{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:IUSIJHNPFRZ7QJTOWX3QM2E4JQ","short_pith_number":"pith:IUSIJHNP","schema_version":"1.0","canonical_sha256":"4524849daf2c73f8266eb5f706689c4c0361fbb5ed81a7775523396a8d145d81","source":{"kind":"arxiv","id":"2606.10381","version":1},"attestation_state":"computed","paper":{"title":"Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.IR","physics.ins-det"],"primary_cat":"hep-ex","authors_text":"Cheng Jiang, Dawei Fu, Qiang Li, Ruobing Jiang, Tianyi Yang, Yajun Mao, Yong Ban, Youpeng Wu, Zijian Wang","submitted_at":"2026-06-09T03:42:50Z","abstract_excerpt":"Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a rapidly expanding and heterogeneous body of scientific literature. As high-energy physics (HEP) increasingly explores agent-assisted analysis workflows, efficiently locating, integrating, and verifying scientific evidence becomes an essential capability. While retrieval-augmented generation (RAG) offers a promising framework for scientific question answering, integrating agentic reasoning without compromising retrieval precision remains a key chal"},"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":"2606.10381","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ex","submitted_at":"2026-06-09T03:42:50Z","cross_cats_sorted":["cs.AI","cs.CL","cs.IR","physics.ins-det"],"title_canon_sha256":"8676ed64f9d251b5daa59188b2bbe7d72f20ae8e48a014f9f8eb7481e611ae2a","abstract_canon_sha256":"b166b0876c24f8baf635e7961aba3de23d95090bf3fd148f83d1c630f98f5f75"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:10:14.950058Z","signature_b64":"nBGOlj46V3iK3Jxq4wL0GCXhELCpdQqcI8MJTm01V20cofqSTjIw+RUQMULvKfwordNsHTpq6S1GiUFFrihIDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4524849daf2c73f8266eb5f706689c4c0361fbb5ed81a7775523396a8d145d81","last_reissued_at":"2026-06-10T01:10:14.949221Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:10:14.949221Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.IR","physics.ins-det"],"primary_cat":"hep-ex","authors_text":"Cheng Jiang, Dawei Fu, Qiang Li, Ruobing Jiang, Tianyi Yang, Yajun Mao, Yong Ban, Youpeng Wu, Zijian Wang","submitted_at":"2026-06-09T03:42:50Z","abstract_excerpt":"Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a rapidly expanding and heterogeneous body of scientific literature. As high-energy physics (HEP) increasingly explores agent-assisted analysis workflows, efficiently locating, integrating, and verifying scientific evidence becomes an essential capability. While retrieval-augmented generation (RAG) offers a promising framework for scientific question answering, integrating agentic reasoning without compromising retrieval precision remains a key chal"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10381","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/2606.10381/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":"2606.10381","created_at":"2026-06-10T01:10:14.949374+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.10381v1","created_at":"2026-06-10T01:10:14.949374+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10381","created_at":"2026-06-10T01:10:14.949374+00:00"},{"alias_kind":"pith_short_12","alias_value":"IUSIJHNPFRZ7","created_at":"2026-06-10T01:10:14.949374+00:00"},{"alias_kind":"pith_short_16","alias_value":"IUSIJHNPFRZ7QJTO","created_at":"2026-06-10T01:10:14.949374+00:00"},{"alias_kind":"pith_short_8","alias_value":"IUSIJHNP","created_at":"2026-06-10T01:10:14.949374+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/IUSIJHNPFRZ7QJTOWX3QM2E4JQ","json":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ.json","graph_json":"https://pith.science/api/pith-number/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/graph.json","events_json":"https://pith.science/api/pith-number/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/events.json","paper":"https://pith.science/paper/IUSIJHNP"},"agent_actions":{"view_html":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ","download_json":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ.json","view_paper":"https://pith.science/paper/IUSIJHNP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.10381&json=true","fetch_graph":"https://pith.science/api/pith-number/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/graph.json","fetch_events":"https://pith.science/api/pith-number/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/action/storage_attestation","attest_author":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/action/author_attestation","sign_citation":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/action/citation_signature","submit_replication":"https://pith.science/pith/IUSIJHNPFRZ7QJTOWX3QM2E4JQ/action/replication_record"}},"created_at":"2026-06-10T01:10:14.949374+00:00","updated_at":"2026-06-10T01:10:14.949374+00:00"}