{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:PABGMUB6GKIHOBNLHM4B6POHSK","short_pith_number":"pith:PABGMUB6","schema_version":"1.0","canonical_sha256":"780266503e32907705ab3b381f3dc7929c9d05816d52df5c1dc30fea767cca50","source":{"kind":"arxiv","id":"2507.08796","version":1},"attestation_state":"computed","paper":{"title":"Filter Equivariant Functions: A symmetric account of length-general extrapolation on lists","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.PL","authors_text":"Andrew Dudzik, Christos Perivolaropoulos, Neil Ghani, Owen Lewis, Petar Veli\\v{c}kovi\\'c, Razvan Pascanu","submitted_at":"2025-07-11T17:57:16Z","abstract_excerpt":"What should a function that extrapolates beyond known input/output examples look like? This is a tricky question to answer in general, as any function matching the outputs on those examples can in principle be a correct extrapolant. We argue that a \"good\" extrapolant should follow certain kinds of rules, and here we study a particularly appealing criterion for rule-following in list functions: that the function should behave predictably even when certain elements are removed. In functional programming, a standard way to express such removal operations is by using a filter function. Accordingly"},"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":"2507.08796","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2025-07-11T17:57:16Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e12f25ff4617dde2078b2baa7328ef53f59f42222457de73cdce8c67cbf802b3","abstract_canon_sha256":"dfed450828a3b96dfa71e59656d3a4279c64759c29ec6542de68c2f1dd60d7d9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:35:46.520952Z","signature_b64":"DtnH1lXEGBgh4js19Ap2b1HTsrtwG0HUIklqxii/vcN9ufrVnryNtGnpdftxfqVmWcGSx4h6FZSmwprWCtz3CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"780266503e32907705ab3b381f3dc7929c9d05816d52df5c1dc30fea767cca50","last_reissued_at":"2026-07-05T11:35:46.520455Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:35:46.520455Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Filter Equivariant Functions: A symmetric account of length-general extrapolation on lists","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.PL","authors_text":"Andrew Dudzik, Christos Perivolaropoulos, Neil Ghani, Owen Lewis, Petar Veli\\v{c}kovi\\'c, Razvan Pascanu","submitted_at":"2025-07-11T17:57:16Z","abstract_excerpt":"What should a function that extrapolates beyond known input/output examples look like? This is a tricky question to answer in general, as any function matching the outputs on those examples can in principle be a correct extrapolant. We argue that a \"good\" extrapolant should follow certain kinds of rules, and here we study a particularly appealing criterion for rule-following in list functions: that the function should behave predictably even when certain elements are removed. In functional programming, a standard way to express such removal operations is by using a filter function. Accordingly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.08796","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/2507.08796/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":"2507.08796","created_at":"2026-07-05T11:35:46.520525+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.08796v1","created_at":"2026-07-05T11:35:46.520525+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.08796","created_at":"2026-07-05T11:35:46.520525+00:00"},{"alias_kind":"pith_short_12","alias_value":"PABGMUB6GKIH","created_at":"2026-07-05T11:35:46.520525+00:00"},{"alias_kind":"pith_short_16","alias_value":"PABGMUB6GKIHOBNL","created_at":"2026-07-05T11:35:46.520525+00:00"},{"alias_kind":"pith_short_8","alias_value":"PABGMUB6","created_at":"2026-07-05T11:35:46.520525+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/PABGMUB6GKIHOBNLHM4B6POHSK","json":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK.json","graph_json":"https://pith.science/api/pith-number/PABGMUB6GKIHOBNLHM4B6POHSK/graph.json","events_json":"https://pith.science/api/pith-number/PABGMUB6GKIHOBNLHM4B6POHSK/events.json","paper":"https://pith.science/paper/PABGMUB6"},"agent_actions":{"view_html":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK","download_json":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK.json","view_paper":"https://pith.science/paper/PABGMUB6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.08796&json=true","fetch_graph":"https://pith.science/api/pith-number/PABGMUB6GKIHOBNLHM4B6POHSK/graph.json","fetch_events":"https://pith.science/api/pith-number/PABGMUB6GKIHOBNLHM4B6POHSK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK/action/storage_attestation","attest_author":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK/action/author_attestation","sign_citation":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK/action/citation_signature","submit_replication":"https://pith.science/pith/PABGMUB6GKIHOBNLHM4B6POHSK/action/replication_record"}},"created_at":"2026-07-05T11:35:46.520525+00:00","updated_at":"2026-07-05T11:35:46.520525+00:00"}