{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:HWVMSN4VYRYK74LDOXJV7RA6AE","short_pith_number":"pith:HWVMSN4V","canonical_record":{"source":{"id":"2205.11200","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-23T11:10:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1db61f987680cc30236973b688683e29f621146c8362df46a2eb1ae6f1fdd59f","abstract_canon_sha256":"d5abbc45adcec38ee131eb68aedb91725d1faea4cc5065dbc4b289ec8bc923c3"},"schema_version":"1.0"},"canonical_sha256":"3daac93795c470aff16375d35fc41e01376f6569f2608c97262546a6b6809749","source":{"kind":"arxiv","id":"2205.11200","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11200","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11200v2","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11200","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_12","alias_value":"HWVMSN4VYRYK","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_16","alias_value":"HWVMSN4VYRYK74LD","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_8","alias_value":"HWVMSN4V","created_at":"2026-07-05T05:06:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:HWVMSN4VYRYK74LDOXJV7RA6AE","target":"record","payload":{"canonical_record":{"source":{"id":"2205.11200","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-23T11:10:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1db61f987680cc30236973b688683e29f621146c8362df46a2eb1ae6f1fdd59f","abstract_canon_sha256":"d5abbc45adcec38ee131eb68aedb91725d1faea4cc5065dbc4b289ec8bc923c3"},"schema_version":"1.0"},"canonical_sha256":"3daac93795c470aff16375d35fc41e01376f6569f2608c97262546a6b6809749","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:06:31.535706Z","signature_b64":"hngei10cu+ywOxiY5KBs/ZaMNh9E9xuOPTLvMi9Raoe2RIAvqA1QkjmPvsYzOoncMQzydugmMaS6jyXgAqCnAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3daac93795c470aff16375d35fc41e01376f6569f2608c97262546a6b6809749","last_reissued_at":"2026-07-05T05:06:31.535253Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:06:31.535253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.11200","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:06:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G6xHeF3fxvqjm0EcVc6mPSMynxqj7kwW+RhZJfXkzf9UOFTPiUmD28YGLOD7KmVH2k8DK8n0OVbAElB3nzRMBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:02:59.948272Z"},"content_sha256":"1030e13352fef10b63385802d1074c50d0a55f2da14ef6c923b4dffdc03cfaa0","schema_version":"1.0","event_id":"sha256:1030e13352fef10b63385802d1074c50d0a55f2da14ef6c923b4dffdc03cfaa0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:HWVMSN4VYRYK74LDOXJV7RA6AE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BBTv2: Towards a Gradient-Free Future with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Hong Qian, Tianxiang Sun, Xipeng Qiu, Xuanjing Huang, Yunhua Zhou, Zhengfu He","submitted_at":"2022-05-23T11:10:19Z","abstract_excerpt":"Most downstream adaptation methods tune all or part of the parameters of pre-trained models (PTMs) through gradient descent, where the tuning cost increases linearly with the growth of the model size. By contrast, gradient-free methods only require the forward computation of the PTM to tune the prompt, retaining the benefits of efficient tuning and deployment. Though, past work on gradient-free tuning often introduces gradient descent to seek a good initialization of prompt and lacks versatility across tasks and PTMs. In this paper, we present BBTv2, an improved version of Black-Box Tuning, to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11200","kind":"arxiv","version":2},"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/2205.11200/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":"2026-07-05T05:06:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5+W+kK8/Jy0GiVs5V3+Gu4VKKj877P2zTJsm3Fhq990IuOlxkC1QgL4X7uc+ra1Pi/Z275bSe42dNI7Zf6k3AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T04:02:59.948756Z"},"content_sha256":"6136ef0a76f256f009388058e8934e558fd55042508fb778b39035a7217cc68e","schema_version":"1.0","event_id":"sha256:6136ef0a76f256f009388058e8934e558fd55042508fb778b39035a7217cc68e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/bundle.json","state_url":"https