted":["astro-ph.GA","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-02-16T18:58:47Z","title_canon_sha256":"ca8bff0433e07a85d408f9be39f45d0c0256cf193f564a7ae8c7335f08e6c12b"},"schema_version":"1.0","source":{"id":"2602.15021","kind":"arxiv","version":2}},"canonical_sha256":"195df2dfb5965f7ce77b4844ca062f966207df557c854ebd6edae291853292a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"195df2dfb5965f7ce77b4844ca062f966207df557c854ebd6edae291853292a4","first_computed_at":"2026-07-29T01:25:34.894542Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-29T01:25:34.894542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MqHmHdu5biyxj+15Kgn/+Fr812G/I8Gks8sOUZTUM0tsCWW8T95wHNQiT7XUUXOQwSIGo0eK8a6t/9hWSeS4AA==","signature_status":"signed_v1","signed_at":"2026-07-29T01:25:34.895509Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.15021","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:740b1dba95fca745118ff20445863588f9fae1ecb700fa1895f4321dee236ec2","sha256:5dff12ca887eed8650e111f1d995d528d64d32c71e4a8e2e802d61c4764585d0"],"state_sha256":"2a704df52cf18c4266adc727469eb2b29c6ae6257b37e653616ffcaa4eb64f2a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3x8slmS/LkjCba/RF2TQDXH+qXfHgrAZ+0w29JqcpojN5l1avVd98en5mve6ivdSOEqaXvfOHsHN89nmlZ9mDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T12:03:59.746257Z","bundle_sha256":"7d3414233807d6218cae3c8b82d3de15f936677c0a3c0401135c94f4ae6c3923"}}