{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:BL5BGFVS7VLH2WAXBC547XEKDC","short_pith_number":"pith:BL5BGFVS","canonical_record":{"source":{"id":"2104.05740","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-04-12T18:10:39Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"9e692f24f7f43475aee6f9e1fbab44832a078c7b0b2b2fb2cddd7e58583535a9","abstract_canon_sha256":"c8e827e06825545e700286d5cbafd65aad17ba6582a3b70fd3156e3da3b55b6b"},"schema_version":"1.0"},"canonical_sha256":"0afa1316b2fd567d581708bbcfdc8a1894a90c7c8deac7312358c07ee8b94daa","source":{"kind":"arxiv","id":"2104.05740","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.05740","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"arxiv_version","alias_value":"2104.05740v1","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.05740","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_12","alias_value":"BL5BGFVS7VLH","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"BL5BGFVS7VLH2WAX","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"BL5BGFVS","created_at":"2026-07-05T02:31:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:BL5BGFVS7VLH2WAXBC547XEKDC","target":"record","payload":{"canonical_record":{"source":{"id":"2104.05740","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-04-12T18:10:39Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"9e692f24f7f43475aee6f9e1fbab44832a078c7b0b2b2fb2cddd7e58583535a9","abstract_canon_sha256":"c8e827e06825545e700286d5cbafd65aad17ba6582a3b70fd3156e3da3b55b6b"},"schema_version":"1.0"},"canonical_sha256":"0afa1316b2fd567d581708bbcfdc8a1894a90c7c8deac7312358c07ee8b94daa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:31:24.459050Z","signature_b64":"WXWt9qQdvvJd/4VjZKa3vIBfogcENh2hwADMbsV1Ot1dR2SYx9uAvVrpz5/x9kqAdTeqNAaggFZnHTVUNecRAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0afa1316b2fd567d581708bbcfdc8a1894a90c7c8deac7312358c07ee8b94daa","last_reissued_at":"2026-07-05T02:31:24.458570Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:31:24.458570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.05740","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":"2026-07-05T02:31:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"k++Qs8Bslmt+4fm5g1z4LEYcLx4nv2pgRwQ5x/q0ChKl68Oy/G8XHZLj0BMYksiAoIB9UoU0Bw2fWFsZdswTCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T07:42:16.299080Z"},"content_sha256":"ecf1446616a0863074a0f209c36c16c9f5efb3b098773b00179b557e28a13fd5","schema_version":"1.0","event_id":"sha256:ecf1446616a0863074a0f209c36c16c9f5efb3b098773b00179b557e28a13fd5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:BL5BGFVS7VLH2WAXBC547XEKDC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Replication Study of Dense Passage Retriever","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Jimmy Lin, Kai Sun, Ronak Pradeep, Xueguang Ma","submitted_at":"2021-04-12T18:10:39Z","abstract_excerpt":"Text retrieval using learned dense representations has recently emerged as a promising alternative to \"traditional\" text retrieval using sparse bag-of-words representations. One recent work that has garnered much attention is the dense passage retriever (DPR) technique proposed by Karpukhin et al. (2020) for end-to-end open-domain question answering. We present a replication study of this work, starting with model checkpoints provided by the authors, but otherwise from an independent implementation in our group's Pyserini IR toolkit and PyGaggle neural text ranking library. Although our experi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.05740","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/2104.05740/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":"2026-07-05T02:31:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VVQZrQSukAN09qWc3/l3XgaYDkrv74ml0KbXK14oRC0E5yzGqnM1ZEWxPX0NbzNk7TbwHGrk5v3lqrO7kwM+CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T07:42:16.299468Z"},"content_sha256":"e194422b5dbc4f11a631793cb01af60f8bc5786eb356954a059ec22aa1c5d910","schema_version":"1.0","event_id":"sha256:e194422b5dbc4f11a631793cb01af60f8bc5786eb356954a059ec22aa1c5d910"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BL5BGFVS7VLH2WAXBC547XEKDC/bundle.json","state_url":"https://pith.science/pith/BL5BGFVS7VLH2WAXBC547XEKDC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BL5BGFVS7VLH2WAXBC547XEKDC/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":"2026-07-05T07:42:16Z","links":{"resolver":"https://pith.science/pith/BL5BGFVS7VLH2WAXBC547XEKDC","bundle":"https://pith.science/pith/BL5BGFVS7VLH2WAXBC547XEKDC/bundle.json","state":"https://pith.science/pith/BL5BGFVS7VLH2WAXBC547XEKDC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BL5BGFVS7VLH2WAXBC547XEKDC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:BL5BGFVS7VLH2WAXBC547XEKDC","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":"c8e827e06825545e700286d5cbafd65aad17ba6582a3b70fd3156e3da3b55b6b","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-04-12T18:10:39Z","title_canon_sha256":"9e692f24f7f43475aee6f9e1fbab44832a078c7b0b2b2fb2cddd7e58583535a9"},"schema_version":"1.0","source":{"id":"2104.05740","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.05740","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"arxiv_version","alias_value":"2104.05740v1","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.05740","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_12","alias_value":"BL5BGFVS7VLH","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_16","alias_value":"BL5BGFVS7VLH2WAX","created_at":"2026-07-05T02:31:24Z"},{"alias_kind":"pith_short_8","alias_value":"BL5BGFVS","created_at":"2026-07-05T02:31:24Z"}],"graph_snapshots":[{"event_id":"sha256:e194422b5dbc4f11a631793cb01af60f8bc5786eb356954a059ec22aa1c5d910","target":"graph","created_at":"2026-07-05T02:31:24Z","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/2104.05740/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text retrieval using learned dense representations has recently emerged as a promising alternative to \"traditional\" text retrieval using sparse bag-of-words representations. One recent work that has garnered much attention is the dense passage retriever (DPR) technique proposed by Karpukhin et al. (2020) for end-to-end open-domain question answering. We present a replication study of this work, starting with model checkpoints provided by the authors, but otherwise from an independent implementation in our group's Pyserini IR toolkit and PyGaggle neural text ranking library. Although our experi","authors_text":"Jimmy Lin, Kai Sun, Ronak Pradeep, Xueguang Ma","cross_cats":["cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-04-12T18:10:39Z","title":"A Replication Study of Dense Passage Retriever"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.05740","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:ecf1446616a0863074a0f209c36c16c9f5efb3b098773b00179b557e28a13fd5","target":"record","created_at":"2026-07-05T02:31:24Z","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":"c8e827e06825545e700286d5cbafd65aad17ba6582a3b70fd3156e3da3b55b6b","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-04-12T18:10:39Z","title_canon_sha256":"9e692f24f7f43475aee6f9e1fbab44832a078c7b0b2b2fb2cddd7e58583535a9"},"schema_version":"1.0","source":{"id":"2104.05740","kind":"arxiv","version":1}},"canonical_sha256":"0afa1316b2fd567d581708bbcfdc8a1894a90c7c8deac7312358c07ee8b94daa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0afa1316b2fd567d581708bbcfdc8a1894a90c7c8deac7312358c07ee8b94daa","first_computed_at":"2026-07-05T02:31:24.458570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:31:24.458570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WXWt9qQdvvJd/4VjZKa3vIBfogcENh2hwADMbsV1Ot1dR2SYx9uAvVrpz5/x9kqAdTeqNAaggFZnHTVUNecRAA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:31:24.459050Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.05740","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ecf1446616a0863074a0f209c36c16c9f5efb3b098773b00179b557e28a13fd5","sha256:e194422b5dbc4f11a631793cb01af60f8bc5786eb356954a059ec22aa1c5d910"],"state_sha256":"3bb9311fd50550d4ca54a26e2efbe52002f38532ed28dd8172b0013241771ac2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kIQYs2z8bT5vvFdUKJdD4AH8q0jeNkfHcLW3LX/1qPnaYwH7qFN/fmQpgyT5HqW2o94rljkedOhXm8fr8IPBCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T07:42:16.301511Z","bundle_sha256":"d0132c63bf5503fc1b0454947adef91fa64a52d67d454ff29625e9374f048fb0"}}