{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:TEUINFWSTH6QAKVHC7HXZOUW5P","short_pith_number":"pith:TEUINFWS","canonical_record":{"source":{"id":"2011.09463","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-11-18T18:41:27Z","cross_cats_sorted":[],"title_canon_sha256":"5a98d84272508712d36db0a49662410f04c5e3033517a37e5c321197c99ee07b","abstract_canon_sha256":"f354c4c25de00a72a496c33fa6dcb834d02a95bb7b2d79a2a0dfc644b64ad110"},"schema_version":"1.0"},"canonical_sha256":"99288696d299fd002aa717cf7cba96ebc451fbbfbf746756fb4cd8ef9b18302d","source":{"kind":"arxiv","id":"2011.09463","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.09463","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"arxiv_version","alias_value":"2011.09463v3","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.09463","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_12","alias_value":"TEUINFWSTH6Q","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_16","alias_value":"TEUINFWSTH6QAKVH","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_8","alias_value":"TEUINFWS","created_at":"2026-07-05T03:07:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:TEUINFWSTH6QAKVHC7HXZOUW5P","target":"record","payload":{"canonical_record":{"source":{"id":"2011.09463","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-11-18T18:41:27Z","cross_cats_sorted":[],"title_canon_sha256":"5a98d84272508712d36db0a49662410f04c5e3033517a37e5c321197c99ee07b","abstract_canon_sha256":"f354c4c25de00a72a496c33fa6dcb834d02a95bb7b2d79a2a0dfc644b64ad110"},"schema_version":"1.0"},"canonical_sha256":"99288696d299fd002aa717cf7cba96ebc451fbbfbf746756fb4cd8ef9b18302d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:07:26.376383Z","signature_b64":"N5/hMD4qhLWlJyO5sktDn2kvZoctQEpCoYUEhyXgzvD5CXF//WRGGyCDpaNCdTgy5fN1WGmj0QWCHW+kzE/1Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99288696d299fd002aa717cf7cba96ebc451fbbfbf746756fb4cd8ef9b18302d","last_reissued_at":"2026-07-05T03:07:26.375954Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:07:26.375954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.09463","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":"2026-07-05T03:07:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DCPeLu95ZVTKurNNgLpazNyRaI9vjov3tsLXa1E8DZ6SW2CGUnrlL896GoDvAKpBPlmdjJmI5vLhhhlxG0zmBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:32:14.476695Z"},"content_sha256":"89526c4ecbb8af486502d2c0adace82b43ad9a9d61cddecac202138d2a061773","schema_version":"1.0","event_id":"sha256:89526c4ecbb8af486502d2c0adace82b43ad9a9d61cddecac202138d2a061773"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:TEUINFWSTH6QAKVHC7HXZOUW5P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ang Wang, Cen Chen, Chengyu Wang, Deng Cai, Hanjie Pan, Jun Huang, Minghui Qiu, Peng Li, Wei Lin, Xianyan Jia, Yaliang Li","submitted_at":"2020-11-18T18:41:27Z","abstract_excerpt":"The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP) applications, yet it is not easy to build an easy-to-use and scalable TL toolkit for this purpose. To bridge this gap, the EasyTransfer platform is designed to develop deep TL algorithms for NLP applications. EasyTransfer is backended with a high-performance and scalable engine for efficient training and inference, and also integrates comprehensive deep TL algorithms, to make the development of industrial-scale TL a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.09463","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/2011.09463/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":"2026-07-05T03:07:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lkpIT5ohzlS+4nEZ3RIWIpCLKQ6IgM1UzkC7jYPDHCZGJyoddH+vttkiLhskFueX80X3fU8qBMpJa8oB8tycDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:32:14.477212Z"},"content_sha256":"54d084879f9b434516f07760db06bd608c0a05ed1baeed936176e6b85f0aa0bb","schema_version":"1.0","event_id":"sha256:54d084879f9b434516f07760db06bd608c0a05ed1baeed936176e6b85f0aa0bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/bundle.json","state_url":"