{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:FHZ4TJMCU66WGOG6KMQG4736QN","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":"89e74d1e68e825c90b08036d056074e024ed9312b93c65d6de60cf0e4ac2e08e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-06-29T08:44:11Z","title_canon_sha256":"82041b4830d6db92fbc0367c9f63db9125bcd212fc0159e75737bd6dae2bdf41"},"schema_version":"1.0","source":{"id":"2606.29966","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.29966","created_at":"2026-06-30T02:17:43Z"},{"alias_kind":"arxiv_version","alias_value":"2606.29966v1","created_at":"2026-06-30T02:17:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29966","created_at":"2026-06-30T02:17:43Z"},{"alias_kind":"pith_short_12","alias_value":"FHZ4TJMCU66W","created_at":"2026-06-30T02:17:43Z"},{"alias_kind":"pith_short_16","alias_value":"FHZ4TJMCU66WGOG6","created_at":"2026-06-30T02:17:43Z"},{"alias_kind":"pith_short_8","alias_value":"FHZ4TJMC","created_at":"2026-06-30T02:17:43Z"}],"graph_snapshots":[{"event_id":"sha256:e52ca8d4fe3c514f5002d9fc0ab18640255dd37796feff40f3a2bed87e36bd4d","target":"graph","created_at":"2026-06-30T02:17:43Z","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/2606.29966/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantum computing provides a powerful paradigm for representing and transforming high-dimensional information through superposition, entanglement, and measurement-induced nonlinear features. While current quantum hardware is not yet practical for direct large-scale vision-language model (VLM) inference, simulated quantum computation can be used during model construction to generate structured parameters for compact classical AI systems. We build RiverONE, a lightweight vision-language model for quantum calibration plot understanding, using simulated quantum computation. It employs a specialize","authors_text":"Monan Wang, Peng Yang, Teng Yu, Wen Qin, Xianghao Li, Xindian Ma, Xinyu Long, Yanchen Liu, Yefei Zhang, Yike Hu, Yikun Wang, Yuedong Zhu, Yufu Wen, Zeyang Ma","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-06-29T08:44:11Z","title":"RiverONE: Generating Knowledge-Intensive VLM by Simulated Quantum Machines"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29966","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":"sha256:270a50bdc5b6251b3a76483e90cd8275fbd1d8abf9e48f19ee0f38c254617c6c","target":"record","created_at":"2026-06-30T02:17:43Z","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":"89e74d1e68e825c90b08036d056074e024ed9312b93c65d6de60cf0e4ac2e08e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2026-06-29T08:44:11Z","title_canon_sha256":"82041b4830d6db92fbc0367c9f63db9125bcd212fc0159e75737bd6dae2bdf41"},"schema_version":"1.0","source":{"id":"2606.29966","kind":"arxiv","version":1}},"canonical_sha256":"29f3c9a582a7bd6338de53206e7f7e834fb1ed6f7c35727e6586a99e9a309296","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"29f3c9a582a7bd6338de53206e7f7e834fb1ed6f7c35727e6586a99e9a309296","first_computed_at":"2026-06-30T02:17:43.080961Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T02:17:43.080961Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mTBn0PADV9n6LLS8rwjDb33mUm2Q/f8ocSlpBOIb2EYeF1Ue+CeCRzOKwhLb4M/9p8EDkbpyvlGRAPSxeAVXBg==","signature_status":"signed_v1","signed_at":"2026-06-30T02:17:43.081502Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.29966","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:270a50bdc5b6251b3a76483e90cd8275fbd1d8abf9e48f19ee0f38c254617c6c","sha256:e52ca8d4fe3c514f5002d9fc0ab18640255dd37796feff40f3a2bed87e36bd4d"],"state_sha256":"1e5f57b313994b73bc14a5ff6442ce04e905c24d05addc2b58e0b6bdfa06a49b"}