{"as_of":"2026-08-16T12:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:934a9c33b5e572ed86d6aeb58f3e2f7df3825f86a2db2d6e6345c5927a285a40","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:36:12.623865Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T14:36:12.500970Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-14T14:36:12.661182Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"cited_work":{"arxiv_id":"1908.02914","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.02914","snapshot_observed_at":"2026-08-14T14:36:12.661182Z","title":"Mitigating Noisy Inputs for Question Answering","venue":"cs.CL","work_id":"88dd5bb9-a87c-4a46-b492-71d52458651a","year":2019},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.500970Z"},"links":{"cited_paper":"/paper/1908.02914","citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:2cad24d6618853d5dfd8bb32e67a7987f708228078c09924bfb0dac72f4f87a0","observation_id":"f79d405c-42ff-489e-93cc-47f79fa87981","resolution":{"observed_at":"2026-08-14T14:36:12.667836Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.02914/citation-record","integrity":"/paper/1908.02914/integrity","json":"/paper/1908.02914/citation-record.json","paper":"/paper/1908.02914"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"cited_work":{"arxiv_id":"1908.02914","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.02914","snapshot_observed_at":"2026-08-14T14:36:12.661182Z","title":"Mitigating Noisy Inputs for Question Answering","venue":"cs.CL","work_id":"88dd5bb9-a87c-4a46-b492-71d52458651a","year":2019},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.500970Z"},"links":{"cited_paper":"/paper/1908.02914","citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:2cad24d6618853d5dfd8bb32e67a7987f708228078c09924bfb0dac72f4f87a0","observation_id":"f79d405c-42ff-489e-93cc-47f79fa87981","resolution":{"observed_at":"2026-08-14T14:36:12.667836Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:13.002826Z","title":"cyclohexane","venue":null,"work_id":"0d68d444-cb47-4fdb-af61-a0ad2946c67d","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.506956Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:e8694078bd39efff261c0301c8743303fb5114c446873e3c8b2af9b2f88595d3","observation_id":"f31aaee2-e6b2-42bb-8446-e05df87256be","resolution":{"observed_at":"2026-08-14T14:36:13.006619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.991741Z","title":"Louis Vampas","venue":null,"work_id":"ef1e118b-6ff5-4db9-8e40-4cf9d7445303","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.511640Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:6afad1d0d8f53fe61a35524a809b613130eddeb28c46f8d3fd185f297b278caf","observation_id":"2789bb60-fa04-4734-bce1-c0f0e7c6269d","resolution":{"observed_at":"2026-08-14T14:36:12.995802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.980464Z","title":"novel”, “character","venue":null,"work_id":"d1fa382c-cc9e-41de-8741-6812f32ed50c","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.516646Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:0ca464527515bf868c297079641e7e10128e975acdcbcbd928feae12fb55cba6","observation_id":"1733cd30-3dd0-409d-a291-523ed0824879","resolution":{"observed_at":"2026-08-14T14:36:12.985170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.970363Z","title":"Introducing ASR into a QA pipeline corrupts the data","venue":null,"work_id":"00ff3458-3d13-44c5-b441-d2c64ae7e7be","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.521755Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:a07535dcc0cd894a050485071cf2d0971fa5a931d0d0b46c615418caab309c2f","observation_id":"1af63212-4ff8-4c49-aa51-3aa0c7c09c61","resolution":{"observed_at":"2026-08-14T14:36:12.974011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.960407Z","title":"The views expressed in this paper are our own","venue":null,"work_id":"a4c40443-5ecb-47c3-8a44-a8df3f3da5b1","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.525791Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:70694880178f446a9aff75d1a3ccc19eb158a2cabc8821f61fd89f201ee5bcb3","observation_id":"36ab6004-3ece-4a91-ac43-fd47cfcae7c7","resolution":{"observed_at":"2026-08-14T14:36:12.963962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.948678Z","title":"Build Watson: an overview of DeepQA for the Jeopardy! challenge,","venue":null,"work_id":"655b465e-61c5-47fe-acca-7d0c40dfdf7f","year":2010},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.529841Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:dfb1f4e1546dee5dc72088d346531d3c9f27060cd95ddf714cee5ae6b5b31160","observation_id":"c9c6a2eb-6a4d-4c53-b85a-7b8130f1f5d0","resolution":{"observed_at":"2026-08-14T14:36:12.952902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.937338Z","title":"Boyd-Graber, S","venue":null,"work_id":"b7c23863-3db5-458f-bb49-a1d03e0b9961","year":2018},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.533410Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:620e3e53222a048c815f41a14314787fe4a37fba58ea882a01ddaba6f4a4ce1f","observation_id":"4f5f631b-b675-47c7-8c89-6b89a02dd775","resolution":{"observed_at":"2026-08-14T14:36:12.940674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.926963Z","title":"Adversarial