{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:NJTHOYK6P2PTQJALQLE2QCHII4","short_pith_number":"pith:NJTHOYK6","canonical_record":{"source":{"id":"2312.12728","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2023-12-20T02:55:15Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2dc59d7625a2a96d4132d93b563805e00ec471e4ae79a6b74944d33536d11b0e","abstract_canon_sha256":"42e3d891d7c86492e35972f44f694caceb11c6f5a9b31ec7d66ba6ddc0ab3c2b"},"schema_version":"1.0"},"canonical_sha256":"6a6677615e7e9f38240b82c9a808e8473baea7ee507d2a8748376ceea3cdbdf2","source":{"kind":"arxiv","id":"2312.12728","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.12728","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"arxiv_version","alias_value":"2312.12728v3","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.12728","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_12","alias_value":"NJTHOYK6P2PT","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_16","alias_value":"NJTHOYK6P2PTQJAL","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_8","alias_value":"NJTHOYK6","created_at":"2026-07-05T08:24:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:NJTHOYK6P2PTQJALQLE2QCHII4","target":"record","payload":{"canonical_record":{"source":{"id":"2312.12728","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2023-12-20T02:55:15Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2dc59d7625a2a96d4132d93b563805e00ec471e4ae79a6b74944d33536d11b0e","abstract_canon_sha256":"42e3d891d7c86492e35972f44f694caceb11c6f5a9b31ec7d66ba6ddc0ab3c2b"},"schema_version":"1.0"},"canonical_sha256":"6a6677615e7e9f38240b82c9a808e8473baea7ee507d2a8748376ceea3cdbdf2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:24:59.067086Z","signature_b64":"SrZRilnCxLOtGBO3dRvoReVAJtTIPak9Cd+jfPX25Ykn7YPfx7RrKnQbbG9knf0ahqgY6xWc9Pm//RezCIE+Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a6677615e7e9f38240b82c9a808e8473baea7ee507d2a8748376ceea3cdbdf2","last_reissued_at":"2026-07-05T08:24:59.066562Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:24:59.066562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.12728","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":"2026-07-05T08:24:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"at56T2bPDir1Ei6CleVNgBtL0aCACZgYlzknsdu3IW5jRFyyNd91vVqFiKtaK8bTCdTxsbXyoiaDLi65/4YxDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T13:57:33.718588Z"},"content_sha256":"5666b9dd5cf6c3e7e92ce1f636b54bc01ad04b3e013ddad75f96060c2c907d91","schema_version":"1.0","event_id":"sha256:5666b9dd5cf6c3e7e92ce1f636b54bc01ad04b3e013ddad75f96060c2c907d91"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:NJTHOYK6P2PTQJALQLE2QCHII4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.IR","authors_text":"Chen Liang, Chenyi Zhuang, Jinjie Gu, Yao Zhao, Zhitian Xie","submitted_at":"2023-12-20T02:55:15Z","abstract_excerpt":"As Large Language Models (LLMs) have made significant advancements across various tasks, such as question answering, translation, text summarization, and dialogue systems, the need for accuracy in information becomes crucial, especially for serious financial products serving billions of users like Alipay. However, for a real-world product serving millions of users, the inference speed of LLMs becomes a critical factor compared to a mere experimental model.\n  Hence, this paper presents a generic framework for accelerating the inference process, resulting in a substantial increase in speed and c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.12728","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/2312.12728/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":"2026-07-05T08:24:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kQUQUnYNuf4RTWBhrp/Zgn11RLyuA6eMIY2jcPKkHELqjqKb8rr+wirs6NAzPzyTLH66h97IsbIv4YQvFm8wCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T13:57:33.718983Z"},"content_sha256":"7da8b9f81697fa22f38e6d77ffd5777a630d246afd9daeb78640af97406056f0","schema_version":"1.0","event_id":"sha256:7da8b9f81697fa22f38e6d77ffd5777a630d246afd9daeb78640af97406056f0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NJTHOYK6P2PTQJALQLE2QCHII4/bundle.json","state_url":"https://pith.science/pith/NJTHOYK6P2PTQJALQLE2QCHII4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NJTHOYK6P2PTQJALQLE2QCHII4/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":"2026-07-10T13:57:33Z","links":{"resolver":"https://pith.science/pith/NJTHOYK6P2PTQJALQLE2QCHII4","bundle":"https://pith.science/pith/NJTHOYK6P2PTQJALQLE2QCHII4/bundle.json","state":"https://pith.science/pith/NJTHOYK6P2PTQJALQLE2QCHII4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NJTHOYK6P2PTQJALQLE2QCHII4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:NJTHOYK6P2PTQJALQLE2QCHII4","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":"42e3d891d7c86492e35972f44f694caceb11c6f5a9b31ec7d66ba6ddc0ab3c2b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2023-12-20T02:55:15Z","title_canon_sha256":"2dc59d7625a2a96d4132d93b563805e00ec471e4ae79a6b74944d33536d11b0e"},"schema_version":"1.0","source":{"id":"2312.12728","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.12728","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"arxiv_version","alias_value":"2312.12728v3","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.12728","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_12","alias_value":"NJTHOYK6P2PT","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_16","alias_value":"NJTHOYK6P2PTQJAL","created_at":"2026-07-05T08:24:59Z"},{"alias_kind":"pith_short_8","alias_value":"NJTHOYK6","created_at":"2026-07-05T08:24:59Z"}],"graph_snapshots":[{"event_id":"sha256:7da8b9f81697fa22f38e6d77ffd5777a630d246afd9daeb78640af97406056f0","target":"graph","created_at":"2026-07-05T08:24:59Z","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/2312.12728/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As Large Language Models (LLMs) have made significant advancements across various tasks, such as question answering, translation, text summarization, and dialogue systems, the need for accuracy in information becomes crucial, especially for serious financial products serving billions of users like Alipay. However, for a real-world product serving millions of users, the inference speed of LLMs becomes a critical factor compared to a mere experimental model.\n  Hence, this paper presents a generic framework for accelerating the inference process, resulting in a substantial increase in speed and c","authors_text":"Chen Liang, Chenyi Zhuang, Jinjie Gu, Yao Zhao, Zhitian Xie","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2023-12-20T02:55:15Z","title":"Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.12728","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":"sha256:5666b9dd5cf6c3e7e92ce1f636b54bc01ad04b3e013ddad75f96060c2c907d91","target":"record","created_at":"2026-07-05T08:24:59Z","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":"42e3d891d7c86492e35972f44f694caceb11c6f5a9b31ec7d66ba6ddc0ab3c2b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.IR","submitted_at":"2023-12-20T02:55:15Z","title_canon_sha256":"2dc59d7625a2a96d4132d93b563805e00ec471e4ae79a6b74944d33536d11b0e"},"schema_version":"1.0","source":{"id":"2312.12728","kind":"arxiv","version":3}},"canonical_sha256":"6a6677615e7e9f38240b82c9a808e8473baea7ee507d2a8748376ceea3cdbdf2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a6677615e7e9f38240b82c9a808e8473baea7ee507d2a8748376ceea3cdbdf2","first_computed_at":"2026-07-05T08:24:59.066562Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:24:59.066562Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SrZRilnCxLOtGBO3dRvoReVAJtTIPak9Cd+jfPX25Ykn7YPfx7RrKnQbbG9knf0ahqgY6xWc9Pm//RezCIE+Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:24:59.067086Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.12728","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5666b9dd5cf6c3e7e92ce1f636b54bc01ad04b3e013ddad75f96060c2c907d91","sha256:7da8b9f81697fa22f38e6d77ffd5777a630d246afd9daeb78640af97406056f0"],"state_sha256":"91a73697dfc34a83328854487e01b920e47e2eff02c7085da3b17a6d84cfe9c2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/WQgrPnj5AEgvdxBOUkqgYCkfGuD/d5uVnHPutcXOJw3OgVpAomyLin+E3dL17AsE2cQ6VB2p0HQ5R9v+9XxCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T13:57:33.721056Z","bundle_sha256":"f5a8b81cd33ab4077e4e9470fb92b633f9e7f7b5023b8f6cf57d444cf757faae"}}