{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:YWJIXG7RNRTO6VWKWAJPTE6MM6","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":"c8b19f2c4e92431030ebf52628f11df959d643468bded08c365fd13798958910","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-08T00:36:33Z","title_canon_sha256":"8f502227261cbf7752ec205ac46ec5bba0cc63be707bdaef860920444a931fd8"},"schema_version":"1.0","source":{"id":"2010.03706","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.03706","created_at":"2026-07-05T02:47:01Z"},{"alias_kind":"arxiv_version","alias_value":"2010.03706v6","created_at":"2026-07-05T02:47:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.03706","created_at":"2026-07-05T02:47:01Z"},{"alias_kind":"pith_short_12","alias_value":"YWJIXG7RNRTO","created_at":"2026-07-05T02:47:01Z"},{"alias_kind":"pith_short_16","alias_value":"YWJIXG7RNRTO6VWK","created_at":"2026-07-05T02:47:01Z"},{"alias_kind":"pith_short_8","alias_value":"YWJIXG7R","created_at":"2026-07-05T02:47:01Z"}],"graph_snapshots":[{"event_id":"sha256:ff83c16f99c21fa2dd71cdaf52709e3cd952584f2acb2cd0aa2ef2e24a763289","target":"graph","created_at":"2026-07-05T02:47:01Z","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/2010.03706/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Flexible neural sequence models outperform grammar- and automaton-based counterparts on a variety of tasks. However, neural models perform poorly in settings requiring compositional generalization beyond the training data -- particularly to rare or unseen subsequences. Past work has found symbolic scaffolding (e.g. grammars or automata) essential in these settings. We describe R&R, a learned data augmentation scheme that enables a large category of compositional generalizations without appeal to latent symbolic structure. R&R has two components: recombination of original training examples via ","authors_text":"Afra Feyza Aky\\\"urek, Ekin Aky\\\"urek, Jacob Andreas","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-08T00:36:33Z","title":"Learning to Recombine and Resample Data for Compositional Generalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.03706","kind":"arxiv","version":6},"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:c3e729687efb1d53ea6fef4d5e58c9001df3bdb23b08aa2d7820e12bb0e0d18f","target":"record","created_at":"2026-07-05T02:47:01Z","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":"c8b19f2c4e92431030ebf52628f11df959d643468bded08c365fd13798958910","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-08T00:36:33Z","title_canon_sha256":"8f502227261cbf7752ec205ac46ec5bba0cc63be707bdaef860920444a931fd8"},"schema_version":"1.0","source":{"id":"2010.03706","kind":"arxiv","version":6}},"canonical_sha256":"c5928b9bf16c66ef56cab012f993cc67a8aa431cc7cb85dfb68f846eb48f4f80","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c5928b9bf16c66ef56cab012f993cc67a8aa431cc7cb85dfb68f846eb48f4f80","first_computed_at":"2026-07-05T02:47:01.613255Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:47:01.613255Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4j1juoc8HZG/uxdnRpYlXgDBefqHp2KZtALGRn7JjtyrKYlMh49xpG/FkFKXFiQ0IvhqUInDTVv5jqWT5ZcBCw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:47:01.613665Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.03706","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c3e729687efb1d53ea6fef4d5e58c9001df3bdb23b08aa2d7820e12bb0e0d18f","sha256:ff83c16f99c21fa2dd71cdaf52709e3cd952584f2acb2cd0aa2ef2e24a763289"],"state_sha256":"347f18eb972144cb2e7a3ba0317470db8e77a4b1b0d39c9b472f6a8772d22173"}