{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:2IGAMTBSTR4KZL4JEZSEYB36PC","short_pith_number":"pith:2IGAMTBS","canonical_record":{"source":{"id":"1705.00557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-23T09:15:35Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"bee64ae7f15e26e80a075ca6e009429139e4efdb9bf6f16bfe2c835f6346b4fc","abstract_canon_sha256":"ddf18a89117ea112672aba9e560d4e785d1b47c4e95020d66d3218e4e3615952"},"schema_version":"1.0"},"canonical_sha256":"d20c064c329c78acaf8926644c077e78abd046d2152c3776da5e08be78218af5","source":{"kind":"arxiv","id":"1705.00557","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.00557","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"arxiv_version","alias_value":"1705.00557v1","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.00557","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"pith_short_12","alias_value":"2IGAMTBSTR4K","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2IGAMTBSTR4KZL4J","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2IGAMTBS","created_at":"2026-05-18T12:30:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:2IGAMTBSTR4KZL4JEZSEYB36PC","target":"record","payload":{"canonical_record":{"source":{"id":"1705.00557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-23T09:15:35Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"bee64ae7f15e26e80a075ca6e009429139e4efdb9bf6f16bfe2c835f6346b4fc","abstract_canon_sha256":"ddf18a89117ea112672aba9e560d4e785d1b47c4e95020d66d3218e4e3615952"},"schema_version":"1.0"},"canonical_sha256":"d20c064c329c78acaf8926644c077e78abd046d2152c3776da5e08be78218af5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:45:16.894882Z","signature_b64":"yn7RRI+utYQ8rtgRMUZUbRfgSAwYrFyav7PjzWb2AWwLenKtPLQ/BG+LFoWuDHOyceAJeUirDbI32+nY5FQTBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d20c064c329c78acaf8926644c077e78abd046d2152c3776da5e08be78218af5","last_reissued_at":"2026-05-18T00:45:16.894194Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:45:16.894194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1705.00557","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":"2026-05-18T00:45:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iFXtSzinpXFQfltISVLUShG4kOLmMP7cnV924FgPXtf4ulrbyOTwOjnIH/oz9LtgTS6Px1yEfU1iENyw/vLECQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T01:59:11.528164Z"},"content_sha256":"4c1b68904f567eba58893db634563ddb6bdf3077dc92bcd0174da7949cf87951","schema_version":"1.0","event_id":"sha256:4c1b68904f567eba58893db634563ddb6bdf3077dc92bcd0174da7949cf87951"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:2IGAMTBSTR4KZL4JEZSEYB36PC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE","stat.ML"],"primary_cat":"cs.CL","authors_text":"David Sontag, Samuel R. Bowman, Yacine Jernite","submitted_at":"2017-04-23T09:15:35Z","abstract_excerpt":"This work presents a novel objective function for the unsupervised training of neural network sentence encoders. It exploits signals from paragraph-level discourse coherence to train these models to understand text. Our objective is purely discriminative, allowing us to train models many times faster than was possible under prior methods, and it yields models which perform well in extrinsic evaluations."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.00557","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":""},"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":"2026-05-18T00:45:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fu29JEwTYQaNNLJsyyJRkaMlgMQ9YH73HpqHtjwJdBstpiQ9tsbfUIjKUUV2znOmf7zJzZIiwxOqX/464g4DDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T01:59:11.528546Z"},"content_sha256":"d8aecf5bd9d1be4716674bd50719c92ad55df513e57ef10ac9d9843eef559096","schema_version":"1.0","event_id":"sha256:d8aecf5bd9d1be4716674bd50719c92ad55df513e57ef10ac9d9843eef559096"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/bundle.json","state_url":"https://pith.science/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/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":"2026-05-28T01:59:11Z","links":{"resolver":"https://pith.science/pith/2IGAMTBSTR4KZL4JEZSEYB36PC","bundle":"https://pith.science/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/bundle.json","state":"https://pith.science/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2IGAMTBSTR4KZL4JEZSEYB36PC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:2IGAMTBSTR4KZL4JEZSEYB36PC","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":"ddf18a89117ea112672aba9e560d4e785d1b47c4e95020d66d3218e4e3615952","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-23T09:15:35Z","title_canon_sha256":"bee64ae7f15e26e80a075ca6e009429139e4efdb9bf6f16bfe2c835f6346b4fc"},"schema_version":"1.0","source":{"id":"1705.00557","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1705.00557","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"arxiv_version","alias_value":"1705.00557v1","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1705.00557","created_at":"2026-05-18T00:45:16Z"},{"alias_kind":"pith_short_12","alias_value":"2IGAMTBSTR4K","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_16","alias_value":"2IGAMTBSTR4KZL4J","created_at":"2026-05-18T12:30:55Z"},{"alias_kind":"pith_short_8","alias_value":"2IGAMTBS","created_at":"2026-05-18T12:30:55Z"}],"graph_snapshots":[{"event_id":"sha256:d8aecf5bd9d1be4716674bd50719c92ad55df513e57ef10ac9d9843eef559096","target":"graph","created_at":"2026-05-18T00:45:16Z","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":"This work presents a novel objective function for the unsupervised training of neural network sentence encoders. It exploits signals from paragraph-level discourse coherence to train these models to understand text. Our objective is purely discriminative, allowing us to train models many times faster than was possible under prior methods, and it yields models which perform well in extrinsic evaluations.","authors_text":"David Sontag, Samuel R. Bowman, Yacine Jernite","cross_cats":["cs.LG","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-23T09:15:35Z","title":"Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1705.00557","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":"sha256:4c1b68904f567eba58893db634563ddb6bdf3077dc92bcd0174da7949cf87951","target":"record","created_at":"2026-05-18T00:45:16Z","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":"ddf18a89117ea112672aba9e560d4e785d1b47c4e95020d66d3218e4e3615952","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-23T09:15:35Z","title_canon_sha256":"bee64ae7f15e26e80a075ca6e009429139e4efdb9bf6f16bfe2c835f6346b4fc"},"schema_version":"1.0","source":{"id":"1705.00557","kind":"arxiv","version":1}},"canonical_sha256":"d20c064c329c78acaf8926644c077e78abd046d2152c3776da5e08be78218af5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d20c064c329c78acaf8926644c077e78abd046d2152c3776da5e08be78218af5","first_computed_at":"2026-05-18T00:45:16.894194Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:45:16.894194Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yn7RRI+utYQ8rtgRMUZUbRfgSAwYrFyav7PjzWb2AWwLenKtPLQ/BG+LFoWuDHOyceAJeUirDbI32+nY5FQTBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:45:16.894882Z","signed_message":"canonical_sha256_bytes"},"source_id":"1705.00557","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4c1b68904f567eba58893db634563ddb6bdf3077dc92bcd0174da7949cf87951","sha256:d8aecf5bd9d1be4716674bd50719c92ad55df513e57ef10ac9d9843eef559096"],"state_sha256":"adc3cdad85ae4e72e6e14e7e51f8a3ec2850447f95a184498027384ae61abca4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v2i7HfPG4MuxDDMDjXKN8zzG5xba6BwVbdcJvLtLdfzH1sjmz/kSmSTKfBBfQg+2inHVZ3lkkQ/hD8Rx7YkYCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T01:59:11.530469Z","bundle_sha256":"a654db1b87bc6ff0f568b2cfd3d14bd13b3c1a0c58035271a53954c7fed7e05e"}}