{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YN37UFVISQLXYGNTVVIXS6PGOO","short_pith_number":"pith:YN37UFVI","canonical_record":{"source":{"id":"2404.10136","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T21:02:48Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"793f4e08b5050041b5b9233c79d619c10d4ff3b1d8170f50033b41bb72dcab30","abstract_canon_sha256":"a75d6fc00ba08b3f8afc14e2b07868e7bcfbdb23eb6c60d88e817300687eedbb"},"schema_version":"1.0"},"canonical_sha256":"c377fa16a894177c19b3ad517979e67394ef670bcc09f940625dd852e19e2a44","source":{"kind":"arxiv","id":"2404.10136","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.10136","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"2404.10136v1","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.10136","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"YN37UFVISQLX","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_16","alias_value":"YN37UFVISQLXYGNT","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_8","alias_value":"YN37UFVI","created_at":"2026-07-05T08:08:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YN37UFVISQLXYGNTVVIXS6PGOO","target":"record","payload":{"canonical_record":{"source":{"id":"2404.10136","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T21:02:48Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"793f4e08b5050041b5b9233c79d619c10d4ff3b1d8170f50033b41bb72dcab30","abstract_canon_sha256":"a75d6fc00ba08b3f8afc14e2b07868e7bcfbdb23eb6c60d88e817300687eedbb"},"schema_version":"1.0"},"canonical_sha256":"c377fa16a894177c19b3ad517979e67394ef670bcc09f940625dd852e19e2a44","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:25.913835Z","signature_b64":"mKAMumKR63LguZhZ8pz695JSj2p5FtUblOMu4VUaSGYoLFPFrhGykwfDd/5nVVyRZO8bllP6AQ7PZBxCkwtaAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c377fa16a894177c19b3ad517979e67394ef670bcc09f940625dd852e19e2a44","last_reissued_at":"2026-07-05T08:08:25.910891Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:25.910891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.10136","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KGZ/taCuQiu+bThgQziPZHr8M41gqD8StiTZImXvApzLa7vJjutLHjFMpDvuu6jazoFiFbYzlP6kAb8u3d1FDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:57:32.449776Z"},"content_sha256":"ae22a84d0b12c29adec9c32af36100b4fe83c0dfddc98959a906e5df7e10e78e","schema_version":"1.0","event_id":"sha256:ae22a84d0b12c29adec9c32af36100b4fe83c0dfddc98959a906e5df7e10e78e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YN37UFVISQLXYGNTVVIXS6PGOO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Language Model Cascades: Token-level uncertainty and beyond","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Aditya Krishna Menon, Ankit Singh Rawat, Harikrishna Narasimhan, Neha Gupta, Sanjiv Kumar, Wittawat Jitkrittum","submitted_at":"2024-04-15T21:02:48Z","abstract_excerpt":"Recent advances in language models (LMs) have led to significant improvements in quality on complex NLP tasks, but at the expense of increased inference costs. Cascading offers a simple strategy to achieve more favorable cost-quality tradeoffs: here, a small model is invoked for most \"easy\" instances, while a few \"hard\" instances are deferred to the large model. While the principles underpinning cascading are well-studied for classification tasks - with deferral based on predicted class uncertainty favored theoretically and practically - a similar understanding is lacking for generative LM tas"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.10136","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/2404.10136/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+MaclGVyu5EszcoIQnq18sz5i1RpwacPMamVebOC1bmdF24VdZbcxrLLhkxrpM53G8m+z704S3Hop8l2ivNjAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T03:57:32.450330Z"},"content_sha256":"8a2b8e38fa8747c87e48b7ded2300f214eeb67855c17441908f3ec62fbce815e","schema_version":"1.0","event_id":"sha256:8a2b8e38fa8747c87e48b7ded2300f214eeb67855c17441908f3ec62fbce815e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YN37UFVISQLXYGNTVVIXS6PGOO/bundle.json","state_url":"https://pith.science/pith/YN37UFVISQLXYGNTVVIXS6PGOO