{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:UBSNX26YAYCSHNN75PTCFEQ6ZS","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":"42f6a33253afc563b88378e2c132ff9d6216f14bd5f685c33473cb5370befd5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T03:50:23Z","title_canon_sha256":"d0fe315c87157e63d9986492efa0b6031337e0af40daad4b29df9dce146c1dde"},"schema_version":"1.0","source":{"id":"2205.12471","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.12471","created_at":"2026-07-05T04:26:26Z"},{"alias_kind":"arxiv_version","alias_value":"2205.12471v1","created_at":"2026-07-05T04:26:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.12471","created_at":"2026-07-05T04:26:26Z"},{"alias_kind":"pith_short_12","alias_value":"UBSNX26YAYCS","created_at":"2026-07-05T04:26:26Z"},{"alias_kind":"pith_short_16","alias_value":"UBSNX26YAYCSHNN7","created_at":"2026-07-05T04:26:26Z"},{"alias_kind":"pith_short_8","alias_value":"UBSNX26Y","created_at":"2026-07-05T04:26:26Z"}],"graph_snapshots":[{"event_id":"sha256:246ae433421c06aa48678c6df28e4c96ffe4819d8f8674c6fd4cb1a4adf971bb","target":"graph","created_at":"2026-07-05T04:26:26Z","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/2205.12471/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Prompt tuning (PT) is an effective approach to adapting pre-trained language models to downstream tasks. Without a good initialization, prompt tuning doesn't perform well under few-shot settings. So pre-trained prompt tuning (PPT) is proposed to initialize prompts by leveraging pre-training data. We propose MetaPT (Meta-learned Prompt Tuning) to further improve PPT's initialization by considering latent structure within the pre-training data. Specifically, we introduce the structure by first clustering pre-training data into different auxiliary tasks with unsupervised methods. Then we use thes","authors_text":"Kun Qian, Yukun Huang, Zhou Yu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T03:50:23Z","title":"Learning a Better Initialization for Soft Prompts via Meta-Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.12471","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":"sha256:3d58850d0bf25130ab40724def1fdfe3acf16b90a642d84e3dd08e11251ee7c7","target":"record","created_at":"2026-07-05T04:26:26Z","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":"42f6a33253afc563b88378e2c132ff9d6216f14bd5f685c33473cb5370befd5b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-05-25T03:50:23Z","title_canon_sha256":"d0fe315c87157e63d9986492efa0b6031337e0af40daad4b29df9dce146c1dde"},"schema_version":"1.0","source":{"id":"2205.12471","kind":"arxiv","version":1}},"canonical_sha256":"a064dbebd8060523b5bfebe622921ecc8f3c7f6d13a267f8f1a91344a889ece7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a064dbebd8060523b5bfebe622921ecc8f3c7f6d13a267f8f1a91344a889ece7","first_computed_at":"2026-07-05T04:26:26.117058Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:26:26.117058Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EwsTLT5Ih07AY4qRVvWSgh4FRMAZlzdGcR5KVisDpI5/oWyqJzLY6qR068f2VMYxeqn2UwbgN70pbMvkxalWDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:26:26.117420Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.12471","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d58850d0bf25130ab40724def1fdfe3acf16b90a642d84e3dd08e11251ee7c7","sha256:246ae433421c06aa48678c6df28e4c96ffe4819d8f8674c6fd4cb1a4adf971bb"],"state_sha256":"8f9545d7afd5281397d921fd46bb746393e13556f9b853a676a3ef7ee5ca1aca"}