{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:5KRPAFRN4HGOGRQA6VYX4GHMSF","short_pith_number":"pith:5KRPAFRN","canonical_record":{"source":{"id":"2105.07623","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-17T06:03:56Z","cross_cats_sorted":[],"title_canon_sha256":"162125bd988c68ad30c4067acf498cca3c363c332b688e00fba0eda99cf17271","abstract_canon_sha256":"be9351c36b206cfac72e695bca5dfba9dccac9d27826ad4589710e7ec75ba152"},"schema_version":"1.0"},"canonical_sha256":"eaa2f0162de1cce34600f5717e18ec91590ee670ef1154f975707b7e9d5003ac","source":{"kind":"arxiv","id":"2105.07623","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07623","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07623v2","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07623","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_12","alias_value":"5KRPAFRN4HGO","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_16","alias_value":"5KRPAFRN4HGOGRQA","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_8","alias_value":"5KRPAFRN","created_at":"2026-07-05T03:52:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:5KRPAFRN4HGOGRQA6VYX4GHMSF","target":"record","payload":{"canonical_record":{"source":{"id":"2105.07623","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-17T06:03:56Z","cross_cats_sorted":[],"title_canon_sha256":"162125bd988c68ad30c4067acf498cca3c363c332b688e00fba0eda99cf17271","abstract_canon_sha256":"be9351c36b206cfac72e695bca5dfba9dccac9d27826ad4589710e7ec75ba152"},"schema_version":"1.0"},"canonical_sha256":"eaa2f0162de1cce34600f5717e18ec91590ee670ef1154f975707b7e9d5003ac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:52:28.343492Z","signature_b64":"ZhD5v9wR8SDnaozsA+IDZHcY10QKke4kjXJmKKr/MOTVc30EGt9kvhVVTJLZOulzEfb7Qc/u7qVlV/W9pHTTCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eaa2f0162de1cce34600f5717e18ec91590ee670ef1154f975707b7e9d5003ac","last_reissued_at":"2026-07-05T03:52:28.343000Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:52:28.343000Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.07623","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":"2026-07-05T03:52:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7Sx7hMTeMSDhpBUAKQHzlgTlH3CX6L+53bmB5OqjTu4u8Lhu6XO8KrK5iNHmmqM+29LHWo6InDdaEAImo07VCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T09:45:45.232403Z"},"content_sha256":"7f3d5b8adccd8c5844d21c7231aa9ef90ba51d7e42909c9ebb3219dcd91b7513","schema_version":"1.0","event_id":"sha256:7f3d5b8adccd8c5844d21c7231aa9ef90ba51d7e42909c9ebb3219dcd91b7513"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:5KRPAFRN4HGOGRQA6VYX4GHMSF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sentence Similarity Based on Contexts","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chun Fan, Fei Wu, Jiwei Li, Tianwei Zhang, Xiang Ao, Xiaofei Sun, Yuxian Meng","submitted_at":"2021-05-17T06:03:56Z","abstract_excerpt":"Existing methods to measure sentence similarity are faced with two challenges: (1) labeled datasets are usually limited in size, making them insufficient to train supervised neural models; (2) there is a training-test gap for unsupervised language modeling (LM) based models to compute semantic scores between sentences, since sentence-level semantics are not explicitly modeled at training. This results in inferior performances in this task. In this work, we propose a new framework to address these two issues. The proposed framework is based on the core idea that the meaning of a sentence should"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07623","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2105.07623/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":"2026-07-05T03:52:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y4voSrDWkfy5BGD7f1/hxZYnJEb6KuIYH7XfzpPidxU8o+KClEpmP9RjBHJyRyVJrTty+oZG7PrQyf1rmSSTAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-15T09:45:45.232997Z"},"content_sha256":"26d48f664b206da20d638d9cf7048d86c9bdf2319600be5b86d6dcb3f5231586","schema_version":"1.0","event_id":"sha256:26d48f664b206da20d638d9cf7048d86c9bdf2319600be5b86d6dcb3f5231586"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/bundle.json","state_url":"https://pith.science/