{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:BXDYMAY5W2O5HATAA4Q5NORL5J","short_pith_number":"pith:BXDYMAY5","schema_version":"1.0","canonical_sha256":"0dc786031db69dd382600721d6ba2bea7370a4b6aeef383b976be712c148687c","source":{"kind":"arxiv","id":"2603.11333","version":2},"attestation_state":"computed","paper":{"title":"LLM-Augmented Digital Twin for Policy Evaluation in Short-Video Platforms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Denglin Jiang, Haoting Zhang, Jinghai He, Yunduan Lin, Zeyu Zheng, Zuo-Jun Shen","submitted_at":"2026-03-11T21:50:21Z","abstract_excerpt":"Short-video platforms are closed-loop, human-in-the-loop ecosystems where platform policy, creator incentives, and user behavior co-evolve. This feedback structure makes counterfactual policy evaluation difficult in production, especially for long-horizon and distributional outcomes. The challenge is amplified as platforms deploy AI tools that change what content enters the system, how agents adapt, and how the platform operates. We propose a large language model (LLM)-augmented digital twin for short-video platforms, with a modular four-twin architecture (User, Content, Interaction, Platform)"},"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":"2603.11333","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-03-11T21:50:21Z","cross_cats_sorted":[],"title_canon_sha256":"0e290e08b794408fb6ff7d8b6271cbbb0a9cc768261d0880355834afca00dc10","abstract_canon_sha256":"ac023d6ccf57d027fcbdffc1d5c8708c7f1a7a4d323eae9502aba6c689417d29"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-08T01:04:00.536695Z","signature_b64":"F1mn+Fxr20P5Yd/ZKH+IzGo5od0Sndx1WoIJGe+plsxuWlgb+zcukYgQXttUbfE3z7ctRYGy8+qhheM2mIPhBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0dc786031db69dd382600721d6ba2bea7370a4b6aeef383b976be712c148687c","last_reissued_at":"2026-06-08T01:04:00.535517Z","signature_status":"signed_v1","first_computed_at":"2026-06-08T01:04:00.535517Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LLM-Augmented Digital Twin for Policy Evaluation in Short-Video Platforms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Denglin Jiang, Haoting Zhang, Jinghai He, Yunduan Lin, Zeyu Zheng, Zuo-Jun Shen","submitted_at":"2026-03-11T21:50:21Z","abstract_excerpt":"Short-video platforms are closed-loop, human-in-the-loop ecosystems where platform policy, creator incentives, and user behavior co-evolve. This feedback structure makes counterfactual policy evaluation difficult in production, especially for long-horizon and distributional outcomes. The challenge is amplified as platforms deploy AI tools that change what content enters the system, how agents adapt, and how the platform operates. We propose a large language model (LLM)-augmented digital twin for short-video platforms, with a modular four-twin architecture (User, Content, Interaction, Platform)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.11333","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/2603.11333/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":"2603.11333","created_at":"2026-06-08T01:04:00.535681+00:00"},{"alias_kind":"arxiv_version","alias_value":"2603.11333v2","created_at":"2026-06-08T01:04:00.535681+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.11333","created_at":"2026-06-08T01:04:00.535681+00:00"},{"alias_kind":"pith_short_12","alias_value":"BXDYMAY5W2O5","created_at":"2026-06-08T01:04:00.535681+00:00"},{"alias_kind":"pith_short_16","alias_value":"BXDYMAY5W2O5HATA","created_at":"2026-06-08T01:04:00.535681+00:00"},{"alias_kind":"pith_short_8","alias_value":"BXDYMAY5","created_at":"2026-06-08T01:04:00.535681+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/BXDYMAY5W2O5HATAA4Q5NORL5J","json":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J.json","graph_json":"https://pith.science/api/pith-number/BXDYMAY5W2O5HATAA4Q5NORL5J/graph.json","events_json":"https://pith.science/api/pith-number/BXDYMAY5W2O5HATAA4Q5NORL5J/events.json","paper":"https://pith.science/paper/BXDYMAY5"},"agent_actions":{"view_html":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J","download_json":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J.json","view_paper":"https://pith.science/paper/BXDYMAY5","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2603.11333&json=true","fetch_graph":"https://pith.science/api/pith-number/BXDYMAY5W2O5HATAA4Q5NORL5J/graph.json","fetch_events":"https://pith.science/api/pith-number/BXDYMAY5W2O5HATAA4Q5NORL5J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J/action/storage_attestation","attest_author":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J/action/author_attestation","sign_citation":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J/action/citation_signature","submit_replication":"https://pith.science/pith/BXDYMAY5W2O5HATAA4Q5NORL5J/action/replication_record"}},"created_at":"2026-06-08T01:04:00.535681+00:00","updated_at":"2026-06-08T01:04:00.535681+00:00"}