{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:R7FZFFFHGXUMI3FKFXA3WIDZK7","short_pith_number":"pith:R7FZFFFH","canonical_record":{"source":{"id":"1608.02689","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-09T04:38:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9abbb3540789f4fafb71117efa95531dbb2a2d1d99f30b3bf8919b9379ae4061","abstract_canon_sha256":"a9387584250d5a6e0c07193c5f0949da48b122bac86130e497947afc62d45560"},"schema_version":"1.0"},"canonical_sha256":"8fcb9294a735e8c46caa2dc1bb207957c7dfc6369b6f41512a62ab3733a9818b","source":{"kind":"arxiv","id":"1608.02689","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.02689","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"arxiv_version","alias_value":"1608.02689v2","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.02689","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"pith_short_12","alias_value":"R7FZFFFHGXUM","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"R7FZFFFHGXUMI3FK","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"R7FZFFFH","created_at":"2026-05-18T12:30:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:R7FZFFFHGXUMI3FKFXA3WIDZK7","target":"record","payload":{"canonical_record":{"source":{"id":"1608.02689","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-09T04:38:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"9abbb3540789f4fafb71117efa95531dbb2a2d1d99f30b3bf8919b9379ae4061","abstract_canon_sha256":"a9387584250d5a6e0c07193c5f0949da48b122bac86130e497947afc62d45560"},"schema_version":"1.0"},"canonical_sha256":"8fcb9294a735e8c46caa2dc1bb207957c7dfc6369b6f41512a62ab3733a9818b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:30.520130Z","signature_b64":"Vhh/GyoiLkgPrGgdrsQU8BHFYDSEEIu9rYdYTXZTd2l8Raru0Jr1Fb69GBwljaIyeRFiaFpGzYDI1P2x99Z8DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8fcb9294a735e8c46caa2dc1bb207957c7dfc6369b6f41512a62ab3733a9818b","last_reissued_at":"2026-05-18T00:43:30.519671Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:30.519671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1608.02689","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":"2026-05-18T00:43:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X5O33Tc95l7Rgitenjy68m4SgeGrnbar42pGJoNndl0x71aZn3Xh6kPkmbGgmv+ODwBuO94ifawVvqAIJaPpCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T08:12:19.317696Z"},"content_sha256":"b12b434867be628687109d0b69b50d0eb93bc027e84d437993ba0f92b05a3731","schema_version":"1.0","event_id":"sha256:b12b434867be628687109d0b69b50d0eb93bc027e84d437993ba0f92b05a3731"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:R7FZFFFHGXUMI3FKFXA3WIDZK7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-task Domain Adaptation for Sequence Tagging","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Mark Dredze, Nanyun Peng","submitted_at":"2016-08-09T04:38:38Z","abstract_excerpt":"Many domain adaptation approaches rely on learning cross domain shared representations to transfer the knowledge learned in one domain to other domains. Traditional domain adaptation only considers adapting for one task. In this paper, we explore multi-task representation learning under the domain adaptation scenario. We propose a neural network framework that supports domain adaptation for multiple tasks simultaneously, and learns shared representations that better generalize for domain adaptation. We apply the proposed framework to domain adaptation for sequence tagging problems considering "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.02689","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":""},"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":"2026-05-18T00:43:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HRQpyeRi6rCQHb9XR2n4ChemlYsdjXHOrMOAZHH5EDfMVu0MYrgTWWWN2qsv4av4nRahqbze06LUTfgrSdZcBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T08:12:19.318400Z"},"content_sha256":"dc41b1588529abaccc6c192c796ca596abbca03f603c0c6bdf422b509b762822","schema_version":"1.0","event_id":"sha256:dc41b1588529abaccc6c192c796ca596abbca03f603c0c6bdf422b509b762822"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/bundle.json","state_url":"https://pith.science/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/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":"2026-06-06T08:12:19Z","links":{"resolver":"https://pith.science/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7","bundle":"https://pith.science/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/bundle.json","state":"https://pith.science/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R7FZFFFHGXUMI3FKFXA3WIDZK7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:R7FZFFFHGXUMI3FKFXA3WIDZK7","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":"a9387584250d5a6e0c07193c5f0949da48b122bac86130e497947afc62d45560","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-09T04:38:38Z","title_canon_sha256":"9abbb3540789f4fafb71117efa95531dbb2a2d1d99f30b3bf8919b9379ae4061"},"schema_version":"1.0","source":{"id":"1608.02689","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1608.02689","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"arxiv_version","alias_value":"1608.02689v2","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1608.02689","created_at":"2026-05-18T00:43:30Z"},{"alias_kind":"pith_short_12","alias_value":"R7FZFFFHGXUM","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_16","alias_value":"R7FZFFFHGXUMI3FK","created_at":"2026-05-18T12:30:41Z"},{"alias_kind":"pith_short_8","alias_value":"R7FZFFFH","created_at":"2026-05-18T12:30:41Z"}],"graph_snapshots":[{"event_id":"sha256:dc41b1588529abaccc6c192c796ca596abbca03f603c0c6bdf422b509b762822","target":"graph","created_at":"2026-05-18T00:43:30Z","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"},"paper":{"abstract_excerpt":"Many domain adaptation approaches rely on learning cross domain shared representations to transfer the knowledge learned in one domain to other domains. Traditional domain adaptation only considers adapting for one task. In this paper, we explore multi-task representation learning under the domain adaptation scenario. We propose a neural network framework that supports domain adaptation for multiple tasks simultaneously, and learns shared representations that better generalize for domain adaptation. We apply the proposed framework to domain adaptation for sequence tagging problems considering ","authors_text":"Mark Dredze, Nanyun Peng","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-09T04:38:38Z","title":"Multi-task Domain Adaptation for Sequence Tagging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1608.02689","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:b12b434867be628687109d0b69b50d0eb93bc027e84d437993ba0f92b05a3731","target":"record","created_at":"2026-05-18T00:43:30Z","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":"a9387584250d5a6e0c07193c5f0949da48b122bac86130e497947afc62d45560","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-08-09T04:38:38Z","title_canon_sha256":"9abbb3540789f4fafb71117efa95531dbb2a2d1d99f30b3bf8919b9379ae4061"},"schema_version":"1.0","source":{"id":"1608.02689","kind":"arxiv","version":2}},"canonical_sha256":"8fcb9294a735e8c46caa2dc1bb207957c7dfc6369b6f41512a62ab3733a9818b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8fcb9294a735e8c46caa2dc1bb207957c7dfc6369b6f41512a62ab3733a9818b","first_computed_at":"2026-05-18T00:43:30.519671Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:43:30.519671Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vhh/GyoiLkgPrGgdrsQU8BHFYDSEEIu9rYdYTXZTd2l8Raru0Jr1Fb69GBwljaIyeRFiaFpGzYDI1P2x99Z8DA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:43:30.520130Z","signed_message":"canonical_sha256_bytes"},"source_id":"1608.02689","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b12b434867be628687109d0b69b50d0eb93bc027e84d437993ba0f92b05a3731","sha256:dc41b1588529abaccc6c192c796ca596abbca03f603c0c6bdf422b509b762822"],"state_sha256":"8537c20c844764cc6d78947d134ef7548dc55b16ca18c9fd94adcd42a7aa1b12"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5hRIqaMJ4lChZYXKaT1njJQVWy9PdWkNHaIUmGfQ6afVeMJmPTJlb9+hgoNZNs8LbPJkC4/4Agn0PpxCMJ+nCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T08:12:19.322332Z","bundle_sha256":"84dd07c161fac14c43a15083d28a8103c549d9cc89a3b1af15b80716fa58208f"}}