{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:M5TRXO7KATY2PX7NFY5S5IJ6GQ","short_pith_number":"pith:M5TRXO7K","canonical_record":{"source":{"id":"2403.13835","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-11T17:45:47Z","cross_cats_sorted":["cs.AI","cs.CL","cs.DB"],"title_canon_sha256":"57f5978e408e9899251d580e070e578a666761279215fc213c23b6b4ea66b14e","abstract_canon_sha256":"64bb28f5768c9d65087eac9c3a1fdd0b497ae1d98d2f53c92838f2a70a6513a4"},"schema_version":"1.0"},"canonical_sha256":"67671bbbea04f1a7dfed2e3b2ea13e343fe8616bc9d9812df4f12c3ab4503eb6","source":{"kind":"arxiv","id":"2403.13835","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13835","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13835v1","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13835","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_12","alias_value":"M5TRXO7KATY2","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_16","alias_value":"M5TRXO7KATY2PX7N","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_8","alias_value":"M5TRXO7K","created_at":"2026-07-05T07:58:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:M5TRXO7KATY2PX7NFY5S5IJ6GQ","target":"record","payload":{"canonical_record":{"source":{"id":"2403.13835","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-11T17:45:47Z","cross_cats_sorted":["cs.AI","cs.CL","cs.DB"],"title_canon_sha256":"57f5978e408e9899251d580e070e578a666761279215fc213c23b6b4ea66b14e","abstract_canon_sha256":"64bb28f5768c9d65087eac9c3a1fdd0b497ae1d98d2f53c92838f2a70a6513a4"},"schema_version":"1.0"},"canonical_sha256":"67671bbbea04f1a7dfed2e3b2ea13e343fe8616bc9d9812df4f12c3ab4503eb6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:58:50.715645Z","signature_b64":"/r348Xg+yFHclEDgBQuMHbJwfXCub/9Vaa9NyDsUioDokNqTDQcb9WpaBbBuUd93ZXACS3vrUomx/MDy1YZfCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"67671bbbea04f1a7dfed2e3b2ea13e343fe8616bc9d9812df4f12c3ab4503eb6","last_reissued_at":"2026-07-05T07:58:50.715158Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:58:50.715158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.13835","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":"2026-07-05T07:58:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DFDmNdNgRPRIb4sjhD7O80Klbm/H0wcEiTI/ptf81CI7z5IWsIYMfhLZXt8VBOoPFdQQPJEYNM77xtJ8l8lwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T05:57:57.944919Z"},"content_sha256":"e1c2e300fc7fed85ac8b1f160e84c2de52eacb839c5ccf875efdae9fc3638716","schema_version":"1.0","event_id":"sha256:e1c2e300fc7fed85ac8b1f160e84c2de52eacb839c5ccf875efdae9fc3638716"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:M5TRXO7KATY2PX7NFY5S5IJ6GQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SMART: Automatically Scaling Down Language Models with Accuracy Guarantees for Reduced Processing Fees","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.DB"],"primary_cat":"cs.LG","authors_text":"Immanuel Trummer, Saehan Jo","submitted_at":"2024-03-11T17:45:47Z","abstract_excerpt":"The advancement of Large Language Models (LLMs) has significantly boosted performance in natural language processing (NLP) tasks. However, the deployment of high-performance LLMs incurs substantial costs, primarily due to the increased number of parameters aimed at enhancing model performance. This has made the use of state-of-the-art LLMs more expensive for end-users. AI service providers, such as OpenAI and Anthropic, often offer multiple versions of LLMs with varying prices and performance. However, end-users still face challenges in choosing the appropriate LLM for their tasks that balance"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13835","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/2403.13835/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":"2026-07-05T07:58:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QlajLxJ80RAvQthKVPWWpPcXzdZDBGZI794kNyGpnXRWktTV8gFfmXUH+paC7hKqBXOPiRnhfCl30nNuzlr4DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T05:57:57.945499Z"},"content_sha256":"59e6294cfcbadb81d6161416eeec39c83738bcd3e676f94eea9058992daac36c","schema_version":"1.0","event_id":"sha256:59e6294cfcbadb81d6161416eeec39c83738bcd3e676f94eea9058992daac36c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/bundle.json","state_url":"https://