{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:PAQ33ITSBSBDFUJXVZC6UKZYBP","short_pith_number":"pith:PAQ33ITS","canonical_record":{"source":{"id":"2202.07962","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-16T10:11:19Z","cross_cats_sorted":[],"title_canon_sha256":"3500b8ae7985648727a51db71a55592c921ebe53b7ca5c03a0c8ff73a4759b9c","abstract_canon_sha256":"25ea9f278f1151b5918f0a4df5d985a22061426b5c937993e2660bd59495847b"},"schema_version":"1.0"},"canonical_sha256":"7821bda2720c8232d137ae45ea2b380bcea18db6a03f1d0fe109881aec47bdc1","source":{"kind":"arxiv","id":"2202.07962","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.07962","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"arxiv_version","alias_value":"2202.07962v2","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.07962","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_12","alias_value":"PAQ33ITSBSBD","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_16","alias_value":"PAQ33ITSBSBDFUJX","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_8","alias_value":"PAQ33ITS","created_at":"2026-07-05T05:09:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:PAQ33ITSBSBDFUJXVZC6UKZYBP","target":"record","payload":{"canonical_record":{"source":{"id":"2202.07962","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-16T10:11:19Z","cross_cats_sorted":[],"title_canon_sha256":"3500b8ae7985648727a51db71a55592c921ebe53b7ca5c03a0c8ff73a4759b9c","abstract_canon_sha256":"25ea9f278f1151b5918f0a4df5d985a22061426b5c937993e2660bd59495847b"},"schema_version":"1.0"},"canonical_sha256":"7821bda2720c8232d137ae45ea2b380bcea18db6a03f1d0fe109881aec47bdc1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:09:15.576662Z","signature_b64":"G39hShAGJwPQXD1/337qLMwbVtNg+3nOKpCXNgK1txIY56pirmjWm8JeZDm8J09wxM37IaPSVj5RbkxVXmKVDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7821bda2720c8232d137ae45ea2b380bcea18db6a03f1d0fe109881aec47bdc1","last_reissued_at":"2026-07-05T05:09:15.576238Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:09:15.576238Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.07962","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":"2026-07-05T05:09:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w58A5R2V4jCu+8vMyDUVrQqj7PUhRCnIRp9nkV4g87jjsrST210d/asucBeNp4ewZzHFx7X1aDWS/k3KI0tLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T12:44:10.394116Z"},"content_sha256":"da583b9d3938fb064f1b936d4679b3bfee7d315e3267e397856c44da631e6c87","schema_version":"1.0","event_id":"sha256:da583b9d3938fb064f1b936d4679b3bfee7d315e3267e397856c44da631e6c87"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:PAQ33ITSBSBDFUJXVZC6UKZYBP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Parameter-Efficient Tuning: Are We Really There Yet?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Fangyu Liu, Guanzheng Chen, Shangsong Liang, Zaiqiao Meng","submitted_at":"2022-02-16T10:11:19Z","abstract_excerpt":"Parameter-Efficient Tuning (PETuning) methods have been deemed by many as the new paradigm for using pretrained language models (PLMs). By tuning just a fraction amount of parameters comparing to full model finetuning, PETuning methods claim to have achieved performance on par with or even better than finetuning. In this work, we take a step back and re-examine these PETuning methods by conducting the first comprehensive investigation into the training and evaluation of them. We found the problematic validation and testing practice in current studies, when accompanied by the instability nature"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.07962","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/2202.07962/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":"2026-07-05T05:09:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qmGX4aijvePli0OH8nYSPul5ZzwkYS6qUPYf3ZqLZzG3oaSPt3OGcO+ZbPoH9TWwTYv25SBky/yzV/Mow8rtAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T12:44:10.394617Z"},"content_sha256":"6f8b703a6e8994be59e391d565caa488d32f50e5ac33fcb57d81eae4789d82e9","schema_version":"1.0","event_id":"sha256:6f8b703a6e8994be59e391d565caa488d32f50e5ac33fcb57d81eae4789d82e9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/bundle.json","state_url":"https://pith.science/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/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":"2026-08-16T12:44:10Z","links":{"resolver":"https://pith.science/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP","bundle":"https://pith.science/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/bundle.json","state":"https://pith.science/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PAQ33ITSBSBDFUJXVZC6UKZYBP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:PAQ33ITSBSBDFUJXVZC6UKZYBP","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":"25ea9f278f1151b5918f0a4df5d985a22061426b5c937993e2660bd59495847b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-16T10:11:19Z","title_canon_sha256":"3500b8ae7985648727a51db71a55592c921ebe53b7ca5c03a0c8ff73a4759b9c"},"schema_version":"1.0","source":{"id":"2202.07962","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.07962","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"arxiv_version","alias_value":"2202.07962v2","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.07962","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_12","alias_value":"PAQ33ITSBSBD","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_16","alias_value":"PAQ33ITSBSBDFUJX","created_at":"2026-07-05T05:09:15Z"},{"alias_kind":"pith_short_8","alias_value":"PAQ33ITS","created_at":"2026-07-05T05:09:15Z"}],"graph_snapshots":[{"event_id":"sha256:6f8b703a6e8994be59e391d565caa488d32f50e5ac33fcb57d81eae4789d82e9","target":"graph","created_at":"2026-07-05T05:09:15Z","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/2202.07962/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parameter-Efficient Tuning (PETuning) methods have been deemed by many as the new paradigm for using pretrained language models (PLMs). By tuning just a fraction amount of parameters comparing to full model finetuning, PETuning methods claim to have achieved performance on par with or even better than finetuning. In this work, we take a step back and re-examine these PETuning methods by conducting the first comprehensive investigation into the training and evaluation of them. We found the problematic validation and testing practice in current studies, when accompanied by the instability nature","authors_text":"Fangyu Liu, Guanzheng Chen, Shangsong Liang, Zaiqiao Meng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-16T10:11:19Z","title":"Revisiting Parameter-Efficient Tuning: Are We Really There Yet?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.07962","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:da583b9d3938fb064f1b936d4679b3bfee7d315e3267e397856c44da631e6c87","target":"record","created_at":"2026-07-05T05:09:15Z","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":"25ea9f278f1151b5918f0a4df5d985a22061426b5c937993e2660bd59495847b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-02-16T10:11:19Z","title_canon_sha256":"3500b8ae7985648727a51db71a55592c921ebe53b7ca5c03a0c8ff73a4759b9c"},"schema_version":"1.0","source":{"id":"2202.07962","kind":"arxiv","version":2}},"canonical_sha256":"7821bda2720c8232d137ae45ea2b380bcea18db6a03f1d0fe109881aec47bdc1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7821bda2720c8232d137ae45ea2b380bcea18db6a03f1d0fe109881aec47bdc1","first_computed_at":"2026-07-05T05:09:15.576238Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:09:15.576238Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G39hShAGJwPQXD1/337qLMwbVtNg+3nOKpCXNgK1txIY56pirmjWm8JeZDm8J09wxM37IaPSVj5RbkxVXmKVDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:09:15.576662Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.07962","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:da583b9d3938fb064f1b936d4679b3bfee7d315e3267e397856c44da631e6c87","sha256:6f8b703a6e8994be59e391d565caa488d32f50e5ac33fcb57d81eae4789d82e9"],"state_sha256":"d77d19a945e9a5e54b02d34c0eccb19e19ea468a78d46cf99290fa30fb65236d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"98L8tVZwXEPp9Ma5qyFECIuFzsDFv24oOT80HC1mWL9MILkLwuE1TP34JU3EehmKrTG34L7PkN56tspDFc2+Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T12:44:10.400645Z","bundle_sha256":"f6642d6d79c6b35b648e570285b928a308958cf8d33f0d963f257ad2b7d772b0"}}