{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:JCYAUQLKRKGC2FHQ7YG7CNVMYT","short_pith_number":"pith:JCYAUQLK","canonical_record":{"source":{"id":"2310.03262","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-05T02:35:00Z","cross_cats_sorted":[],"title_canon_sha256":"a1ba8859b9ba7591c9a22c1c7135d86fde1efec309d6f336fa47a0fa35f5cb09","abstract_canon_sha256":"5f3977e7c0c4133b3e3033cdf59add7774c14359dee9397b113d02aa44931b1b"},"schema_version":"1.0"},"canonical_sha256":"48b00a416a8a8c2d14f0fe0df136acc4e343cba58ad64fda50f16d28356a9f15","source":{"kind":"arxiv","id":"2310.03262","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03262","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03262v3","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03262","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_12","alias_value":"JCYAUQLKRKGC","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_16","alias_value":"JCYAUQLKRKGC2FHQ","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_8","alias_value":"JCYAUQLK","created_at":"2026-07-05T08:08:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:JCYAUQLKRKGC2FHQ7YG7CNVMYT","target":"record","payload":{"canonical_record":{"source":{"id":"2310.03262","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-05T02:35:00Z","cross_cats_sorted":[],"title_canon_sha256":"a1ba8859b9ba7591c9a22c1c7135d86fde1efec309d6f336fa47a0fa35f5cb09","abstract_canon_sha256":"5f3977e7c0c4133b3e3033cdf59add7774c14359dee9397b113d02aa44931b1b"},"schema_version":"1.0"},"canonical_sha256":"48b00a416a8a8c2d14f0fe0df136acc4e343cba58ad64fda50f16d28356a9f15","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:08:51.817006Z","signature_b64":"u0XKCcfR/8Mr5O79zycbvUnUV8kUS1s+PlcLSMMZpKl/TfvUL34RYXh0Zaz2WMD6EIzAKXltlmmJavXcHtH3Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48b00a416a8a8c2d14f0fe0df136acc4e343cba58ad64fda50f16d28356a9f15","last_reissued_at":"2026-07-05T08:08:51.816529Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:08:51.816529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.03262","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:08:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YpSMDkl1MVrJwNN/yzQVuxCloc5ebBkksRWgU+Sz15uW3Gql9oEzbb8Bw9MaCczGklFgRBLx7rKxgeCfh4zZDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:09:49.061305Z"},"content_sha256":"a79d7a119fc5d2b509080c4f1a57343b15cf36365ac2e5baafa3ac444e0389dd","schema_version":"1.0","event_id":"sha256:a79d7a119fc5d2b509080c4f1a57343b15cf36365ac2e5baafa3ac444e0389dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:JCYAUQLKRKGC2FHQ7YG7CNVMYT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Predicting Emergent Abilities with Infinite Resolution Evaluation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chaoqun He, Guoyang Zeng, Maosong Sun, Ning Ding, Shengding Hu, Weilin Zhao, Xin Liu, Xinrong Zhang, Xu Han, Yankai Lin, Zebin Ou, Zhiyuan Liu","submitted_at":"2023-10-05T02:35:00Z","abstract_excerpt":"The scientific scale-up of large language models (LLMs) necessitates a comprehensive understanding of their scaling properties. However, the existing literature on the scaling properties only yields an incomplete answer: optimization loss decreases predictably as the model size increases, in line with established scaling law; yet no scaling law for task has been established and the task performances are far from predictable during scaling. Task performances typically show minor gains on small models until they improve dramatically once models exceed a size threshold, exemplifying the ``emergen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03262","kind":"arxiv","version":3},"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/2310.03262/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":"2026-07-05T08:08:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"474mf9dUSZF+hZ+GgzntE34PfXwRjf/EnVignYdGgDkf2srOAF3lLcSCbxBNHTqVNAUMCH7yE+EKcc27/FzDBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T15:09:49.061778Z"},"content_sha256":"8918413e9c481db2eabdae49bc6653ecd0d64ecea94b7f6bcab9528558d54e6a","schema_version":"1.0","event_id":"sha256:8918413e9c481db2eabdae49bc6653ecd0d64ecea94b7f6bcab9528558d54e6a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/bundle.json","state_url":"