pith.science/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/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":"2026-08-06T05:57:57Z","links":{"resolver":"https://pith.science/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ","bundle":"https://pith.science/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/bundle.json","state":"https://pith.science/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M5TRXO7KATY2PX7NFY5S5IJ6GQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:M5TRXO7KATY2PX7NFY5S5IJ6GQ","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":"64bb28f5768c9d65087eac9c3a1fdd0b497ae1d98d2f53c92838f2a70a6513a4","cross_cats_sorted":["cs.AI","cs.CL","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-11T17:45:47Z","title_canon_sha256":"57f5978e408e9899251d580e070e578a666761279215fc213c23b6b4ea66b14e"},"schema_version":"1.0","source":{"id":"2403.13835","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13835","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13835v1","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13835","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_12","alias_value":"M5TRXO7KATY2","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_16","alias_value":"M5TRXO7KATY2PX7N","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_8","alias_value":"M5TRXO7K","created_at":"2026-07-05T07:58:50Z"}],"graph_snapshots":[{"event_id":"sha256:59e6294cfcbadb81d6161416eeec39c83738bcd3e676f94eea9058992daac36c","target":"graph","created_at":"2026-07-05T07:58:50Z","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/2403.13835/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The advancement of Large Language Models (LLMs) has significantly boosted performance in natural language processing (NLP) tasks. However, the deployment of high-performance LLMs incurs substantial costs, primarily due to the increased number of parameters aimed at enhancing model performance. This has made the use of state-of-the-art LLMs more expensive for end-users. AI service providers, such as OpenAI and Anthropic, often offer multiple versions of LLMs with varying prices and performance. However, end-users still face challenges in choosing the appropriate LLM for their tasks that balance","authors_text":"Immanuel Trummer, Saehan Jo","cross_cats":["cs.AI","cs.CL","cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-11T17:45:47Z","title":"SMART: Automatically Scaling Down Language Models with Accuracy Guarantees for Reduced Processing Fees"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13835","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:e1c2e300fc7fed85ac8b1f160e84c2de52eacb839c5ccf875efdae9fc3638716","target":"record","created_at":"2026-07-05T07:58:50Z","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":"64bb28f5768c9d65087eac9c3a1fdd0b497ae1d98d2f53c92838f2a70a6513a4","cross_cats_sorted":["cs.AI","cs.CL","cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-11T17:45:47Z","title_canon_sha256":"57f5978e408e9899251d580e070e578a666761279215fc213c23b6b4ea66b14e"},"schema_version":"1.0","source":{"id":"2403.13835","kind":"arxiv","version":1}},"canonical_sha256":"67671bbbea04f1a7dfed2e3b2ea13e343fe8616bc9d9812df4f12c3ab4503eb6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"67671bbbea04f1a7dfed2e3b2ea13e343fe8616bc9d9812df4f12c3ab4503eb6","first_computed_at":"2026-07-05T07:58:50.715158Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:58:50.715158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/r348Xg+yFHclEDgBQuMHbJwfXCub/9Vaa9NyDsUioDokNqTDQcb9WpaBbBuUd93ZXACS3vrUomx/MDy1YZfCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:58:50.715645Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.13835","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e1c2e300fc7fed85ac8b1f160e84c2de52eacb839c5ccf875efdae9fc3638716","sha256:59e6294cfcbadb81d6161416eeec39c83738bcd3e676f94eea9058992daac36c"],"state_sha256":"5adf35ebf561f485ae9fb4bb9f406f011657a38bf0dfca43805075cb55b03ff8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aA5QSUYZnYnKrhx+rjBcmQHfmeNSDU9UN2tpuPVxRtPjT2bfqZSJ/4p/JBgOLNg2jiMbVwnF2bCc8oK/TqAaCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T05:57:57.949162Z","bundle_sha256":"30ab27d45e456aaf931bab94c3c7696eaf08a3b04428eb18f17a53a4ba744e38"}}