{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:L57LYG2SYUSFRSREUNNEALEOV5","short_pith_number":"pith:L57LYG2S","canonical_record":{"source":{"id":"2305.08208","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-14T17:53:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"839a51a0be949e4b8281cdb04ab272f3d8f10b62757c1d68b759c7b539d214c1","abstract_canon_sha256":"5ea49ada3085226aa890738b3237449fab645312bcc99ecbb34f4d53f416566b"},"schema_version":"1.0"},"canonical_sha256":"5f7ebc1b52c52458ca24a35a402c8eaf7695abf8fcc207cd1b0d14be350d8dc6","source":{"kind":"arxiv","id":"2305.08208","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.08208","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"arxiv_version","alias_value":"2305.08208v2","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.08208","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_12","alias_value":"L57LYG2SYUSF","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_16","alias_value":"L57LYG2SYUSFRSRE","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_8","alias_value":"L57LYG2S","created_at":"2026-07-05T06:11:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:L57LYG2SYUSFRSREUNNEALEOV5","target":"record","payload":{"canonical_record":{"source":{"id":"2305.08208","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-14T17:53:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"839a51a0be949e4b8281cdb04ab272f3d8f10b62757c1d68b759c7b539d214c1","abstract_canon_sha256":"5ea49ada3085226aa890738b3237449fab645312bcc99ecbb34f4d53f416566b"},"schema_version":"1.0"},"canonical_sha256":"5f7ebc1b52c52458ca24a35a402c8eaf7695abf8fcc207cd1b0d14be350d8dc6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:11:21.316378Z","signature_b64":"kaVJ1Z+aRaTXvtHFufKU21hKcEvD6jzeLtNPawPuF1n3iQ3l80TvgWdpU17gbSGh3AcfuTIc4AlzhnR4MA6MBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f7ebc1b52c52458ca24a35a402c8eaf7695abf8fcc207cd1b0d14be350d8dc6","last_reissued_at":"2026-07-05T06:11:21.315939Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:11:21.315939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.08208","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":"2026-07-05T06:11:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2nKPv8smXrXmYdTGCOtmEKHibEPXy/mvzROCHlUZj3tGi4WNEmZgB0VkUvvopPWOmwfC/6ZhvDL62yMm6dFAAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T08:22:32.955510Z"},"content_sha256":"4b200890d620fadd0b060841db2f1e29bc87d698198a22242a120479f74f0b5b","schema_version":"1.0","event_id":"sha256:4b200890d620fadd0b060841db2f1e29bc87d698198a22242a120479f74f0b5b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:L57LYG2SYUSFRSREUNNEALEOV5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Generalize for Cross-domain QA","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Linyi Yang, Ruihai Dong, Yingjie Niu, Yue Zhang","submitted_at":"2023-05-14T17:53:54Z","abstract_excerpt":"There have been growing concerns regarding the out-of-domain generalization ability of natural language processing (NLP) models, particularly in question-answering (QA) tasks. Current synthesized data augmentation methods for QA are hampered by increased training costs. To address this issue, we propose a novel approach that combines prompting methods and linear probing then fine-tuning strategy, which does not entail additional cost. Our method has been theoretically and empirically shown to be effective in enhancing the generalization ability of both generative and discriminative models. Our"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.08208","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/2305.08208/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":"2026-07-05T06:11:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MlxQRykUMu89SbdAwDzvgnMVEHtjuggZtNOTAsqMep9M1xD1Dv7DRhuVsfJDsNzVQ+1dHLzw7kV2LEiL0pABCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T08:22:32.955886Z"},"content_sha256":"7b0177031971784e3549010ab80bf96ff3d2f91f206082682d5a6bb7cbb0dbac","schema_version":"1.0","event_id":"sha256:7b0177031971784e3549010ab80bf96ff3d2f91f206082682d5a6bb7cbb0dbac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L57LYG2SYUSFRSREUNNEALEOV5/bundle.json","state_url":"https://pith