{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VAFMMPJFOPTNSGWES2BUERJOIM","short_pith_number":"pith:VAFMMPJF","schema_version":"1.0","canonical_sha256":"a80ac63d2573e6d91ac4968342452e4320a9420348ae833ac5d7d970c51e1579","source":{"kind":"arxiv","id":"2607.29088","version":1},"attestation_state":"computed","paper":{"title":"Learning transferable event representations for charmed baryon physics at BESIII","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["hep-ex"],"primary_cat":"physics.data-an","authors_text":"Junpeng Zhao, Kaixuan Huang, Peilian Li, Peirong Li, Shengsen Sun, Xiaorui Lyu, Yangheng Zheng, Yangu Li, Yunxuan Song","submitted_at":"2026-07-31T07:14:07Z","abstract_excerpt":"Deep learning has become an essential tool in high-energy physics, where the ability to learn transferable event representations can significantly improve model generalization across related physics processes. In this work, we present a Particle Transformer-based framework for learning such representations for charmed baryon physics in the BESIII experiment. The framework is implemented through large-scale pre-training on Monte Carlo simulation samples and subsequent fine-tuning for downstream analyses. Using the production and decays of the charmed baryon $\\Lambda_c^+$ as a benchmark, we deve"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.29088","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.data-an","submitted_at":"2026-07-31T07:14:07Z","cross_cats_sorted":["hep-ex"],"title_canon_sha256":"e962d5f98c9f617bc1bedf928b206b96d946cbf8e895aea7cd9c66a74d01f1de","abstract_canon_sha256":"7a0c8a4436cb224f7157f096ca2e1b8ccde6e6d2b7c77ea87b4df5c86f0a09a6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:19:06.185089Z","signature_b64":"o51fIGm824gX/44TWr6afuP+eN9jdHFj8I8vcYCmv5tOEPQGlb5zMZ81ggl9/OQgGr6bVe+Yf9xO4+pGw+jWCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a80ac63d2573e6d91ac4968342452e4320a9420348ae833ac5d7d970c51e1579","last_reissued_at":"2026-08-03T01:19:06.183474Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:19:06.183474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning transferable event representations for charmed baryon physics at BESIII","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["hep-ex"],"primary_cat":"physics.data-an","authors_text":"Junpeng Zhao, Kaixuan Huang, Peilian Li, Peirong Li, Shengsen Sun, Xiaorui Lyu, Yangheng Zheng, Yangu Li, Yunxuan Song","submitted_at":"2026-07-31T07:14:07Z","abstract_excerpt":"Deep learning has become an essential tool in high-energy physics, where the ability to learn transferable event representations can significantly improve model generalization across related physics processes. In this work, we present a Particle Transformer-based framework for learning such representations for charmed baryon physics in the BESIII experiment. The framework is implemented through large-scale pre-training on Monte Carlo simulation samples and subsequent fine-tuning for downstream analyses. Using the production and decays of the charmed baryon $\\Lambda_c^+$ as a benchmark, we deve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.29088","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/2607.29088/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.29088","created_at":"2026-08-03T01:19:06.184413+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.29088v1","created_at":"2026-08-03T01:19:06.184413+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.29088","created_at":"2026-08-03T01:19:06.184413+00:00"},{"alias_kind":"pith_short_12","alias_value":"VAFMMPJFOPTN","created_at":"2026-08-03T01:19:06.184413+00:00"},{"alias_kind":"pith_short_16","alias_value":"VAFMMPJFOPTNSGWE","created_at":"2026-08-03T01:19:06.184413+00:00"},{"alias_kind":"pith_short_8","alias_value":"VAFMMPJF","created_at":"2026-08-03T01:19:06.184413+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM","json":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM.json","graph_json":"https://pith.science/api/pith-number/VAFMMPJFOPTNSGWES2BUERJOIM/graph.json","events_json":"https://pith.science/api/pith-number/VAFMMPJFOPTNSGWES2BUERJOIM/events.json","paper":"https://pith.science/paper/VAFMMPJF"},"agent_actions":{"view_html":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM","download_json":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM.json","view_paper":"https://pith.science/paper/VAFMMPJF","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.29088&json=true","fetch_graph":"https://pith.science/api/pith-number/VAFMMPJFOPTNSGWES2BUERJOIM/graph.json","fetch_events":"https://pith.science/api/pith-number/VAFMMPJFOPTNSGWES2BUERJOIM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM/action/storage_attestation","attest_author":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM/action/author_attestation","sign_citation":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM/action/citation_signature","submit_replication":"https://pith.science/pith/VAFMMPJFOPTNSGWES2BUERJOIM/action/replication_record"}},"created_at":"2026-08-03T01:19:06.184413+00:00","updated_at":"2026-08-03T01:19:06.184413+00:00"}