{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UVTIJ6BCB3WPBBV44NHJHA5J2Z","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":"ec3ea5b05f4da79019795c4cb781dfe6e7fd16b8dba84f66e6f494ab98e247d1","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-13T06:08:01Z","title_canon_sha256":"1597762ca6b304137279c51a256f2c578d43270367a7f17c2f5c7c18295f3538"},"schema_version":"1.0","source":{"id":"2502.08991","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.08991","created_at":"2026-07-05T11:18:17Z"},{"alias_kind":"arxiv_version","alias_value":"2502.08991v2","created_at":"2026-07-05T11:18:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.08991","created_at":"2026-07-05T11:18:17Z"},{"alias_kind":"pith_short_12","alias_value":"UVTIJ6BCB3WP","created_at":"2026-07-05T11:18:17Z"},{"alias_kind":"pith_short_16","alias_value":"UVTIJ6BCB3WPBBV4","created_at":"2026-07-05T11:18:17Z"},{"alias_kind":"pith_short_8","alias_value":"UVTIJ6BC","created_at":"2026-07-05T11:18:17Z"}],"graph_snapshots":[{"event_id":"sha256:1bf424658340c22f79dab595ffdc7947c0199ea7da2d2fcdb56a09dd62237610","target":"graph","created_at":"2026-07-05T11:18:17Z","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/2502.08991/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) exhibit remarkable task generalization, solving tasks they were never explicitly trained on with only a few demonstrations. This raises a fundamental question: When can learning from a small set of tasks generalize to a large task family? In this paper, we investigate task generalization through the lens of autoregressive compositional structure, where each task is a composition of $T$ operations, and each operation is among a finite family of $D$ subtasks. This yields a total class of size $D^T$. We first show that generalization to all $D^T$ tasks is theoreticall","authors_text":"Amirhesam Abedsoltan, Hongzhou Lin, Huaqing Zhang, Jingzhao Zhang, Kaiyue Wen, Mikhail Belkin","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-13T06:08:01Z","title":"Task Generalization With AutoRegressive Compositional Structure: Can Learning From $D$ Tasks Generalize to $D^{T}$ Tasks?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.08991","kind":"arxiv","version":2},"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":"sha256:24de50a2adb02606101e2945ec5dcd0faf8caf5ee85e5f1265d3ed2e8b81656a","target":"record","created_at":"2026-07-05T11:18:17Z","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":"ec3ea5b05f4da79019795c4cb781dfe6e7fd16b8dba84f66e6f494ab98e247d1","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-13T06:08:01Z","title_canon_sha256":"1597762ca6b304137279c51a256f2c578d43270367a7f17c2f5c7c18295f3538"},"schema_version":"1.0","source":{"id":"2502.08991","kind":"arxiv","version":2}},"canonical_sha256":"a56684f8220eecf086bce34e9383a9d6586f8aae18b2231349bd758ac227ac1c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a56684f8220eecf086bce34e9383a9d6586f8aae18b2231349bd758ac227ac1c","first_computed_at":"2026-07-05T11:18:17.954278Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:17.954278Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oveA4k2cDCtlliqyoNBKMJBa+kQOF9tKT8pb+GWeZVrcG3uhE/XuHwy9Z+v4q7fxNgTAkRpxLDsDqfJUtg2RDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:17.954778Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.08991","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:24de50a2adb02606101e2945ec5dcd0faf8caf5ee85e5f1265d3ed2e8b81656a","sha256:1bf424658340c22f79dab595ffdc7947c0199ea7da2d2fcdb56a09dd62237610"],"state_sha256":"a459a671b61736d6a330b384f25ad77d6b8039f7ce9fde061c185943510f15f3"}