{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PSHTPY52PXVIIYEGNDAN3M7QPK","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":"f3ca8c4284260c651f5c522fc46de4233f042161470827e155fbc05d803ed741","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T21:34:56Z","title_canon_sha256":"eb4a9b6850d289872aaf88e9a2ca3de3604372d65bac42c806a9b0537b9511e8"},"schema_version":"1.0","source":{"id":"2402.13388","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.13388","created_at":"2026-07-05T07:54:54Z"},{"alias_kind":"arxiv_version","alias_value":"2402.13388v3","created_at":"2026-07-05T07:54:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.13388","created_at":"2026-07-05T07:54:54Z"},{"alias_kind":"pith_short_12","alias_value":"PSHTPY52PXVI","created_at":"2026-07-05T07:54:54Z"},{"alias_kind":"pith_short_16","alias_value":"PSHTPY52PXVIIYEG","created_at":"2026-07-05T07:54:54Z"},{"alias_kind":"pith_short_8","alias_value":"PSHTPY52","created_at":"2026-07-05T07:54:54Z"}],"graph_snapshots":[{"event_id":"sha256:7ca61d8be92f9736c7c4a697c38b7f6d9e6f6be869729e80f5218bc31f37f9be","target":"graph","created_at":"2026-07-05T07:54:54Z","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/2402.13388/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This micro-paper describes a trick to speed up inference of transformers with RoPE (such as LLaMA, Mistral, PaLM, and Gemma). For these models, a large portion of the first transformer layer can be precomputed, which results in slightly lower latency and lower cost-per-token. Because this trick optimizes only one layer, the relative savings depend on the total number of layers. For example, the maximum savings for a model with only 4 layers (such as Whisper tiny) is limited to 25%, while a 32-layer model is limited to 3% savings. See https://github.com/OpenMachine-ai/transformer-tricks for cod","authors_text":"Nils Graef","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T21:34:56Z","title":"Transformer tricks: Precomputing the first layer"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.13388","kind":"arxiv","version":3},"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":"sha256:15ab13c86a336b2925f917a4eaa166b87268ffa2a04c451513697e3390afc0dc","target":"record","created_at":"2026-07-05T07:54:54Z","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":"f3ca8c4284260c651f5c522fc46de4233f042161470827e155fbc05d803ed741","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-20T21:34:56Z","title_canon_sha256":"eb4a9b6850d289872aaf88e9a2ca3de3604372d65bac42c806a9b0537b9511e8"},"schema_version":"1.0","source":{"id":"2402.13388","kind":"arxiv","version":3}},"canonical_sha256":"7c8f37e3ba7dea84608668c0ddb3f07a8120cf832c35d8a77c07e4c53f2ca9b0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c8f37e3ba7dea84608668c0ddb3f07a8120cf832c35d8a77c07e4c53f2ca9b0","first_computed_at":"2026-07-05T07:54:54.999850Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:54:54.999850Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GOavLJ//hsmqnHoXhgvpHukh2g85Q172DyPfwSE2Ts44WJI5hgUsTMKEq9N5VUqiiQ9R6deVZbJYvpJz7jeZDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:54:55.000257Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.13388","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:15ab13c86a336b2925f917a4eaa166b87268ffa2a04c451513697e3390afc0dc","sha256:7ca61d8be92f9736c7c4a697c38b7f6d9e6f6be869729e80f5218bc31f37f9be"],"state_sha256":"59b8d326f0b5a0e8ef6bcc3a34ebf17cb9ccf52d409bf4578902a3154b737247"}