{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:UWFKTFYMKIPKPCUR2UUT5P37OB","short_pith_number":"pith:UWFKTFYM","schema_version":"1.0","canonical_sha256":"a58aa9970c521ea78a91d5293ebf7f704bf51189d013d757f2c785079e85db56","source":{"kind":"arxiv","id":"2509.10486","version":1},"attestation_state":"computed","paper":{"title":"SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.MM"],"primary_cat":"cs.NI","authors_text":"Boon-Hee Soong, Bowen Zhang, Chau Yuen, Genke Yang, Pengcheng Luo, Yunyang Zhao","submitted_at":"2025-08-30T05:32:45Z","abstract_excerpt":"With the advent of 5G, the internet has entered a new video-centric era. From short-video platforms like TikTok to long-video platforms like Bilibili, online video services are reshaping user consumption habits. Adaptive Bitrate (ABR) control is widely recognized as a critical factor influencing Quality of Experience (QoE). Recent learning-based ABR methods have attracted increasing attention. However, most of them rely on limited network trace sets during training and overlook the wide-distribution characteristics of real-world network conditions, resulting in poor generalization in out-of-di"},"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":"2509.10486","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NI","submitted_at":"2025-08-30T05:32:45Z","cross_cats_sorted":["cs.AI","cs.LG","cs.MM"],"title_canon_sha256":"179ec03bbd867e50335fcf1f635f9cf8a30ce2c85b4574d76884d416e7ac114d","abstract_canon_sha256":"d7f74c5b7928c6fd392b1c3cf8657eb5084d6254c8da028827dcf5435460da40"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:11:21.724624Z","signature_b64":"9Ve8rzgXF8Yb2W8ourUBFPImyneZY6igy7iz3O46SX5T06a/QzHALdNbdWjrcp4El+R85Le50RPeFE57cCmJDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a58aa9970c521ea78a91d5293ebf7f704bf51189d013d757f2c785079e85db56","last_reissued_at":"2026-07-05T12:11:21.724107Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:11:21.724107Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SABR: A Stable Adaptive Bitrate Framework Using Behavior Cloning Pretraining and Reinforcement Learning Fine-Tuning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.MM"],"primary_cat":"cs.NI","authors_text":"Boon-Hee Soong, Bowen Zhang, Chau Yuen, Genke Yang, Pengcheng Luo, Yunyang Zhao","submitted_at":"2025-08-30T05:32:45Z","abstract_excerpt":"With the advent of 5G, the internet has entered a new video-centric era. From short-video platforms like TikTok to long-video platforms like Bilibili, online video services are reshaping user consumption habits. Adaptive Bitrate (ABR) control is widely recognized as a critical factor influencing Quality of Experience (QoE). Recent learning-based ABR methods have attracted increasing attention. However, most of them rely on limited network trace sets during training and overlook the wide-distribution characteristics of real-world network conditions, resulting in poor generalization in out-of-di"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.10486","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/2509.10486/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":"2509.10486","created_at":"2026-07-05T12:11:21.724174+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.10486v1","created_at":"2026-07-05T12:11:21.724174+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.10486","created_at":"2026-07-05T12:11:21.724174+00:00"},{"alias_kind":"pith_short_12","alias_value":"UWFKTFYMKIPK","created_at":"2026-07-05T12:11:21.724174+00:00"},{"alias_kind":"pith_short_16","alias_value":"UWFKTFYMKIPKPCUR","created_at":"2026-07-05T12:11:21.724174+00:00"},{"alias_kind":"pith_short_8","alias_value":"UWFKTFYM","created_at":"2026-07-05T12:11:21.724174+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.23560","citing_title":"SafeSABR: Risk-Calibrated Adaptive Bitrate Streaming over Starlink Networks","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2605.23560","citing_title":"SafeSABR: Risk-Calibrated Adaptive Bitrate Streaming over Starlink Networks","ref_index":18,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB","json":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB.json","graph_json":"https://pith.science/api/pith-number/UWFKTFYMKIPKPCUR2UUT5P37OB/graph.json","events_json":"https://pith.science/api/pith-number/UWFKTFYMKIPKPCUR2UUT5P37OB/events.json","paper":"https://pith.science/paper/UWFKTFYM"},"agent_actions":{"view_html":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB","download_json":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB.json","view_paper":"https://pith.science/paper/UWFKTFYM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.10486&json=true","fetch_graph":"https://pith.science/api/pith-number/UWFKTFYMKIPKPCUR2UUT5P37OB/graph.json","fetch_events":"https://pith.science/api/pith-number/UWFKTFYMKIPKPCUR2UUT5P37OB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB/action/storage_attestation","attest_author":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB/action/author_attestation","sign_citation":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB/action/citation_signature","submit_replication":"https://pith.science/pith/UWFKTFYMKIPKPCUR2UUT5P37OB/action/replication_record"}},"created_at":"2026-07-05T12:11:21.724174+00:00","updated_at":"2026-07-05T12:11:21.724174+00:00"}