{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:6LEPZ7KDK2R4CQOOFZLQEC23XH","short_pith_number":"pith:6LEPZ7KD","canonical_record":{"source":{"id":"1901.00603","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-01-03T03:55:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"38bd8462ce5a1c5204e45cb63854ea12f1a7338e48d2bbf2cab68c0c3bd2ecf1","abstract_canon_sha256":"d96d221faef98f56ea2fd3066d25365e24d406067f1a727d49374065871aa90c"},"schema_version":"1.0"},"canonical_sha256":"f2c8fcfd4356a3c141ce2e57020b5bb9d2ec4ec6daadb10ca1cfb99ee4a76641","source":{"kind":"arxiv","id":"1901.00603","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.00603","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"arxiv_version","alias_value":"1901.00603v2","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.00603","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"pith_short_12","alias_value":"6LEPZ7KDK2R4","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"6LEPZ7KDK2R4CQOO","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"6LEPZ7KD","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:6LEPZ7KDK2R4CQOOFZLQEC23XH","target":"record","payload":{"canonical_record":{"source":{"id":"1901.00603","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-01-03T03:55:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"38bd8462ce5a1c5204e45cb63854ea12f1a7338e48d2bbf2cab68c0c3bd2ecf1","abstract_canon_sha256":"d96d221faef98f56ea2fd3066d25365e24d406067f1a727d49374065871aa90c"},"schema_version":"1.0"},"canonical_sha256":"f2c8fcfd4356a3c141ce2e57020b5bb9d2ec4ec6daadb10ca1cfb99ee4a76641","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:46:29.211268Z","signature_b64":"cVyTTEW+OvQ0IxxnY5idJVd8VmCvNOXiP40BSpv9z97UrWbnKuB5WatG5Ww/YIcUc5iUNDjyWLtalBm+D9fOCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f2c8fcfd4356a3c141ce2e57020b5bb9d2ec4ec6daadb10ca1cfb99ee4a76641","last_reissued_at":"2026-05-17T23:46:29.210629Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:46:29.210629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1901.00603","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":"2026-05-17T23:46:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"st6uEe9XMQKs/S2aZ33akB3mr07WtveBv+ZxI/nBC5lmyWDDqWyCisgui8eFV7+RZkhdODTE2onrenRFB1c8Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T14:15:58.011631Z"},"content_sha256":"bcd33c38ec03244afcaf5edbbfc6c35ac21a96d82e15c182aea372dd4a0d80cf","schema_version":"1.0","event_id":"sha256:bcd33c38ec03244afcaf5edbbfc6c35ac21a96d82e15c182aea372dd4a0d80cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:6LEPZ7KDK2R4CQOOFZLQEC23XH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Caiming Xiong, Nitish Shirish Keskar, Richard Socher, Victor Zhong","submitted_at":"2019-01-03T03:55:49Z","abstract_excerpt":"End-to-end neural models have made significant progress in question answering, however recent studies show that these models implicitly assume that the answer and evidence appear close together in a single document. In this work, we propose the Coarse-grain Fine-grain Coattention Network (CFC), a new question answering model that combines information from evidence across multiple documents. The CFC consists of a coarse-grain module that interprets documents with respect to the query then finds a relevant answer, and a fine-grain module which scores each candidate answer by comparing its occurr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.00603","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":""},"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":"2026-05-17T23:46:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6dHKRgosgWCFlDtQ/BRdFUgWVi7twwbfb+eS/ilXw8ljbZMrA91mzWFF82vLNCz7l61ovFN7p/MvaNDTrPiHDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T14:15:58.011980Z"},"content_sha256":"323932daa927078f8ca54216e94fc70f1619329dbb3940e452fd124976df8183","schema_version":"1.0","event_id":"sha256:323932daa927078f8ca54216e94fc70f1619329dbb3940e452fd124976df8183"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/bundle.json","state_url":"https://pith.science/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/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":"2026-05-27T14:15:58Z","links":{"resolver":"https://pith.science/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH","bundle":"https://pith.science/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/bundle.json","state":"https://pith.science/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6LEPZ7KDK2R4CQOOFZLQEC23XH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:6LEPZ7KDK2R4CQOOFZLQEC23XH","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":"d96d221faef98f56ea2fd3066d25365e24d406067f1a727d49374065871aa90c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-01-03T03:55:49Z","title_canon_sha256":"38bd8462ce5a1c5204e45cb63854ea12f1a7338e48d2bbf2cab68c0c3bd2ecf1"},"schema_version":"1.0","source":{"id":"1901.00603","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1901.00603","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"arxiv_version","alias_value":"1901.00603v2","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1901.00603","created_at":"2026-05-17T23:46:29Z"},{"alias_kind":"pith_short_12","alias_value":"6LEPZ7KDK2R4","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"6LEPZ7KDK2R4CQOO","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"6LEPZ7KD","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:323932daa927078f8ca54216e94fc70f1619329dbb3940e452fd124976df8183","target":"graph","created_at":"2026-05-17T23:46:29Z","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":"End-to-end neural models have made significant progress in question answering, however recent studies show that these models implicitly assume that the answer and evidence appear close together in a single document. In this work, we propose the Coarse-grain Fine-grain Coattention Network (CFC), a new question answering model that combines information from evidence across multiple documents. The CFC consists of a coarse-grain module that interprets documents with respect to the query then finds a relevant answer, and a fine-grain module which scores each candidate answer by comparing its occurr","authors_text":"Caiming Xiong, Nitish Shirish Keskar, Richard Socher, Victor Zhong","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-01-03T03:55:49Z","title":"Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1901.00603","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:bcd33c38ec03244afcaf5edbbfc6c35ac21a96d82e15c182aea372dd4a0d80cf","target":"record","created_at":"2026-05-17T23:46:29Z","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":"d96d221faef98f56ea2fd3066d25365e24d406067f1a727d49374065871aa90c","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-01-03T03:55:49Z","title_canon_sha256":"38bd8462ce5a1c5204e45cb63854ea12f1a7338e48d2bbf2cab68c0c3bd2ecf1"},"schema_version":"1.0","source":{"id":"1901.00603","kind":"arxiv","version":2}},"canonical_sha256":"f2c8fcfd4356a3c141ce2e57020b5bb9d2ec4ec6daadb10ca1cfb99ee4a76641","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f2c8fcfd4356a3c141ce2e57020b5bb9d2ec4ec6daadb10ca1cfb99ee4a76641","first_computed_at":"2026-05-17T23:46:29.210629Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:46:29.210629Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cVyTTEW+OvQ0IxxnY5idJVd8VmCvNOXiP40BSpv9z97UrWbnKuB5WatG5Ww/YIcUc5iUNDjyWLtalBm+D9fOCw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:46:29.211268Z","signed_message":"canonical_sha256_bytes"},"source_id":"1901.00603","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcd33c38ec03244afcaf5edbbfc6c35ac21a96d82e15c182aea372dd4a0d80cf","sha256:323932daa927078f8ca54216e94fc70f1619329dbb3940e452fd124976df8183"],"state_sha256":"d19386e71a8ee3f74ec057e1540d2089123fbb5eda4cb54b77e5a428ea3ff9ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xp59EGV4eJqjgfxCS5VJnvnCs+v8wvcNs9UtxVXp7NqVY7LMP0Y+if4d2gjaSbAWISI0GTYnd/gFRECL+ETTBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T14:15:58.014219Z","bundle_sha256":"67376beb946c438d7bc988d5f438f56db3325dc8e4ac4e0c5fdbd15a2f2f4835"}}