https://pith.science/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/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":"2026-08-01T08:32:14Z","links":{"resolver":"https://pith.science/pith/TEUINFWSTH6QAKVHC7HXZOUW5P","bundle":"https://pith.science/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/bundle.json","state":"https://pith.science/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TEUINFWSTH6QAKVHC7HXZOUW5P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:TEUINFWSTH6QAKVHC7HXZOUW5P","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":"f354c4c25de00a72a496c33fa6dcb834d02a95bb7b2d79a2a0dfc644b64ad110","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-11-18T18:41:27Z","title_canon_sha256":"5a98d84272508712d36db0a49662410f04c5e3033517a37e5c321197c99ee07b"},"schema_version":"1.0","source":{"id":"2011.09463","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.09463","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"arxiv_version","alias_value":"2011.09463v3","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.09463","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_12","alias_value":"TEUINFWSTH6Q","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_16","alias_value":"TEUINFWSTH6QAKVH","created_at":"2026-07-05T03:07:26Z"},{"alias_kind":"pith_short_8","alias_value":"TEUINFWS","created_at":"2026-07-05T03:07:26Z"}],"graph_snapshots":[{"event_id":"sha256:54d084879f9b434516f07760db06bd608c0a05ed1baeed936176e6b85f0aa0bb","target":"graph","created_at":"2026-07-05T03:07:26Z","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/2011.09463/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP) applications, yet it is not easy to build an easy-to-use and scalable TL toolkit for this purpose. To bridge this gap, the EasyTransfer platform is designed to develop deep TL algorithms for NLP applications. EasyTransfer is backended with a high-performance and scalable engine for efficient training and inference, and also integrates comprehensive deep TL algorithms, to make the development of industrial-scale TL a","authors_text":"Ang Wang, Cen Chen, Chengyu Wang, Deng Cai, Hanjie Pan, Jun Huang, Minghui Qiu, Peng Li, Wei Lin, Xianyan Jia, Yaliang Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-11-18T18:41:27Z","title":"EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.09463","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":"sha256:89526c4ecbb8af486502d2c0adace82b43ad9a9d61cddecac202138d2a061773","target":"record","created_at":"2026-07-05T03:07:26Z","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":"f354c4c25de00a72a496c33fa6dcb834d02a95bb7b2d79a2a0dfc644b64ad110","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-11-18T18:41:27Z","title_canon_sha256":"5a98d84272508712d36db0a49662410f04c5e3033517a37e5c321197c99ee07b"},"schema_version":"1.0","source":{"id":"2011.09463","kind":"arxiv","version":3}},"canonical_sha256":"99288696d299fd002aa717cf7cba96ebc451fbbfbf746756fb4cd8ef9b18302d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99288696d299fd002aa717cf7cba96ebc451fbbfbf746756fb4cd8ef9b18302d","first_computed_at":"2026-07-05T03:07:26.375954Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:07:26.375954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N5/hMD4qhLWlJyO5sktDn2kvZoctQEpCoYUEhyXgzvD5CXF//WRGGyCDpaNCdTgy5fN1WGmj0QWCHW+kzE/1Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:07:26.376383Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.09463","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:89526c4ecbb8af486502d2c0adace82b43ad9a9d61cddecac202138d2a061773","sha256:54d084879f9b434516f07760db06bd608c0a05ed1baeed936176e6b85f0aa0bb"],"state_sha256":"4968c919165779b2526631f96241870f7c9eda0f3eda0c00b2aaf34c72252ea9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DfgOWLt89poVnbTNvLb0mbc6ku39vM5vqoHX26gQ3+zVvArAIZ7kevop1R4I/HHTcILiB09L3AB3RocxscaxCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T08:32:14.485071Z","bundle_sha256":"bbaebad2f69c7f76164fd9f9ece1d358c3f8e0aabf11915bc9141fc8bb1d3602"}}