{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VL2QNC4P7S5YMTUFPPUKMXBCUD","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":"6cce5099589b9e25c06ea5008773109d53739fd8149b31eacc4bdba19e13f5c1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-04-29T09:05:47Z","title_canon_sha256":"f06af4516813b4c43a27e93a7693d742e3ac5722947cb3f7cee31a25867eb0b2"},"schema_version":"1.0","source":{"id":"2505.02844","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.02844","created_at":"2026-07-05T10:58:48Z"},{"alias_kind":"arxiv_version","alias_value":"2505.02844v1","created_at":"2026-07-05T10:58:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.02844","created_at":"2026-07-05T10:58:48Z"},{"alias_kind":"pith_short_12","alias_value":"VL2QNC4P7S5Y","created_at":"2026-07-05T10:58:48Z"},{"alias_kind":"pith_short_16","alias_value":"VL2QNC4P7S5YMTUF","created_at":"2026-07-05T10:58:48Z"},{"alias_kind":"pith_short_8","alias_value":"VL2QNC4P","created_at":"2026-07-05T10:58:48Z"}],"graph_snapshots":[{"event_id":"sha256:f4dc2a093c39d243177f0840deac933206f21fd08cbad7fc8eacc6a6356a38e0","target":"graph","created_at":"2026-07-05T10:58:48Z","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/2505.02844/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Click-through Rate (CTR) prediction in real-world recommender systems often deals with billions of user interactions every day. To improve the training efficiency, it is common to update the CTR prediction model incrementally using the new incremental data and a subset of historical data. However, the feature embeddings of a CTR prediction model often get stale when the corresponding features do not appear in current incremental data. In the next period, the model would have a performance degradation on samples containing stale features, which we call the feature staleness problem. To mitigate","authors_text":"Kangyi Lin, Yanyan Shen, Zhikai Wang, Zibin Zhang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-04-29T09:05:47Z","title":"Feature Staleness Aware Incremental Learning for CTR Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.02844","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":"sha256:8edfd7a730083ef822bb1b64decd0ac0604dba251ab43b25068d43cf9afecd5b","target":"record","created_at":"2026-07-05T10:58:48Z","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":"6cce5099589b9e25c06ea5008773109d53739fd8149b31eacc4bdba19e13f5c1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2025-04-29T09:05:47Z","title_canon_sha256":"f06af4516813b4c43a27e93a7693d742e3ac5722947cb3f7cee31a25867eb0b2"},"schema_version":"1.0","source":{"id":"2505.02844","kind":"arxiv","version":1}},"canonical_sha256":"aaf5068b8ffcbb864e857be8a65c22a0e4306289e38aa66092f0a14b216a5865","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aaf5068b8ffcbb864e857be8a65c22a0e4306289e38aa66092f0a14b216a5865","first_computed_at":"2026-07-05T10:58:48.045772Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:58:48.045772Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Av5/moj2riv2w5drLD7LzDLUDYY6SggZjZp8QFUQH9OysSRY5T8xLJejsxxvVBs91SsYdZS1ORu8qc2RuSJJAw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:58:48.046242Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.02844","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8edfd7a730083ef822bb1b64decd0ac0604dba251ab43b25068d43cf9afecd5b","sha256:f4dc2a093c39d243177f0840deac933206f21fd08cbad7fc8eacc6a6356a38e0"],"state_sha256":"00d1ff02a422760ac661cb8dd04f989ae8fb60d2ba83b16e2bcee210939cce17"}