{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:MXMNTKXYPDJ2EAT64BC6SAZOI3","short_pith_number":"pith:MXMNTKXY","canonical_record":{"source":{"id":"2212.09739","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-19T18:56:52Z","cross_cats_sorted":[],"title_canon_sha256":"83bebff6175c31f76840d47a0b934913f382ac25393a5f327f65228e5066d3e8","abstract_canon_sha256":"7ae0727adf92d04193e8fafc32882066de78039a0057b78e1e14faa0b26fa21d"},"schema_version":"1.0"},"canonical_sha256":"65d8d9aaf878d3a2027ee045e9032e46ee8ae968377f039bb969a600fd55797d","source":{"kind":"arxiv","id":"2212.09739","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.09739","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"arxiv_version","alias_value":"2212.09739v4","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.09739","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_12","alias_value":"MXMNTKXYPDJ2","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_16","alias_value":"MXMNTKXYPDJ2EAT6","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_8","alias_value":"MXMNTKXY","created_at":"2026-07-05T06:28:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:MXMNTKXYPDJ2EAT64BC6SAZOI3","target":"record","payload":{"canonical_record":{"source":{"id":"2212.09739","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-19T18:56:52Z","cross_cats_sorted":[],"title_canon_sha256":"83bebff6175c31f76840d47a0b934913f382ac25393a5f327f65228e5066d3e8","abstract_canon_sha256":"7ae0727adf92d04193e8fafc32882066de78039a0057b78e1e14faa0b26fa21d"},"schema_version":"1.0"},"canonical_sha256":"65d8d9aaf878d3a2027ee045e9032e46ee8ae968377f039bb969a600fd55797d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:28:47.356334Z","signature_b64":"tNL3R3vP9rO6NDn7wlnetFOGfYJuViNK01IW5q/ymPPFl7k+j5mc9vh1L/BPfWpLfAwqtt6jK7FTYElnw55iCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65d8d9aaf878d3a2027ee045e9032e46ee8ae968377f039bb969a600fd55797d","last_reissued_at":"2026-07-05T06:28:47.355797Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:28:47.355797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2212.09739","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:28:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"epLA61vxVhzOax+shHBhGULMRqZ21tf02hZ7tm7vKbIcT4WrA1bKmWaaOZZr2FgjW6qYZX9W9rDG+2K/QsHwAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:50:23.123910Z"},"content_sha256":"c211535c193b1632a2012eafce1ccf2d8b6d9d71c0029b1caefddc3a115aa8c2","schema_version":"1.0","event_id":"sha256:c211535c193b1632a2012eafce1ccf2d8b6d9d71c0029b1caefddc3a115aa8c2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:MXMNTKXYPDJ2EAT64BC6SAZOI3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LENS: A Learnable Evaluation Metric for Text Simplification","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"David Heineman, Mounica Maddela, Wei Xu, Yao Dou","submitted_at":"2022-12-19T18:56:52Z","abstract_excerpt":"Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human evaluation datasets for text simplification have limited annotations that are based on unitary or outdated models, making them unsuitable for this approach. To address these issues, we introduce the SimpEval corpus that contains: SimpEval_past, comprising 12K human ratings on 2.4K simplifications of 24 past systems, and SimpEval_2022, a challenging simplification benchmark consisting of over 1K human ratings of 360 simpl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.09739","kind":"arxiv","version":4},"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/2212.09739/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":"2026-07-05T06:28:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FmlKDNfnJ5b3WFanD4GfTDBOm7VoBu0CYnwKblLuZiVyC/W6FKzB43mghKv1pVY26yZ0MoytSzd7dDjoqzbNCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:50:23.124590Z"},"content_sha256":"b6de287d8c77c89badb0324f22aa3db55d3ad49c5b5dc95a74334cab71516696","schema_version":"1.0","event_id":"sha256:b6de287d8c77c89badb0324f22aa3db55d3ad49c5b5dc95a74334cab71516696"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/bundle.json","state_url":"https://pith.science/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