{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:W7HRHUDFOXCKQGYOMEUIBBS2MB","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":"d42e2b5e2e0712636fa29ed19b717aa72d013221caf6a0ae794943f7dcc34e39","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-09-30T02:30:15Z","title_canon_sha256":"68ca7d76412b1510d49f6cfc84058a5ec8b444203116e661455a2ae714aef384"},"schema_version":"1.0","source":{"id":"2209.15189","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2209.15189","created_at":"2026-07-05T05:02:17Z"},{"alias_kind":"arxiv_version","alias_value":"2209.15189v1","created_at":"2026-07-05T05:02:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.15189","created_at":"2026-07-05T05:02:17Z"},{"alias_kind":"pith_short_12","alias_value":"W7HRHUDFOXCK","created_at":"2026-07-05T05:02:17Z"},{"alias_kind":"pith_short_16","alias_value":"W7HRHUDFOXCKQGYO","created_at":"2026-07-05T05:02:17Z"},{"alias_kind":"pith_short_8","alias_value":"W7HRHUDF","created_at":"2026-07-05T05:02:17Z"}],"graph_snapshots":[{"event_id":"sha256:8b204625edc03bdd2cd3785ce4cb587eae4502ee5a606799927d6df502440bfb","target":"graph","created_at":"2026-07-05T05:02:17Z","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/2209.15189/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Language models significantly benefit from context tokens, such as prompts or scratchpads. They perform better when prompted with informative instructions, and they acquire new reasoning capabilities by generating a scratch-pad before predicting the final answers. However, they do not \\textit{internalize} these performance gains, which disappear when the context tokens are gone. Our work proposes to apply context distillation so that a language model can improve itself by internalizing these gains. Concretely, given a synthetic unlabeled input for the target task, we condition the model on ``[","authors_text":"Charlie Snell, Dan Klein, Ruiqi Zhong","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-09-30T02:30:15Z","title":"Learning by Distilling Context"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.15189","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":"sha256:4d154d25d22eeb34f1cc9a9006a9b52fa35fd6db22698a1635b0b4c93e0f8a66","target":"record","created_at":"2026-07-05T05:02:17Z","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":"d42e2b5e2e0712636fa29ed19b717aa72d013221caf6a0ae794943f7dcc34e39","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-09-30T02:30:15Z","title_canon_sha256":"68ca7d76412b1510d49f6cfc84058a5ec8b444203116e661455a2ae714aef384"},"schema_version":"1.0","source":{"id":"2209.15189","kind":"arxiv","version":1}},"canonical_sha256":"b7cf13d06575c4a81b0e612880865a6075972f91d888b692ab7efde452109fed","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7cf13d06575c4a81b0e612880865a6075972f91d888b692ab7efde452109fed","first_computed_at":"2026-07-05T05:02:17.252719Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:02:17.252719Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Es7jAjdsxVt4o/M127q9gu3ZclQO8ipAL+S1cfiA1RVX85ym5pDDNIGGyUPYYMb8FzbA/Z2FM4pST3mS9ZUUDA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:02:17.253111Z","signed_message":"canonical_sha256_bytes"},"source_id":"2209.15189","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d154d25d22eeb34f1cc9a9006a9b52fa35fd6db22698a1635b0b4c93e0f8a66","sha256:8b204625edc03bdd2cd3785ce4cb587eae4502ee5a606799927d6df502440bfb"],"state_sha256":"37b497613e6e2d22c7cedb8822826d38bfecae0692d90443eccbe087854d3aac"}