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YN37UFVISQLXYGNTVVIXS6PGOO/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T03:57:32Z","links":{"resolver":"https://pith.science/pith/YN37UFVISQLXYGNTVVIXS6PGOO","bundle":"https://pith.science/pith/YN37UFVISQLXYGNTVVIXS6PGOO/bundle.json","state":"https://pith.science/pith/YN37UFVISQLXYGNTVVIXS6PGOO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YN37UFVISQLXYGNTVVIXS6PGOO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YN37UFVISQLXYGNTVVIXS6PGOO","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":"a75d6fc00ba08b3f8afc14e2b07868e7bcfbdb23eb6c60d88e817300687eedbb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T21:02:48Z","title_canon_sha256":"793f4e08b5050041b5b9233c79d619c10d4ff3b1d8170f50033b41bb72dcab30"},"schema_version":"1.0","source":{"id":"2404.10136","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.10136","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"2404.10136v1","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.10136","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"YN37UFVISQLX","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_16","alias_value":"YN37UFVISQLXYGNT","created_at":"2026-07-05T08:08:25Z"},{"alias_kind":"pith_short_8","alias_value":"YN37UFVI","created_at":"2026-07-05T08:08:25Z"}],"graph_snapshots":[{"event_id":"sha256:8a2b8e38fa8747c87e48b7ded2300f214eeb67855c17441908f3ec62fbce815e","target":"graph","created_at":"2026-07-05T08:08:25Z","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/2404.10136/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in language models (LMs) have led to significant improvements in quality on complex NLP tasks, but at the expense of increased inference costs. Cascading offers a simple strategy to achieve more favorable cost-quality tradeoffs: here, a small model is invoked for most \"easy\" instances, while a few \"hard\" instances are deferred to the large model. While the principles underpinning cascading are well-studied for classification tasks - with deferral based on predicted class uncertainty favored theoretically and practically - a similar understanding is lacking for generative LM tas","authors_text":"Aditya Krishna Menon, Ankit Singh Rawat, Harikrishna Narasimhan, Neha Gupta, Sanjiv Kumar, Wittawat Jitkrittum","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T21:02:48Z","title":"Language Model Cascades: Token-level uncertainty and beyond"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.10136","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:ae22a84d0b12c29adec9c32af36100b4fe83c0dfddc98959a906e5df7e10e78e","target":"record","created_at":"2026-07-05T08:08:25Z","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":"a75d6fc00ba08b3f8afc14e2b07868e7bcfbdb23eb6c60d88e817300687eedbb","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-04-15T21:02:48Z","title_canon_sha256":"793f4e08b5050041b5b9233c79d619c10d4ff3b1d8170f50033b41bb72dcab30"},"schema_version":"1.0","source":{"id":"2404.10136","kind":"arxiv","version":1}},"canonical_sha256":"c377fa16a894177c19b3ad517979e67394ef670bcc09f940625dd852e19e2a44","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c377fa16a894177c19b3ad517979e67394ef670bcc09f940625dd852e19e2a44","first_computed_at":"2026-07-05T08:08:25.910891Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:25.910891Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mKAMumKR63LguZhZ8pz695JSj2p5FtUblOMu4VUaSGYoLFPFrhGykwfDd/5nVVyRZO8bllP6AQ7PZBxCkwtaAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:25.913835Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.10136","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae22a84d0b12c29adec9c32af36100b4fe83c0dfddc98959a906e5df7e10e78e","sha256:8a2b8e38fa8747c87e48b7ded2300f214eeb67855c17441908f3ec62fbce815e"],"state_sha256":"d8c6956abfbf29d622a516fad35d6aac653c721e259c22f27ee870cba1837b7c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aFw4TnP3gxnvwgzCKf9xg3Gy+zsf8sbS0aP2fc5OQbgVBzUh9v5z11bBfFLSKk0GbEdTHhYHSgdHN0hQDyfVAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T03:57:32.453603Z","bundle_sha256":"952000b84693548660cb71cad7ef342625995047109834c7c79288eca487b337"}}