/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":"2026-07-07T04:50:23Z","links":{"resolver":"https://pith.science/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3","bundle":"https://pith.science/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/bundle.json","state":"https://pith.science/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MXMNTKXYPDJ2EAT64BC6SAZOI3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:MXMNTKXYPDJ2EAT64BC6SAZOI3","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":"7ae0727adf92d04193e8fafc32882066de78039a0057b78e1e14faa0b26fa21d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-19T18:56:52Z","title_canon_sha256":"83bebff6175c31f76840d47a0b934913f382ac25393a5f327f65228e5066d3e8"},"schema_version":"1.0","source":{"id":"2212.09739","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.09739","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"arxiv_version","alias_value":"2212.09739v4","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.09739","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_12","alias_value":"MXMNTKXYPDJ2","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_16","alias_value":"MXMNTKXYPDJ2EAT6","created_at":"2026-07-05T06:28:47Z"},{"alias_kind":"pith_short_8","alias_value":"MXMNTKXY","created_at":"2026-07-05T06:28:47Z"}],"graph_snapshots":[{"event_id":"sha256:b6de287d8c77c89badb0324f22aa3db55d3ad49c5b5dc95a74334cab71516696","target":"graph","created_at":"2026-07-05T06:28:47Z","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/2212.09739/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training learnable metrics using modern language models has recently emerged as a promising method for the automatic evaluation of machine translation. However, existing human evaluation datasets for text simplification have limited annotations that are based on unitary or outdated models, making them unsuitable for this approach. To address these issues, we introduce the SimpEval corpus that contains: SimpEval_past, comprising 12K human ratings on 2.4K simplifications of 24 past systems, and SimpEval_2022, a challenging simplification benchmark consisting of over 1K human ratings of 360 simpl","authors_text":"David Heineman, Mounica Maddela, Wei Xu, Yao Dou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-19T18:56:52Z","title":"LENS: A Learnable Evaluation Metric for Text Simplification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.09739","kind":"arxiv","version":4},"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:c211535c193b1632a2012eafce1ccf2d8b6d9d71c0029b1caefddc3a115aa8c2","target":"record","created_at":"2026-07-05T06:28:47Z","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":"7ae0727adf92d04193e8fafc32882066de78039a0057b78e1e14faa0b26fa21d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-12-19T18:56:52Z","title_canon_sha256":"83bebff6175c31f76840d47a0b934913f382ac25393a5f327f65228e5066d3e8"},"schema_version":"1.0","source":{"id":"2212.09739","kind":"arxiv","version":4}},"canonical_sha256":"65d8d9aaf878d3a2027ee045e9032e46ee8ae968377f039bb969a600fd55797d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65d8d9aaf878d3a2027ee045e9032e46ee8ae968377f039bb969a600fd55797d","first_computed_at":"2026-07-05T06:28:47.355797Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:28:47.355797Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tNL3R3vP9rO6NDn7wlnetFOGfYJuViNK01IW5q/ymPPFl7k+j5mc9vh1L/BPfWpLfAwqtt6jK7FTYElnw55iCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:28:47.356334Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.09739","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c211535c193b1632a2012eafce1ccf2d8b6d9d71c0029b1caefddc3a115aa8c2","sha256:b6de287d8c77c89badb0324f22aa3db55d3ad49c5b5dc95a74334cab71516696"],"state_sha256":"57981b2c2156632d551b6548f1f01702db012f05736844c1e985a71a7a5fdfd3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BCQ2/w8RWgz/3cZVz63HvVrfk47iOaoZGlubKgEQA3HIE/OFoHa3aIG3Z+MDEct0n0Hf3Z/KDHwEvJe9oLskAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:50:23.129336Z","bundle_sha256":"48730f9b240fc3befecc5e542eb013b6fe36373fe74e12c0683e43e9de0864eb"}}