{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:SDNZB6WMET7HVSQZ77EARMROPH","short_pith_number":"pith:SDNZB6WM","canonical_record":{"source":{"id":"2210.03029","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T16:26:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"677ff2d933a814b3bd4c8c641c92ef6f7f1b65347747a62ff3ec395154478e1c","abstract_canon_sha256":"1b32d52fed58238b636cc323a52df9a72e2f4be8f96e043d6bd4272a4d44f834"},"schema_version":"1.0"},"canonical_sha256":"90db90facc24fe7aca19ffc808b22e79f09554b8d89ef3a63520813eeb23e6c0","source":{"kind":"arxiv","id":"2210.03029","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03029","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03029v4","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03029","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_12","alias_value":"SDNZB6WMET7H","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_16","alias_value":"SDNZB6WMET7HVSQZ","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_8","alias_value":"SDNZB6WM","created_at":"2026-07-05T07:00:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:SDNZB6WMET7HVSQZ77EARMROPH","target":"record","payload":{"canonical_record":{"source":{"id":"2210.03029","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T16:26:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"677ff2d933a814b3bd4c8c641c92ef6f7f1b65347747a62ff3ec395154478e1c","abstract_canon_sha256":"1b32d52fed58238b636cc323a52df9a72e2f4be8f96e043d6bd4272a4d44f834"},"schema_version":"1.0"},"canonical_sha256":"90db90facc24fe7aca19ffc808b22e79f09554b8d89ef3a63520813eeb23e6c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:00:56.677904Z","signature_b64":"1pQTkPgceERj6XbAB2Pq3bk+PQid5WpBd7tuy1w2AY0Wtjq9DqB9xigBrQtP2VSyGjzzXuwjshsvtF3B+OrNDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90db90facc24fe7aca19ffc808b22e79f09554b8d89ef3a63520813eeb23e6c0","last_reissued_at":"2026-07-05T07:00:56.677407Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:00:56.677407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.03029","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:00:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YMAf+1maLipGH+I7Voc2S1CyVVCQLZwZnvSU9MJVnGRnYPXvHN2vXRY03g0AOpYw0LwsILvTc/IDC/RGVQqlAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T22:57:49.033670Z"},"content_sha256":"34bbde577b4b6cebdf60ce612f537c600d32284f41875c0bb48a5988edd5d997","schema_version":"1.0","event_id":"sha256:34bbde577b4b6cebdf60ce612f537c600d32284f41875c0bb48a5988edd5d997"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:SDNZB6WMET7HVSQZ77EARMROPH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft Prompt","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Doyoung Kim, Joel Jang, Minjoon Seo, Seonghyeon Ye, Yongrae Jo","submitted_at":"2022-10-06T16:26:03Z","abstract_excerpt":"Enhancing the zero-shot performance of instruction-following models requires heavy computation, either by scaling the total number of training datasets or the model size. In this work, we explore how retrieval of soft prompts obtained through prompt tuning can efficiently assist hard prompts in zero-shot task generalization. Specifically, we train soft prompt embeddings for each prompt through prompt tuning, store the samples of the training instances mapped with the prompt embeddings, and retrieve the corresponding prompt embedding of the training instance closest to the query instance during"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03029","kind":"arxiv","version":4},"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/2210.03029/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":"2026-07-05T07:00:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gVUd7JVuRClNUGber6Yj/a+3AxHZiAAs6UyeXMVWdOTfnFOI6qJ6jXcxLHT8UW2iBxWn8bXDfcDeYiMTtFL3CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T22:57:49.034062Z"},"content_sha256":"d7e8e9820a4b2510db9b7b5f71fa3de88d74e1e844a1e75e8778330be6f4d7da","schema_version":"1.0","event_id":"sha256:d7e8e9820a4b2510db9b7b5f71fa3de88d74e1e844a1e75e8778330be6f4d7da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SDNZB6WMET7HVSQZ77EARMROPH/bundle.json","state_url":"https://pith.science/pith/SDNZB6WMET7HVSQZ77EARMROPH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SDNZB6WMET7HVSQZ77EARMROPH/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":"2026-08-03T22:57:49Z","links":{"resolver":"https://pith.science/pith/SDNZB6WMET7HVSQZ77EARMROPH","bundle":"https://pith.science/pith/SDNZB6WMET7HVSQZ77EARMROPH/bundle.json","state":"https://pith.science/pith/SDNZB6WMET7HVSQZ77EARMROPH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SDNZB6WMET7HVSQZ77EARMROPH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SDNZB6WMET7HVSQZ77EARMROPH","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":"1b32d52fed58238b636cc323a52df9a72e2f4be8f96e043d6bd4272a4d44f834","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T16:26:03Z","title_canon_sha256":"677ff2d933a814b3bd4c8c641c92ef6f7f1b65347747a62ff3ec395154478e1c"},"schema_version":"1.0","source":{"id":"2210.03029","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03029","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03029v4","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03029","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_12","alias_value":"SDNZB6WMET7H","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_16","alias_value":"SDNZB6WMET7HVSQZ","created_at":"2026-07-05T07:00:56Z"},{"alias_kind":"pith_short_8","alias_value":"SDNZB6WM","created_at":"2026-07-05T07:00:56Z"}],"graph_snapshots":[{"event_id":"sha256:d7e8e9820a4b2510db9b7b5f71fa3de88d74e1e844a1e75e8778330be6f4d7da","target":"graph","created_at":"2026-07-05T07:00:56Z","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/2210.03029/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Enhancing the zero-shot performance of instruction-following models requires heavy computation, either by scaling the total number of training datasets or the model size. In this work, we explore how retrieval of soft prompts obtained through prompt tuning can efficiently assist hard prompts in zero-shot task generalization. Specifically, we train soft prompt embeddings for each prompt through prompt tuning, store the samples of the training instances mapped with the prompt embeddings, and retrieve the corresponding prompt embedding of the training instance closest to the query instance during","authors_text":"Doyoung Kim, Joel Jang, Minjoon Seo, Seonghyeon Ye, Yongrae Jo","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T16:26:03Z","title":"Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft Prompt"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03029","kind":"arxiv","version":4},"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":"sha256:34bbde577b4b6cebdf60ce612f537c600d32284f41875c0bb48a5988edd5d997","target":"record","created_at":"2026-07-05T07:00:56Z","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":"1b32d52fed58238b636cc323a52df9a72e2f4be8f96e043d6bd4272a4d44f834","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-06T16:26:03Z","title_canon_sha256":"677ff2d933a814b3bd4c8c641c92ef6f7f1b65347747a62ff3ec395154478e1c"},"schema_version":"1.0","source":{"id":"2210.03029","kind":"arxiv","version":4}},"canonical_sha256":"90db90facc24fe7aca19ffc808b22e79f09554b8d89ef3a63520813eeb23e6c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90db90facc24fe7aca19ffc808b22e79f09554b8d89ef3a63520813eeb23e6c0","first_computed_at":"2026-07-05T07:00:56.677407Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:00:56.677407Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1pQTkPgceERj6XbAB2Pq3bk+PQid5WpBd7tuy1w2AY0Wtjq9DqB9xigBrQtP2VSyGjzzXuwjshsvtF3B+OrNDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:00:56.677904Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.03029","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34bbde577b4b6cebdf60ce612f537c600d32284f41875c0bb48a5988edd5d997","sha256:d7e8e9820a4b2510db9b7b5f71fa3de88d74e1e844a1e75e8778330be6f4d7da"],"state_sha256":"017c3e31fac37d3e9b52a45e469f2390cb37141c967e463fe3f0a5cd90c1aadc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ClGyi8mawEDleJXNido2ROXk8oOBAkXgY0YvdMc9J163eTQDxzNBuMfqqi0Jo/HWAdxkawKh0YVyekM3ct7vBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T22:57:49.037075Z","bundle_sha256":"a34d656ac47f857d9569af6c31722394391d8e1130f303da2957cf6399992e0c"}}