{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:FZSSMG3742BZM4WNKBPJENQUZL","short_pith_number":"pith:FZSSMG37","canonical_record":{"source":{"id":"2010.10673","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-20T23:45:04Z","cross_cats_sorted":[],"title_canon_sha256":"d9c966ba4825d14297693c122ae313c024da9f864c09501ae9cde155d8d3372c","abstract_canon_sha256":"2883d3f7719a6badf7474538532a8248e967cf6a3af9cc4b194a4018ecac223f"},"schema_version":"1.0"},"canonical_sha256":"2e65261b7fe6839672cd505e923614cad7c11bf876bbf1279a5a3f13796abd0b","source":{"kind":"arxiv","id":"2010.10673","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10673","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10673v1","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10673","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_12","alias_value":"FZSSMG3742BZ","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_16","alias_value":"FZSSMG3742BZM4WN","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_8","alias_value":"FZSSMG37","created_at":"2026-07-05T01:44:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:FZSSMG3742BZM4WNKBPJENQUZL","target":"record","payload":{"canonical_record":{"source":{"id":"2010.10673","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-20T23:45:04Z","cross_cats_sorted":[],"title_canon_sha256":"d9c966ba4825d14297693c122ae313c024da9f864c09501ae9cde155d8d3372c","abstract_canon_sha256":"2883d3f7719a6badf7474538532a8248e967cf6a3af9cc4b194a4018ecac223f"},"schema_version":"1.0"},"canonical_sha256":"2e65261b7fe6839672cd505e923614cad7c11bf876bbf1279a5a3f13796abd0b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:44:53.415308Z","signature_b64":"T5wZlhl7IflTaYy8tNoSu+8RpgZQxUuMjar05piVylwy9iig/OO1qDe3Cr2Mjafn0RkSGJEekjsfOwd1ExPxDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2e65261b7fe6839672cd505e923614cad7c11bf876bbf1279a5a3f13796abd0b","last_reissued_at":"2026-07-05T01:44:53.414954Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:44:53.414954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.10673","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":"2026-07-05T01:44:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ld5Di8DyN4Qaw02Mf65IFrFZSbGv4U8oO2Mv3sRgY2f7uNqeykhSqXvoNnToIqzDRUIPvF1H2ndctD0Da8UyBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:15:54.450470Z"},"content_sha256":"7c885225da72647030c880822b23620cc29b1ee4ab5016b1ade6586aee6420dc","schema_version":"1.0","event_id":"sha256:7c885225da72647030c880822b23620cc29b1ee4ab5016b1ade6586aee6420dc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:FZSSMG3742BZM4WNKBPJENQUZL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pushing the Limits of AMR Parsing with Self-Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Radu Florian, Ramon Fernandez Astudillo, Revanth Gangi Reddy, Salim Roukos, Tahira Naseem, Young-Suk Lee","submitted_at":"2020-10-20T23:45:04Z","abstract_excerpt":"Abstract Meaning Representation (AMR) parsing has experienced a notable growth in performance in the last two years, due both to the impact of transfer learning and the development of novel architectures specific to AMR. At the same time, self-learning techniques have helped push the performance boundaries of other natural language processing applications, such as machine translation or question answering. In this paper, we explore different ways in which trained models can be applied to improve AMR parsing performance, including generation of synthetic text and AMR annotations as well as refi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10673","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2010.10673/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":"2026-07-05T01:44:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"48cU5BUT9cX9SfpfgCh8v807J+heBhYzo0F0u507vzvjPwF07Z8UJuylAcXO9NInZi7PjZDi+iLf2lpnn5alCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T07:15:54.451184Z"},"content_sha256":"490fa95dfe8d7d19be5b43e0286ec77f4975311bbe05c02097798752075a2240","schema_version":"1.0","event_id":"sha256:490fa95dfe8d7d19be5b43e0286ec77f4975311bbe05c02097798752075a2240"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FZSSMG3742BZM4WNKBPJENQUZL/bundle.json","state_url":"https://pith.science/pith/FZSSMG3742BZM4WNKBPJENQUZL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FZSSMG3742BZM4WNKBPJENQUZL/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":"2026-07-07T07:15:54Z","links":{"resolver":"https://pith.science/pith/FZSSMG3742BZM4WNKBPJENQUZL","bundle":"https://pith.science/pith/FZSSMG3742BZM4WNKBPJENQUZL/bundle.json","state":"https://pith.science/pith/FZSSMG3742BZM4WNKBPJENQUZL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FZSSMG3742BZM4WNKBPJENQUZL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:FZSSMG3742BZM4WNKBPJENQUZL","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":"2883d3f7719a6badf7474538532a8248e967cf6a3af9cc4b194a4018ecac223f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-20T23:45:04Z","title_canon_sha256":"d9c966ba4825d14297693c122ae313c024da9f864c09501ae9cde155d8d3372c"},"schema_version":"1.0","source":{"id":"2010.10673","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.10673","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"arxiv_version","alias_value":"2010.10673v1","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.10673","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_12","alias_value":"FZSSMG3742BZ","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_16","alias_value":"FZSSMG3742BZM4WN","created_at":"2026-07-05T01:44:53Z"},{"alias_kind":"pith_short_8","alias_value":"FZSSMG37","created_at":"2026-07-05T01:44:53Z"}],"graph_snapshots":[{"event_id":"sha256:490fa95dfe8d7d19be5b43e0286ec77f4975311bbe05c02097798752075a2240","target":"graph","created_at":"2026-07-05T01:44:53Z","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/2010.10673/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Abstract Meaning Representation (AMR) parsing has experienced a notable growth in performance in the last two years, due both to the impact of transfer learning and the development of novel architectures specific to AMR. At the same time, self-learning techniques have helped push the performance boundaries of other natural language processing applications, such as machine translation or question answering. In this paper, we explore different ways in which trained models can be applied to improve AMR parsing performance, including generation of synthetic text and AMR annotations as well as refi","authors_text":"Radu Florian, Ramon Fernandez Astudillo, Revanth Gangi Reddy, Salim Roukos, Tahira Naseem, Young-Suk Lee","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-20T23:45:04Z","title":"Pushing the Limits of AMR Parsing with Self-Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.10673","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":"sha256:7c885225da72647030c880822b23620cc29b1ee4ab5016b1ade6586aee6420dc","target":"record","created_at":"2026-07-05T01:44:53Z","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":"2883d3f7719a6badf7474538532a8248e967cf6a3af9cc4b194a4018ecac223f","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-20T23:45:04Z","title_canon_sha256":"d9c966ba4825d14297693c122ae313c024da9f864c09501ae9cde155d8d3372c"},"schema_version":"1.0","source":{"id":"2010.10673","kind":"arxiv","version":1}},"canonical_sha256":"2e65261b7fe6839672cd505e923614cad7c11bf876bbf1279a5a3f13796abd0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e65261b7fe6839672cd505e923614cad7c11bf876bbf1279a5a3f13796abd0b","first_computed_at":"2026-07-05T01:44:53.414954Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:44:53.414954Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"T5wZlhl7IflTaYy8tNoSu+8RpgZQxUuMjar05piVylwy9iig/OO1qDe3Cr2Mjafn0RkSGJEekjsfOwd1ExPxDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:44:53.415308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.10673","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c885225da72647030c880822b23620cc29b1ee4ab5016b1ade6586aee6420dc","sha256:490fa95dfe8d7d19be5b43e0286ec77f4975311bbe05c02097798752075a2240"],"state_sha256":"a97f731b834db054dc958af1fcd0c03c0d5766f761d1906caab0f2522ece23da"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R8lMHTIfnhiRjDAZPQD4OMlzZduAcg+cwIh4t5cuFK0jMilq9idjxNtbQPB0URotaYITessY8gt5X4mRM3keAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T07:15:54.454529Z","bundle_sha256":"da14523e467aaff31da7aa6dfe306ccc4422f0bb65fbc09760a64238ca20e654"}}