://pith.science/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/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":"2026-08-06T04:02:59Z","links":{"resolver":"https://pith.science/pith/HWVMSN4VYRYK74LDOXJV7RA6AE","bundle":"https://pith.science/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/bundle.json","state":"https://pith.science/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HWVMSN4VYRYK74LDOXJV7RA6AE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:HWVMSN4VYRYK74LDOXJV7RA6AE","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":"d5abbc45adcec38ee131eb68aedb91725d1faea4cc5065dbc4b289ec8bc923c3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-23T11:10:19Z","title_canon_sha256":"1db61f987680cc30236973b688683e29f621146c8362df46a2eb1ae6f1fdd59f"},"schema_version":"1.0","source":{"id":"2205.11200","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11200","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11200v2","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11200","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_12","alias_value":"HWVMSN4VYRYK","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_16","alias_value":"HWVMSN4VYRYK74LD","created_at":"2026-07-05T05:06:31Z"},{"alias_kind":"pith_short_8","alias_value":"HWVMSN4V","created_at":"2026-07-05T05:06:31Z"}],"graph_snapshots":[{"event_id":"sha256:6136ef0a76f256f009388058e8934e558fd55042508fb778b39035a7217cc68e","target":"graph","created_at":"2026-07-05T05:06:31Z","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/2205.11200/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Most downstream adaptation methods tune all or part of the parameters of pre-trained models (PTMs) through gradient descent, where the tuning cost increases linearly with the growth of the model size. By contrast, gradient-free methods only require the forward computation of the PTM to tune the prompt, retaining the benefits of efficient tuning and deployment. Though, past work on gradient-free tuning often introduces gradient descent to seek a good initialization of prompt and lacks versatility across tasks and PTMs. In this paper, we present BBTv2, an improved version of Black-Box Tuning, to","authors_text":"Hong Qian, Tianxiang Sun, Xipeng Qiu, Xuanjing Huang, Yunhua Zhou, Zhengfu He","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-23T11:10:19Z","title":"BBTv2: Towards a Gradient-Free Future with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11200","kind":"arxiv","version":2},"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":"sha256:1030e13352fef10b63385802d1074c50d0a55f2da14ef6c923b4dffdc03cfaa0","target":"record","created_at":"2026-07-05T05:06:31Z","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":"d5abbc45adcec38ee131eb68aedb91725d1faea4cc5065dbc4b289ec8bc923c3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-23T11:10:19Z","title_canon_sha256":"1db61f987680cc30236973b688683e29f621146c8362df46a2eb1ae6f1fdd59f"},"schema_version":"1.0","source":{"id":"2205.11200","kind":"arxiv","version":2}},"canonical_sha256":"3daac93795c470aff16375d35fc41e01376f6569f2608c97262546a6b6809749","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3daac93795c470aff16375d35fc41e01376f6569f2608c97262546a6b6809749","first_computed_at":"2026-07-05T05:06:31.535253Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:06:31.535253Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hngei10cu+ywOxiY5KBs/ZaMNh9E9xuOPTLvMi9Raoe2RIAvqA1QkjmPvsYzOoncMQzydugmMaS6jyXgAqCnAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:06:31.535706Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11200","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1030e13352fef10b63385802d1074c50d0a55f2da14ef6c923b4dffdc03cfaa0","sha256:6136ef0a76f256f009388058e8934e558fd55042508fb778b39035a7217cc68e"],"state_sha256":"b0d4d917182aff6eb69198a62e514a199d80a8676d667d12abd8414cae5448fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Am191iEBBtg+6r2UpQzwygz6h7OtXvBivt/6/T2BNkI/D8UIEOFLF5PCh0yK+SEiGIwia+fI2YbqoW2TDZyuBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T04:02:59.951880Z","bundle_sha256":"7c5d13ffbb54358b9ddcd63ad1cd6fa9d193ab9b865c4a78155b4c2668b138b9"}}