{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HQ555QBHF7DADFAMSBLUTHMZNP","short_pith_number":"pith:HQ555QBH","canonical_record":{"source":{"id":"1811.12239","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-11-29T15:20:30Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"e35593a99516c9cfb8866c8a924e2be688e34de664d7465ce3c1bac676084102","abstract_canon_sha256":"c32d6ab1c594913d8587d8c41c9f55e83dd34457c47763ba33f356533ab3d24a"},"schema_version":"1.0"},"canonical_sha256":"3c3bdec0272fc601940c9057499d996bc27f74e521663a856f3dee37c6ba8f36","source":{"kind":"arxiv","id":"1811.12239","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12239","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12239v1","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12239","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"HQ555QBHF7DA","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HQ555QBHF7DADFAM","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HQ555QBH","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HQ555QBHF7DADFAMSBLUTHMZNP","target":"record","payload":{"canonical_record":{"source":{"id":"1811.12239","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-11-29T15:20:30Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"e35593a99516c9cfb8866c8a924e2be688e34de664d7465ce3c1bac676084102","abstract_canon_sha256":"c32d6ab1c594913d8587d8c41c9f55e83dd34457c47763ba33f356533ab3d24a"},"schema_version":"1.0"},"canonical_sha256":"3c3bdec0272fc601940c9057499d996bc27f74e521663a856f3dee37c6ba8f36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:59:33.953820Z","signature_b64":"6M9IukfkjADUIwVaRE3RJX79G5Zeayr7KoEQyzPlnsCWxZWTaUn7WVgccWePJd+SQjVCP8/XnI5lF5gQSYUrAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3c3bdec0272fc601940c9057499d996bc27f74e521663a856f3dee37c6ba8f36","last_reissued_at":"2026-05-17T23:59:33.953096Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:59:33.953096Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.12239","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":"2026-05-17T23:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O0QcbGQO5yEsR4PVvjxelhaa5OuGgjzYaTLrMagfACVFB23+sw9wSTRlczBYnZj48mg5TRKsYGgr0nM5iSlXCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T16:44:38.149110Z"},"content_sha256":"3a167bbb2d82d46fdab52098b044960ce7062d3760abc861576fccd942757ed6","schema_version":"1.0","event_id":"sha256:3a167bbb2d82d46fdab52098b044960ce7062d3760abc861576fccd942757ed6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HQ555QBHF7DADFAMSBLUTHMZNP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CL","authors_text":"Carolin Lawrence, Stefan Riezler","submitted_at":"2018-11-29T15:20:30Z","abstract_excerpt":"In semantic parsing for question-answering, it is often too expensive to collect gold parses or even gold answers as supervision signals. We propose to convert model outputs into a set of human-understandable statements which allow non-expert users to act as proofreaders, providing error markings as learning signals to the parser. Because model outputs were suggested by a historic system, we operate in a counterfactual, or off-policy, learning setup. We introduce new estimators which can effectively leverage the given feedback and which avoid known degeneracies in counterfactual learning, whil"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12239","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":"2026-05-17T23:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"G5CcFKuBaezjHOfNexy5X6ort6oKSf1WBz8yZ9zVI8HB+YglJtlWIrVnBcGQ2nOPzb9o2gJhl+hHxO/8znKVCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T16:44:38.149872Z"},"content_sha256":"52dff95b2f3f90cdf88978328d32bb41cc097905a65f766e749447060f914231","schema_version":"1.0","event_id":"sha256:52dff95b2f3f90cdf88978328d32bb41cc097905a65f766e749447060f914231"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HQ555QBHF7DADFAMSBLUTHMZNP/bundle.json","state_url":"https://pith.science/pith/HQ555QBHF7DADFAMSBLUTHMZNP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HQ555QBHF7DADFAMSBLUTHMZNP/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":"2026-06-08T16:44:38Z","links":{"resolver":"https://pith.science/pith/HQ555QBHF7DADFAMSBLUTHMZNP","bundle":"https://pith.science/pith/HQ555QBHF7DADFAMSBLUTHMZNP/bundle.json","state":"https://pith.science/pith/HQ555QBHF7DADFAMSBLUTHMZNP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HQ555QBHF7DADFAMSBLUTHMZNP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HQ555QBHF7DADFAMSBLUTHMZNP","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":"c32d6ab1c594913d8587d8c41c9f55e83dd34457c47763ba33f356533ab3d24a","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-11-29T15:20:30Z","title_canon_sha256":"e35593a99516c9cfb8866c8a924e2be688e34de664d7465ce3c1bac676084102"},"schema_version":"1.0","source":{"id":"1811.12239","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.12239","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"1811.12239v1","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.12239","created_at":"2026-05-17T23:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"HQ555QBHF7DA","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HQ555QBHF7DADFAM","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HQ555QBH","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:52dff95b2f3f90cdf88978328d32bb41cc097905a65f766e749447060f914231","target":"graph","created_at":"2026-05-17T23:59:33Z","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":"In semantic parsing for question-answering, it is often too expensive to collect gold parses or even gold answers as supervision signals. We propose to convert model outputs into a set of human-understandable statements which allow non-expert users to act as proofreaders, providing error markings as learning signals to the parser. Because model outputs were suggested by a historic system, we operate in a counterfactual, or off-policy, learning setup. We introduce new estimators which can effectively leverage the given feedback and which avoid known degeneracies in counterfactual learning, whil","authors_text":"Carolin Lawrence, Stefan Riezler","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-11-29T15:20:30Z","title":"Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.12239","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":"sha256:3a167bbb2d82d46fdab52098b044960ce7062d3760abc861576fccd942757ed6","target":"record","created_at":"2026-05-17T23:59:33Z","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":"c32d6ab1c594913d8587d8c41c9f55e83dd34457c47763ba33f356533ab3d24a","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-11-29T15:20:30Z","title_canon_sha256":"e35593a99516c9cfb8866c8a924e2be688e34de664d7465ce3c1bac676084102"},"schema_version":"1.0","source":{"id":"1811.12239","kind":"arxiv","version":1}},"canonical_sha256":"3c3bdec0272fc601940c9057499d996bc27f74e521663a856f3dee37c6ba8f36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3c3bdec0272fc601940c9057499d996bc27f74e521663a856f3dee37c6ba8f36","first_computed_at":"2026-05-17T23:59:33.953096Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:59:33.953096Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6M9IukfkjADUIwVaRE3RJX79G5Zeayr7KoEQyzPlnsCWxZWTaUn7WVgccWePJd+SQjVCP8/XnI5lF5gQSYUrAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:59:33.953820Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.12239","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3a167bbb2d82d46fdab52098b044960ce7062d3760abc861576fccd942757ed6","sha256:52dff95b2f3f90cdf88978328d32bb41cc097905a65f766e749447060f914231"],"state_sha256":"8d96476c6c43917772ecdbbb59877d997330286c1e55df30ac0e1645985b9b1e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KRmSqdxY2gWnOpgzOaCz25sQvoIKH8mR1/C+dWtCIspNz6ZALSoBwC/MpZOcBaT9lobywE7e5W9yh/23yC3lBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T16:44:38.153699Z","bundle_sha256":"4db84f6c3a5e5c07ea4634808e7cd49eb5939c8d71e62c703d88d99e5fdec56b"}}