{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:O6OB24UXU3EJXH22DWR647EBE5","short_pith_number":"pith:O6OB24UX","canonical_record":{"source":{"id":"1707.06372","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-07-20T04:47:00Z","cross_cats_sorted":[],"title_canon_sha256":"777c57d6cd85486a7841c27f3564dd107b5ae3337f3909ed8da0261948c5e133","abstract_canon_sha256":"5f99eabeac5f1f57dad83663ee777ada6bbf0b0258209117ad1d7dd0c40cf65d"},"schema_version":"1.0"},"canonical_sha256":"779c1d7297a6c89b9f5a1da3ee7c81276583a24ba317b4bf397a9dca56ef57c2","source":{"kind":"arxiv","id":"1707.06372","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06372","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06372v1","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06372","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"pith_short_12","alias_value":"O6OB24UXU3EJ","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"O6OB24UXU3EJXH22","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"O6OB24UX","created_at":"2026-05-18T12:31:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:O6OB24UXU3EJXH22DWR647EBE5","target":"record","payload":{"canonical_record":{"source":{"id":"1707.06372","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-07-20T04:47:00Z","cross_cats_sorted":[],"title_canon_sha256":"777c57d6cd85486a7841c27f3564dd107b5ae3337f3909ed8da0261948c5e133","abstract_canon_sha256":"5f99eabeac5f1f57dad83663ee777ada6bbf0b0258209117ad1d7dd0c40cf65d"},"schema_version":"1.0"},"canonical_sha256":"779c1d7297a6c89b9f5a1da3ee7c81276583a24ba317b4bf397a9dca56ef57c2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:53.974477Z","signature_b64":"dOKBjGwG5FDUOLKGHFFk1yMpc3p3xUz0fkGv5Hz17wnplNfbJwdEkNYoSb6JiRuHsNCQpWoOkzdWqSrffhLzCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"779c1d7297a6c89b9f5a1da3ee7c81276583a24ba317b4bf397a9dca56ef57c2","last_reissued_at":"2026-05-18T00:39:53.973853Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:53.973853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.06372","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":"2026-05-18T00:39:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f1OknO5HP9jjxxzAeYLU8fifPL6Y/etoIn0ccnYnAYUxumMtTdOsEF8UrxvST3M263KNZ/D202jvGMMLoBqxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T02:59:06.291640Z"},"content_sha256":"02b394e5ee85cf9430913853be9b39a84be34a4ea642c7f21a30a59e1a590e66","schema_version":"1.0","event_id":"sha256:02b394e5ee85cf9430913853be9b39a84be34a4ea642c7f21a30a59e1a590e66"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:O6OB24UXU3EJXH22DWR647EBE5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Luu Anh Tuan, Minh C. Phan, Siu Cheung Hui, Yi Tay","submitted_at":"2017-07-20T04:47:00Z","abstract_excerpt":"We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term memory (LSTM) network with holographic composition to model the relationship between question and answer representations. As opposed to the neural tensor layer that has been adopted recently, the holographic composition provides the benefits of scalable and rich representational learning approach without incurring huge parameter costs. Overall, we present Holographic Dual LSTM (HD-LSTM), a unified architecture for both deep sentence modeling and semantic matching. E"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06372","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":"2026-05-18T00:39:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PuUWKVy4GzRQb4X0pjckds8mSfkoqyWn2J1Xew80mpD/vBJW2EhvFJ0n3Nphcw6QC04yxkhbIT0d5LaqOaWtAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T02:59:06.292369Z"},"content_sha256":"014e5722aec4ed83bbcd7d75ce604dfd4549f41ee3039419b432f91dc4183d95","schema_version":"1.0","event_id":"sha256:014e5722aec4ed83bbcd7d75ce604dfd4549f41ee3039419b432f91dc4183d95"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/O6OB24UXU3EJXH22DWR647EBE5/bundle.json","state_url":"https://pith.science/pith/O6OB24UXU3EJXH22DWR647EBE5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/O6OB24UXU3EJXH22DWR647EBE5/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