{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:AW4D6UXA3QHIVOAHQWVOGDLLIX","short_pith_number":"pith:AW4D6UXA","canonical_record":{"source":{"id":"1707.06799","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T08:36:31Z","cross_cats_sorted":[],"title_canon_sha256":"c056b6ebbd7515721980c8dd756a52801ba5a77dbe787db10690cab861a114c8","abstract_canon_sha256":"5e3766abc1dce2fd8d7dd8aa043bb1c285456a138b8973e2ce265e3b3c971bd0"},"schema_version":"1.0"},"canonical_sha256":"05b83f52e0dc0e8ab80785aae30d6b45e4f81a144ff2d10187aea8efb0aced33","source":{"kind":"arxiv","id":"1707.06799","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06799","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06799v2","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06799","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"pith_short_12","alias_value":"AW4D6UXA3QHI","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"AW4D6UXA3QHIVOAH","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"AW4D6UXA","created_at":"2026-05-18T12:31:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:AW4D6UXA3QHIVOAHQWVOGDLLIX","target":"record","payload":{"canonical_record":{"source":{"id":"1707.06799","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T08:36:31Z","cross_cats_sorted":[],"title_canon_sha256":"c056b6ebbd7515721980c8dd756a52801ba5a77dbe787db10690cab861a114c8","abstract_canon_sha256":"5e3766abc1dce2fd8d7dd8aa043bb1c285456a138b8973e2ce265e3b3c971bd0"},"schema_version":"1.0"},"canonical_sha256":"05b83f52e0dc0e8ab80785aae30d6b45e4f81a144ff2d10187aea8efb0aced33","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:37:57.383388Z","signature_b64":"dGtzOzUVXXoheT03WQPNf8ihGAmAo+BbIlJEgMB616hA4lOucr45oGGpl1NPGrWrMTdm1r4c3P496vSGyZ3AAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05b83f52e0dc0e8ab80785aae30d6b45e4f81a144ff2d10187aea8efb0aced33","last_reissued_at":"2026-05-18T00:37:57.382876Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:37:57.382876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.06799","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":"2026-05-18T00:37:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+0oqK3pziCMHu5nBoH/snxCz0G9F05H9tVc//7NOnsjG2X2qBFgllqFM2DeWmRNSqdjH8EpLyDNJrbq6oKuSAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:20:28.936482Z"},"content_sha256":"9c250c95ed5bd8ad376a67c31e766fef597c3f989abca8a7eea24143e1477c63","schema_version":"1.0","event_id":"sha256:9c250c95ed5bd8ad376a67c31e766fef597c3f989abca8a7eea24143e1477c63"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:AW4D6UXA3QHIVOAHQWVOGDLLIX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Iryna Gurevych, Nils Reimers","submitted_at":"2017-07-21T08:36:31Z","abstract_excerpt":"Selecting optimal parameters for a neural network architecture can often make the difference between mediocre and state-of-the-art performance. However, little is published which parameters and design choices should be evaluated or selected making the correct hyperparameter optimization often a \"black art that requires expert experiences\" (Snoek et al., 2012). In this paper, we evaluate the importance of different network design choices and hyperparameters for five common linguistic sequence tagging tasks (POS, Chunking, NER, Entity Recognition, and Event Detection). We evaluated over 50.000 d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06799","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":"2026-05-18T00:37:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PWXpJkuYCbSclW3WWCFBTBIS0LHrHSSOE5ZCw2MafV1DBgzsdzW93o9bb7AuFSK6B1fJqlG2CIrhACcSGWFwAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:20:28.936827Z"},"content_sha256":"f4edef717d08d95a72e29262cee6e107287e475bc4859533f7c3077127fe3cff","schema_version":"1.0","event_id":"sha256:f4edef717d08d95a72e29262cee6e107287e475bc4859533f7c3077127fe3cff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/bundle.json","state_url":"https://pith.science/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/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":"2026-06-02T14:20:28Z","links":{"resolver":"https://pith.science/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX","bundle":"https://pith.science/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/bundle.json","state":"https://pith.science/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AW4D6UXA3QHIVOAHQWVOGDLLIX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:AW4D6UXA3QHIVOAHQWVOGDLLIX","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":"5e3766abc1dce2fd8d7dd8aa043bb1c285456a138b8973e2ce265e3b3c971bd0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T08:36:31Z","title_canon_sha256":"c056b6ebbd7515721980c8dd756a52801ba5a77dbe787db10690cab861a114c8"},"schema_version":"1.0","source":{"id":"1707.06799","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06799","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06799v2","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06799","created_at":"2026-05-18T00:37:57Z"},{"alias_kind":"pith_short_12","alias_value":"AW4D6UXA3QHI","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_16","alias_value":"AW4D6UXA3QHIVOAH","created_at":"2026-05-18T12:31:08Z"},{"alias_kind":"pith_short_8","alias_value":"AW4D6UXA","created_at":"2026-05-18T12:31:08Z"}],"graph_snapshots":[{"event_id":"sha256:f4edef717d08d95a72e29262cee6e107287e475bc4859533f7c3077127fe3cff","target":"graph","created_at":"2026-05-18T00:37:57Z","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":"Selecting optimal parameters for a neural network architecture can often make the difference between mediocre and state-of-the-art performance. However, little is published which parameters and design choices should be evaluated or selected making the correct hyperparameter optimization often a \"black art that requires expert experiences\" (Snoek et al., 2012). In this paper, we evaluate the importance of different network design choices and hyperparameters for five common linguistic sequence tagging tasks (POS, Chunking, NER, Entity Recognition, and Event Detection). We evaluated over 50.000 d","authors_text":"Iryna Gurevych, Nils Reimers","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T08:36:31Z","title":"Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06799","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":"sha256:9c250c95ed5bd8ad376a67c31e766fef597c3f989abca8a7eea24143e1477c63","target":"record","created_at":"2026-05-18T00:37:57Z","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":"5e3766abc1dce2fd8d7dd8aa043bb1c285456a138b8973e2ce265e3b3c971bd0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2017-07-21T08:36:31Z","title_canon_sha256":"c056b6ebbd7515721980c8dd756a52801ba5a77dbe787db10690cab861a114c8"},"schema_version":"1.0","source":{"id":"1707.06799","kind":"arxiv","version":2}},"canonical_sha256":"05b83f52e0dc0e8ab80785aae30d6b45e4f81a144ff2d10187aea8efb0aced33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"05b83f52e0dc0e8ab80785aae30d6b45e4f81a144ff2d10187aea8efb0aced33","first_computed_at":"2026-05-18T00:37:57.382876Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:37:57.382876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dGtzOzUVXXoheT03WQPNf8ihGAmAo+BbIlJEgMB616hA4lOucr45oGGpl1NPGrWrMTdm1r4c3P496vSGyZ3AAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:37:57.383388Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.06799","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c250c95ed5bd8ad376a67c31e766fef597c3f989abca8a7eea24143e1477c63","sha256:f4edef717d08d95a72e29262cee6e107287e475bc4859533f7c3077127fe3cff"],"state_sha256":"3479e5f444935f27d714a19a82623a96c695a491666ab047a37c5ab5169bb88b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K44imrzvXUgANc/bPvACOfX7O8Ep6rjU7V7ZpxGPScSiVvanWaFuh+VEdLjVL8GfVpoOZoOTn2tjIO2a8305Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T14:20:28.939000Z","bundle_sha256":"56eb75e40fa3b6707ece11e3999ae61cde386f5643967d44a665fa319e00f7a0"}}