.science/pith/L57LYG2SYUSFRSREUNNEALEOV5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L57LYG2SYUSFRSREUNNEALEOV5/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":"2026-07-27T08:22:32Z","links":{"resolver":"https://pith.science/pith/L57LYG2SYUSFRSREUNNEALEOV5","bundle":"https://pith.science/pith/L57LYG2SYUSFRSREUNNEALEOV5/bundle.json","state":"https://pith.science/pith/L57LYG2SYUSFRSREUNNEALEOV5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L57LYG2SYUSFRSREUNNEALEOV5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:L57LYG2SYUSFRSREUNNEALEOV5","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":"5ea49ada3085226aa890738b3237449fab645312bcc99ecbb34f4d53f416566b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-14T17:53:54Z","title_canon_sha256":"839a51a0be949e4b8281cdb04ab272f3d8f10b62757c1d68b759c7b539d214c1"},"schema_version":"1.0","source":{"id":"2305.08208","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.08208","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"arxiv_version","alias_value":"2305.08208v2","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.08208","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_12","alias_value":"L57LYG2SYUSF","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_16","alias_value":"L57LYG2SYUSFRSRE","created_at":"2026-07-05T06:11:21Z"},{"alias_kind":"pith_short_8","alias_value":"L57LYG2S","created_at":"2026-07-05T06:11:21Z"}],"graph_snapshots":[{"event_id":"sha256:7b0177031971784e3549010ab80bf96ff3d2f91f206082682d5a6bb7cbb0dbac","target":"graph","created_at":"2026-07-05T06:11:21Z","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/2305.08208/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"There have been growing concerns regarding the out-of-domain generalization ability of natural language processing (NLP) models, particularly in question-answering (QA) tasks. Current synthesized data augmentation methods for QA are hampered by increased training costs. To address this issue, we propose a novel approach that combines prompting methods and linear probing then fine-tuning strategy, which does not entail additional cost. Our method has been theoretically and empirically shown to be effective in enhancing the generalization ability of both generative and discriminative models. Our","authors_text":"Linyi Yang, Ruihai Dong, Yingjie Niu, Yue Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-14T17:53:54Z","title":"Learning to Generalize for Cross-domain QA"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.08208","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":"sha256:4b200890d620fadd0b060841db2f1e29bc87d698198a22242a120479f74f0b5b","target":"record","created_at":"2026-07-05T06:11:21Z","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":"5ea49ada3085226aa890738b3237449fab645312bcc99ecbb34f4d53f416566b","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-14T17:53:54Z","title_canon_sha256":"839a51a0be949e4b8281cdb04ab272f3d8f10b62757c1d68b759c7b539d214c1"},"schema_version":"1.0","source":{"id":"2305.08208","kind":"arxiv","version":2}},"canonical_sha256":"5f7ebc1b52c52458ca24a35a402c8eaf7695abf8fcc207cd1b0d14be350d8dc6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5f7ebc1b52c52458ca24a35a402c8eaf7695abf8fcc207cd1b0d14be350d8dc6","first_computed_at":"2026-07-05T06:11:21.315939Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:21.315939Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kaVJ1Z+aRaTXvtHFufKU21hKcEvD6jzeLtNPawPuF1n3iQ3l80TvgWdpU17gbSGh3AcfuTIc4AlzhnR4MA6MBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:21.316378Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.08208","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4b200890d620fadd0b060841db2f1e29bc87d698198a22242a120479f74f0b5b","sha256:7b0177031971784e3549010ab80bf96ff3d2f91f206082682d5a6bb7cbb0dbac"],"state_sha256":"13de25a307fe672baa02b71fb30b551ba4322edb01cd5a539d2fb6ac3bfc1aff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pKwzPWlPKT0yGS+poALmqDzCTXZU4N92PffXCZVrPqn3oLuFfmiqX/ph6fUb3CA/Xop4QUZ/9eBHDDI6MfItBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T08:22:32.958341Z","bundle_sha256":"6a4da5a539ba102655df5cddf8569e3b7d958c3cf12419e50535cd44669613f4"}}