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/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":"2026-08-15T09:45:45Z","links":{"resolver":"https://pith.science/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF","bundle":"https://pith.science/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/bundle.json","state":"https://pith.science/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5KRPAFRN4HGOGRQA6VYX4GHMSF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:5KRPAFRN4HGOGRQA6VYX4GHMSF","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":"be9351c36b206cfac72e695bca5dfba9dccac9d27826ad4589710e7ec75ba152","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-17T06:03:56Z","title_canon_sha256":"162125bd988c68ad30c4067acf498cca3c363c332b688e00fba0eda99cf17271"},"schema_version":"1.0","source":{"id":"2105.07623","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.07623","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"arxiv_version","alias_value":"2105.07623v2","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.07623","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_12","alias_value":"5KRPAFRN4HGO","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_16","alias_value":"5KRPAFRN4HGOGRQA","created_at":"2026-07-05T03:52:28Z"},{"alias_kind":"pith_short_8","alias_value":"5KRPAFRN","created_at":"2026-07-05T03:52:28Z"}],"graph_snapshots":[{"event_id":"sha256:26d48f664b206da20d638d9cf7048d86c9bdf2319600be5b86d6dcb3f5231586","target":"graph","created_at":"2026-07-05T03:52:28Z","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/2105.07623/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing methods to measure sentence similarity are faced with two challenges: (1) labeled datasets are usually limited in size, making them insufficient to train supervised neural models; (2) there is a training-test gap for unsupervised language modeling (LM) based models to compute semantic scores between sentences, since sentence-level semantics are not explicitly modeled at training. This results in inferior performances in this task. In this work, we propose a new framework to address these two issues. The proposed framework is based on the core idea that the meaning of a sentence should","authors_text":"Chun Fan, Fei Wu, Jiwei Li, Tianwei Zhang, Xiang Ao, Xiaofei Sun, Yuxian Meng","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-17T06:03:56Z","title":"Sentence Similarity Based on Contexts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.07623","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":"sha256:7f3d5b8adccd8c5844d21c7231aa9ef90ba51d7e42909c9ebb3219dcd91b7513","target":"record","created_at":"2026-07-05T03:52:28Z","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":"be9351c36b206cfac72e695bca5dfba9dccac9d27826ad4589710e7ec75ba152","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-17T06:03:56Z","title_canon_sha256":"162125bd988c68ad30c4067acf498cca3c363c332b688e00fba0eda99cf17271"},"schema_version":"1.0","source":{"id":"2105.07623","kind":"arxiv","version":2}},"canonical_sha256":"eaa2f0162de1cce34600f5717e18ec91590ee670ef1154f975707b7e9d5003ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eaa2f0162de1cce34600f5717e18ec91590ee670ef1154f975707b7e9d5003ac","first_computed_at":"2026-07-05T03:52:28.343000Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:52:28.343000Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZhD5v9wR8SDnaozsA+IDZHcY10QKke4kjXJmKKr/MOTVc30EGt9kvhVVTJLZOulzEfb7Qc/u7qVlV/W9pHTTCA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:52:28.343492Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.07623","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7f3d5b8adccd8c5844d21c7231aa9ef90ba51d7e42909c9ebb3219dcd91b7513","sha256:26d48f664b206da20d638d9cf7048d86c9bdf2319600be5b86d6dcb3f5231586"],"state_sha256":"6270c4ce96fa00fa96900d7a49de90b7acc549059fd7a074090938788c5d4d3d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0fsTzxpSRQmJpKE29+mLF6OpGhTbzvHanOF2GwFubH1f9g14YyJVfsaG4thP0ckTdu4VOcLF7l4B264A0kUAAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-15T09:45:45.238498Z","bundle_sha256":"d2bff2427f213419cc2352cf381f5d49d6050201429bd3e1c85c0ed054aedbd0"}}