{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:HAU4ZNHVUC5CQB2UZK6RHB7VKV","short_pith_number":"pith:HAU4ZNHV","canonical_record":{"source":{"id":"2007.04239","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-31T21:52:31Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"3a4490a8321baad0067e88b464204390d98d81daa3218544cd47fb46ecf0d509","abstract_canon_sha256":"e17f1b31a65651d452610a01dd883059e53eadda78e10deb952a95e501981296"},"schema_version":"1.0"},"canonical_sha256":"3829ccb4f5a0ba280754cabd1387f55552828878933f479e518fc4629d8c5b7d","source":{"kind":"arxiv","id":"2007.04239","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.04239","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"arxiv_version","alias_value":"2007.04239v1","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.04239","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_12","alias_value":"HAU4ZNHVUC5C","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_16","alias_value":"HAU4ZNHVUC5CQB2U","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_8","alias_value":"HAU4ZNHV","created_at":"2026-07-05T01:17:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:HAU4ZNHVUC5CQB2UZK6RHB7VKV","target":"record","payload":{"canonical_record":{"source":{"id":"2007.04239","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-31T21:52:31Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"3a4490a8321baad0067e88b464204390d98d81daa3218544cd47fb46ecf0d509","abstract_canon_sha256":"e17f1b31a65651d452610a01dd883059e53eadda78e10deb952a95e501981296"},"schema_version":"1.0"},"canonical_sha256":"3829ccb4f5a0ba280754cabd1387f55552828878933f479e518fc4629d8c5b7d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:17:22.362302Z","signature_b64":"wfT2xSMF1CxBOt1a5hjrTdAkSSbibNgRQtdwsDtPWRu3Vy/54lBu9M//jLwANlp3m1rcAN2TGWoCAThmWY2FDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3829ccb4f5a0ba280754cabd1387f55552828878933f479e518fc4629d8c5b7d","last_reissued_at":"2026-07-05T01:17:22.361899Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:17:22.361899Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2007.04239","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T01:17:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IFtxlHTMcfvYwNFZ4PO6+OlyPxpLIXAMD8JV+P8CyNW6fVyxTMCPijvGbSorY1j5ABHJIW9A7CUOQspGJLOlAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T07:33:10.296113Z"},"content_sha256":"9c56bdabc29c42108a728ec4ec7ba6f1a1ef5d5a946fa6e7f9bc3ca5e7adf980","schema_version":"1.0","event_id":"sha256:9c56bdabc29c42108a728ec4ec7ba6f1a1ef5d5a946fa6e7f9bc3ca5e7adf980"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:HAU4ZNHVUC5CQB2UZK6RHB7VKV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey on Transfer Learning in Natural Language Processing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CL","authors_text":"Irfan Ahmad, Maged Saeed AlShaibani, Zaid Alyafeai","submitted_at":"2020-05-31T21:52:31Z","abstract_excerpt":"Deep learning models usually require a huge amount of data. However, these large datasets are not always attainable. This is common in many challenging NLP tasks. Consider Neural Machine Translation, for instance, where curating such large datasets may not be possible specially for low resource languages. Another limitation of deep learning models is the demand for huge computing resources. These obstacles motivate research to question the possibility of knowledge transfer using large trained models. The demand for transfer learning is increasing as many large models are emerging. In this surv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.04239","kind":"arxiv","version":1},"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/2007.04239/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":"2026-07-05T01:17:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IG4OxmJWKiEolW1HHwgLN6aqDM/Lqpm9GY0EiuD6mPbVGbTFNn997IHW9kvd+M64MEEKq/S/+PeCC0vOyu6gDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T07:33:10.296495Z"},"content_sha256":"436dd31b948cad566eace212c5e2745211b8ec2c0c8181d21cab2c5c6fa713d8","schema_version":"1.0","event_id":"sha256:436dd31b948cad566eace212c5e2745211b8ec2c0c8181d21cab2c5c6fa713d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/bundle.json