https://pith.science/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/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":"2026-08-06T15:09:49Z","links":{"resolver":"https://pith.science/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT","bundle":"https://pith.science/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/bundle.json","state":"https://pith.science/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JCYAUQLKRKGC2FHQ7YG7CNVMYT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:JCYAUQLKRKGC2FHQ7YG7CNVMYT","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":"5f3977e7c0c4133b3e3033cdf59add7774c14359dee9397b113d02aa44931b1b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-05T02:35:00Z","title_canon_sha256":"a1ba8859b9ba7591c9a22c1c7135d86fde1efec309d6f336fa47a0fa35f5cb09"},"schema_version":"1.0","source":{"id":"2310.03262","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03262","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03262v3","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03262","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_12","alias_value":"JCYAUQLKRKGC","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_16","alias_value":"JCYAUQLKRKGC2FHQ","created_at":"2026-07-05T08:08:51Z"},{"alias_kind":"pith_short_8","alias_value":"JCYAUQLK","created_at":"2026-07-05T08:08:51Z"}],"graph_snapshots":[{"event_id":"sha256:8918413e9c481db2eabdae49bc6653ecd0d64ecea94b7f6bcab9528558d54e6a","target":"graph","created_at":"2026-07-05T08:08:51Z","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/2310.03262/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The scientific scale-up of large language models (LLMs) necessitates a comprehensive understanding of their scaling properties. However, the existing literature on the scaling properties only yields an incomplete answer: optimization loss decreases predictably as the model size increases, in line with established scaling law; yet no scaling law for task has been established and the task performances are far from predictable during scaling. Task performances typically show minor gains on small models until they improve dramatically once models exceed a size threshold, exemplifying the ``emergen","authors_text":"Chaoqun He, Guoyang Zeng, Maosong Sun, Ning Ding, Shengding Hu, Weilin Zhao, Xin Liu, Xinrong Zhang, Xu Han, Yankai Lin, Zebin Ou, Zhiyuan Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-05T02:35:00Z","title":"Predicting Emergent Abilities with Infinite Resolution Evaluation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03262","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:a79d7a119fc5d2b509080c4f1a57343b15cf36365ac2e5baafa3ac444e0389dd","target":"record","created_at":"2026-07-05T08:08:51Z","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":"5f3977e7c0c4133b3e3033cdf59add7774c14359dee9397b113d02aa44931b1b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-10-05T02:35:00Z","title_canon_sha256":"a1ba8859b9ba7591c9a22c1c7135d86fde1efec309d6f336fa47a0fa35f5cb09"},"schema_version":"1.0","source":{"id":"2310.03262","kind":"arxiv","version":3}},"canonical_sha256":"48b00a416a8a8c2d14f0fe0df136acc4e343cba58ad64fda50f16d28356a9f15","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"48b00a416a8a8c2d14f0fe0df136acc4e343cba58ad64fda50f16d28356a9f15","first_computed_at":"2026-07-05T08:08:51.816529Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:08:51.816529Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"u0XKCcfR/8Mr5O79zycbvUnUV8kUS1s+PlcLSMMZpKl/TfvUL34RYXh0Zaz2WMD6EIzAKXltlmmJavXcHtH3Aw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:08:51.817006Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.03262","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a79d7a119fc5d2b509080c4f1a57343b15cf36365ac2e5baafa3ac444e0389dd","sha256:8918413e9c481db2eabdae49bc6653ecd0d64ecea94b7f6bcab9528558d54e6a"],"state_sha256":"faefc59f6b3e078c6f74285d72d7fd53db88842c3231d3b109e994cf8b35ba79"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i8XAhxFLePFdSNS/Ac4x7kPMqrceUJShbv34Q5xlpKdhZ+giKnH/2b8dHuSt8spU8WNRM4ESgnQSNpQTgMkICA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T15:09:49.064896Z","bundle_sha256":"a209c27fe9388ceabe442e47bf8ed0d7e56e986b6394675734b8bb6a717755ef"}}