":"2026-05-26T02:59:06Z","links":{"resolver":"https://pith.science/pith/O6OB24UXU3EJXH22DWR647EBE5","bundle":"https://pith.science/pith/O6OB24UXU3EJXH22DWR647EBE5/bundle.json","state":"https://pith.science/pith/O6OB24UXU3EJXH22DWR647EBE5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/O6OB24UXU3EJXH22DWR647EBE5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:O6OB24UXU3EJXH22DWR647EBE5","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":"5f99eabeac5f1f57dad83663ee777ada6bbf0b0258209117ad1d7dd0c40cf65d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-07-20T04:47:00Z","title_canon_sha256":"777c57d6cd85486a7841c27f3564dd107b5ae3337f3909ed8da0261948c5e133"},"schema_version":"1.0","source":{"id":"1707.06372","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06372","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06372v1","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06372","created_at":"2026-05-18T00:39:53Z"},{"alias_kind":"pith_short_12","alias_value":"O6OB24UXU3EJ","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_16","alias_value":"O6OB24UXU3EJXH22","created_at":"2026-05-18T12:31:34Z"},{"alias_kind":"pith_short_8","alias_value":"O6OB24UX","created_at":"2026-05-18T12:31:34Z"}],"graph_snapshots":[{"event_id":"sha256:014e5722aec4ed83bbcd7d75ce604dfd4549f41ee3039419b432f91dc4183d95","target":"graph","created_at":"2026-05-18T00:39:53Z","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"},"paper":{"abstract_excerpt":"We describe a new deep learning architecture for learning to rank question answer pairs. Our approach extends the long short-term memory (LSTM) network with holographic composition to model the relationship between question and answer representations. As opposed to the neural tensor layer that has been adopted recently, the holographic composition provides the benefits of scalable and rich representational learning approach without incurring huge parameter costs. Overall, we present Holographic Dual LSTM (HD-LSTM), a unified architecture for both deep sentence modeling and semantic matching. E","authors_text":"Luu Anh Tuan, Minh C. Phan, Siu Cheung Hui, Yi Tay","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-07-20T04:47:00Z","title":"Learning to Rank Question Answer Pairs with Holographic Dual LSTM Architecture"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06372","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":"sha256:02b394e5ee85cf9430913853be9b39a84be34a4ea642c7f21a30a59e1a590e66","target":"record","created_at":"2026-05-18T00:39:53Z","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":"5f99eabeac5f1f57dad83663ee777ada6bbf0b0258209117ad1d7dd0c40cf65d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IR","submitted_at":"2017-07-20T04:47:00Z","title_canon_sha256":"777c57d6cd85486a7841c27f3564dd107b5ae3337f3909ed8da0261948c5e133"},"schema_version":"1.0","source":{"id":"1707.06372","kind":"arxiv","version":1}},"canonical_sha256":"779c1d7297a6c89b9f5a1da3ee7c81276583a24ba317b4bf397a9dca56ef57c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"779c1d7297a6c89b9f5a1da3ee7c81276583a24ba317b4bf397a9dca56ef57c2","first_computed_at":"2026-05-18T00:39:53.973853Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:53.973853Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dOKBjGwG5FDUOLKGHFFk1yMpc3p3xUz0fkGv5Hz17wnplNfbJwdEkNYoSb6JiRuHsNCQpWoOkzdWqSrffhLzCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:53.974477Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.06372","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:02b394e5ee85cf9430913853be9b39a84be34a4ea642c7f21a30a59e1a590e66","sha256:014e5722aec4ed83bbcd7d75ce604dfd4549f41ee3039419b432f91dc4183d95"],"state_sha256":"8a2f488114a975a90c8375b31b52d7cba0e0e81b7c40e4b0b4e1fd50dac5d631"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L/kaq3p6I/W4mjqMRZXsdR09+aOYy9owkIG7ApvABu5Ip0yuYN6F7qTAyAa2HZNo1Yw7wHBHoBaXj1u4jHYbAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T02:59:06.296194Z","bundle_sha256":"73d041efbcd404c116ac2f849ee7cbada0fb662135d46438765176721f73c721"}}