{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EIT2V2XPORD6ZIYJBZPCT5QJ6P","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":"021811969bc05e007ec2224fc66b65153f158381b50cc61ddcdfa82acb7b850a","cross_cats_sorted":["cs.MS","quant-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-18T17:57:29Z","title_canon_sha256":"87142a5e91706970e3d19bd1deb70a8be6b6ab70a23da0298dd49f5c24cb17b5"},"schema_version":"1.0","source":{"id":"2502.13090","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.13090","created_at":"2026-07-05T10:16:29Z"},{"alias_kind":"arxiv_version","alias_value":"2502.13090v1","created_at":"2026-07-05T10:16:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.13090","created_at":"2026-07-05T10:16:29Z"},{"alias_kind":"pith_short_12","alias_value":"EIT2V2XPORD6","created_at":"2026-07-05T10:16:29Z"},{"alias_kind":"pith_short_16","alias_value":"EIT2V2XPORD6ZIYJ","created_at":"2026-07-05T10:16:29Z"},{"alias_kind":"pith_short_8","alias_value":"EIT2V2XP","created_at":"2026-07-05T10:16:29Z"}],"graph_snapshots":[{"event_id":"sha256:29e37319e13a38b1fcc60785293543faefc35f751581585d1d9d23ee6a7c986d","target":"graph","created_at":"2026-07-05T10:16:29Z","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/2502.13090/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Tensor Networks have emerged as a prominent alternative to neural networks for addressing Machine Learning challenges in foundational sciences, paving the way for their applications to real-life problems. This paper introduces tn4ml, a novel library designed to seamlessly integrate Tensor Networks into optimization pipelines for Machine Learning tasks. Inspired by existing Machine Learning frameworks, the library offers a user-friendly structure with modules for data embedding, objective function definition, and model training using diverse optimization strategies. We demonstrate its versatili","authors_text":"Artur Garcia-Saez, Ema Puljak, Jofre Vall\\`es-Muns, Maurizio Pierini, Sergi Masot-Llima, Sergio Sanchez-Ramirez","cross_cats":["cs.MS","quant-ph"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-18T17:57:29Z","title":"tn4ml: Tensor Network Training and Customization for Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.13090","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":"sha256:12ddbb25717c5148f92a223c695c9821a74c87841be074f9394c60376e9ee08a","target":"record","created_at":"2026-07-05T10:16:29Z","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":"021811969bc05e007ec2224fc66b65153f158381b50cc61ddcdfa82acb7b850a","cross_cats_sorted":["cs.MS","quant-ph"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-18T17:57:29Z","title_canon_sha256":"87142a5e91706970e3d19bd1deb70a8be6b6ab70a23da0298dd49f5c24cb17b5"},"schema_version":"1.0","source":{"id":"2502.13090","kind":"arxiv","version":1}},"canonical_sha256":"2227aaeaef7447eca3090e5e29f609f3c01562b75fc7ba21a1c676d53ae6afce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2227aaeaef7447eca3090e5e29f609f3c01562b75fc7ba21a1c676d53ae6afce","first_computed_at":"2026-07-05T10:16:29.185193Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:16:29.185193Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+7A58/SPOWt7P5Um54I3v7s9NqI4cfJ9Vr1z6NlAXLRidQivCNQA+JUHRfAWn0rtWhmldNI6hnZb1s+X2zUUDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:16:29.185683Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.13090","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:12ddbb25717c5148f92a223c695c9821a74c87841be074f9394c60376e9ee08a","sha256:29e37319e13a38b1fcc60785293543faefc35f751581585d1d9d23ee6a7c986d"],"state_sha256":"7ab6bd8ecf05c756f7109d2ed2b62462859c5a1c08ff8b4c7669932b8577924e"}