","state_url":"https://pith.science/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/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":"2026-08-20T07:33:10Z","links":{"resolver":"https://pith.science/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV","bundle":"https://pith.science/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/bundle.json","state":"https://pith.science/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HAU4ZNHVUC5CQB2UZK6RHB7VKV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:HAU4ZNHVUC5CQB2UZK6RHB7VKV","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":"e17f1b31a65651d452610a01dd883059e53eadda78e10deb952a95e501981296","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-31T21:52:31Z","title_canon_sha256":"3a4490a8321baad0067e88b464204390d98d81daa3218544cd47fb46ecf0d509"},"schema_version":"1.0","source":{"id":"2007.04239","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2007.04239","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"arxiv_version","alias_value":"2007.04239v1","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.04239","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_12","alias_value":"HAU4ZNHVUC5C","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_16","alias_value":"HAU4ZNHVUC5CQB2U","created_at":"2026-07-05T01:17:22Z"},{"alias_kind":"pith_short_8","alias_value":"HAU4ZNHV","created_at":"2026-07-05T01:17:22Z"}],"graph_snapshots":[{"event_id":"sha256:436dd31b948cad566eace212c5e2745211b8ec2c0c8181d21cab2c5c6fa713d8","target":"graph","created_at":"2026-07-05T01:17:22Z","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/2007.04239/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning models usually require a huge amount of data. However, these large datasets are not always attainable. This is common in many challenging NLP tasks. Consider Neural Machine Translation, for instance, where curating such large datasets may not be possible specially for low resource languages. Another limitation of deep learning models is the demand for huge computing resources. These obstacles motivate research to question the possibility of knowledge transfer using large trained models. The demand for transfer learning is increasing as many large models are emerging. In this surv","authors_text":"Irfan Ahmad, Maged Saeed AlShaibani, Zaid Alyafeai","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-31T21:52:31Z","title":"A Survey on Transfer Learning in Natural Language Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.04239","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":"sha256:9c56bdabc29c42108a728ec4ec7ba6f1a1ef5d5a946fa6e7f9bc3ca5e7adf980","target":"record","created_at":"2026-07-05T01:17:22Z","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":"e17f1b31a65651d452610a01dd883059e53eadda78e10deb952a95e501981296","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-05-31T21:52:31Z","title_canon_sha256":"3a4490a8321baad0067e88b464204390d98d81daa3218544cd47fb46ecf0d509"},"schema_version":"1.0","source":{"id":"2007.04239","kind":"arxiv","version":1}},"canonical_sha256":"3829ccb4f5a0ba280754cabd1387f55552828878933f479e518fc4629d8c5b7d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3829ccb4f5a0ba280754cabd1387f55552828878933f479e518fc4629d8c5b7d","first_computed_at":"2026-07-05T01:17:22.361899Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:17:22.361899Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wfT2xSMF1CxBOt1a5hjrTdAkSSbibNgRQtdwsDtPWRu3Vy/54lBu9M//jLwANlp3m1rcAN2TGWoCAThmWY2FDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:17:22.362302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2007.04239","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c56bdabc29c42108a728ec4ec7ba6f1a1ef5d5a946fa6e7f9bc3ca5e7adf980","sha256:436dd31b948cad566eace212c5e2745211b8ec2c0c8181d21cab2c5c6fa713d8"],"state_sha256":"35d391c9cd5101ae7b681a2da41624305469caf4fca8ebc18db2f9c9b2da117c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"edDU6R+XhAidUQkMDxLCAuOwaRyl7HCQaB4sCKKIIVH3g8lSYcGOhxesOj1CWdAXof+F/hUqFesdui2FNF9iCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T07:33:10.298767Z","bundle_sha256":"e5fc2c14b23caf9343516446b035c94d8b00e5c48b3039c484a8401a71cfdbec"}}