{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:UVY2UT3EH27G2Y7VX6SEAVOY4V","short_pith_number":"pith:UVY2UT3E","schema_version":"1.0","canonical_sha256":"a571aa4f643ebe6d63f5bfa44055d8e5749f35f433a965e8c0dbfb4f9763e1aa","source":{"kind":"arxiv","id":"2607.28415","version":1},"attestation_state":"computed","paper":{"title":"QQWorld: Quantile-Quantile Matching for World Model Regularization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.MM","cs.RO"],"primary_cat":"cs.LG","authors_text":"Xiangyu Xu, Xiaoyu Hu, Zhoushun Yu","submitted_at":"2026-07-30T16:00:39Z","abstract_excerpt":"Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically on the quality of the learned latent distribution. LeWorldModel (LeWM) regularizes its latents toward an isotropic Gaussian using the Epps-Pulley (EP) objective. We show that the corrective gradients of EP rapidly vanish for isolated tail samples, leaving heavy-tailed deviations insufficiently controlled. To address this limitation, we propose QQWorld, which replaces EP with a quantile-quantile matching objective that directly aligns projected la"},"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":"2607.28415","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-30T16:00:39Z","cross_cats_sorted":["cs.AI","cs.CV","cs.MM","cs.RO"],"title_canon_sha256":"ef9bb1cc509fcaf8a3ab6ed5f9fb9b53eec553c361047e99c8ba81c71be4e5ea","abstract_canon_sha256":"c3c8bdd88843b634edf9d03058205dff7a2d21b8c6b12991e46b6ac5b7b144b8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a571aa4f643ebe6d63f5bfa44055d8e5749f35f433a965e8c0dbfb4f9763e1aa","last_reissued_at":"2026-07-31T01:37:34.361762Z","signature_status":"unsigned_v0","first_computed_at":"2026-07-31T01:37:34.361762Z"},"graph_snapshot":{"paper":{"title":"QQWorld: Quantile-Quantile Matching for World Model Regularization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.MM","cs.RO"],"primary_cat":"cs.LG","authors_text":"Xiangyu Xu, Xiaoyu Hu, Zhoushun Yu","submitted_at":"2026-07-30T16:00:39Z","abstract_excerpt":"Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically on the quality of the learned latent distribution. LeWorldModel (LeWM) regularizes its latents toward an isotropic Gaussian using the Epps-Pulley (EP) objective. We show that the corrective gradients of EP rapidly vanish for isolated tail samples, leaving heavy-tailed deviations insufficiently controlled. To address this limitation, we propose QQWorld, which replaces EP with a quantile-quantile matching objective that directly aligns projected la"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28415","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/2607.28415/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":"2607.28415","created_at":"2026-07-31T01:37:34.364886+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.28415v1","created_at":"2026-07-31T01:37:34.364886+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28415","created_at":"2026-07-31T01:37:34.364886+00:00"},{"alias_kind":"pith_short_12","alias_value":"UVY2UT3EH27G","created_at":"2026-07-31T01:37:34.364886+00:00"},{"alias_kind":"pith_short_16","alias_value":"UVY2UT3EH27G2Y7V","created_at":"2026-07-31T01:37:34.364886+00:00"},{"alias_kind":"pith_short_8","alias_value":"UVY2UT3E","created_at":"2026-07-31T01:37:34.364886+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/UVY2UT3EH27G2Y7VX6SEAVOY4V","json":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V.json","graph_json":"https://pith.science/api/pith-number/UVY2UT3EH27G2Y7VX6SEAVOY4V/graph.json","events_json":"https://pith.science/api/pith-number/UVY2UT3EH27G2Y7VX6SEAVOY4V/events.json","paper":"https://pith.science/paper/UVY2UT3E"},"agent_actions":{"view_html":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V","download_json":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V.json","view_paper":"https://pith.science/paper/UVY2UT3E","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.28415&json=true","fetch_graph":"https://pith.science/api/pith-number/UVY2UT3EH27G2Y7VX6SEAVOY4V/graph.json","fetch_events":"https://pith.science/api/pith-number/UVY2UT3EH27G2Y7VX6SEAVOY4V/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V/action/storage_attestation","attest_author":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V/action/author_attestation","sign_citation":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V/action/citation_signature","submit_replication":"https://pith.science/pith/UVY2UT3EH27G2Y7VX6SEAVOY4V/action/replication_record"}},"created_at":"2026-07-31T01:37:34.364886+00:00","updated_at":"2026-07-31T01:37:34.364886+00:00"}