examples for evaluating reading comprehension systems,","venue":null,"work_id":"85b95ebf-d988-46f6-8def-060802eb33ab","year":2017},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.537033Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:d376733ff461199c631a28066ddf157be1aa97a7794d976e7619e173d8334c3f","observation_id":"773fcbb8-6e5f-48ac-89b0-75d67d386192","resolution":{"observed_at":"2026-08-14T14:36:12.930365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.916788Z","title":"Qme!: A speech-based question-answering system on mobile devices,","venue":null,"work_id":"afc63386-97fd-4632-9ed8-20ae02db2162","year":2010},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.541462Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:46183af8d7e25a6de9fad9aa9d54ad947603a9f7b379bc853d204af48f80c0f2","observation_id":"906829da-394c-452b-9d9a-6ee8eab6e35b","resolution":{"observed_at":"2026-08-14T14:36:12.920314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.905958Z","title":"Building effective question answering characters,","venue":null,"work_id":"85eebe4a-aece-42bc-97df-8cdf27d6e654","year":2009},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.545331Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:a83c4d3e0e0508371cdd109c048ca15b28564626efcaaeb283a5c317ec183ce0","observation_id":"5cbdf62c-e4ea-4770-b002-9a30106254b9","resolution":{"observed_at":"2026-08-14T14:36:12.910004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.895344Z","title":"Neural lattice-to-sequence models for uncertain inputs,","venue":null,"work_id":"908bbd28-4232-4c67-a61a-e77df3872af3","year":2017},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.549527Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:89c745a2628b2538f59391691ca996da77cca711339ac8d749d908b52c2bcf33","observation_id":"8f202e6f-d43c-4dd5-beca-17a54594149b","resolution":{"observed_at":"2026-08-14T14:36:12.899208Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.884622Z","title":"Jhu aspire system: Robust lvcsr with tdnns, ivector adaptation and rnn-lms,","venue":null,"work_id":"5d0aa4ea-e662-43c0-9459-3f25a8320bbc","year":2015},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.553200Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:8b2e693f87e65ab71ad84b3773bf84456ce93b82af31a9573536d4ae484b154c","observation_id":"5a0d7ffa-7e91-40b6-b8d5-8a5c6d394575","resolution":{"observed_at":"2026-08-14T14:36:12.888287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.873529Z","title":"The fisher corpus: a resource for the next generations of speech-to-text,","venue":null,"work_id":"68741379-d600-4883-bfd0-560e02cafe1a","year":2004},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.556820Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:4432843e7cb6276d27b8f90f0030d887b35c146495da07a515c5ea4cc543ba30","observation_id":"d8d2783c-6913-4ad3-b0d0-7b8cadde9994","resolution":{"observed_at":"2026-08-14T14:36:12.877073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.862570Z","title":"Mtnt: A testbed for machine translation of noisy text,","venue":null,"work_id":"6eda16a5-7508-4e0d-a8b5-3210bcc14662","year":2018},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.560576Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:f9bb6072908d7434e47d602013bf3b53083352ba7edb47721966dbb59a051b33","observation_id":"0987fc42-61da-4a69-ab5f-48d81edfa205","resolution":{"observed_at":"2026-08-14T14:36:12.866514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.850907Z","title":"Synthetic and natural noise both break neural machine translation,","venue":null,"work_id":"629616c5-2ded-4d9f-91aa-8ca420b04511","year":2017},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.565151Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:e1908f95f9b336ec087682de4ece6aa390f4797f90b6c3b11c30bbf2a077f739","observation_id":"06186bda-d735-44d8-884b-9b65e175d0b6","resolution":{"observed_at":"2026-08-14T14:36:12.854567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.837981Z","title":"Exploring speech enhancement with generative adversarial networks for ro- bust speech recognition,","venue":null,"work_id":"dbb8e5e5-dc81-456f-8f63-f59f007a3dc0","year":2018},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.569195Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:1778d472560a9a830aeca028344e28da10e7c38517e50b05c93d8e4817e8bc37","observation_id":"44842636-a21b-4962-bb1b-049e382eb077","resolution":{"observed_at":"2026-08-14T14:36:12.843071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.827201Z","title":"Odsqa: Open-domain spoken question answering dataset,","venue":null,"work_id":"643f5bc6-ce25-4d6c-8d23-482094d51496","year":2018},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.572857Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:d33186914b905377f26ab7e798ec4f55463c8ab5c43375733af03b80ceabb6ec","observation_id":"56290b56-05c4-4619-8235-8c0c796feea7","resolution":{"observed_at":"2026-08-14T14:36:12.830666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.816103Z","title":"Studio Ousia’s quiz bowl question answering system,","venue":null,"work_id":"56864260-aeb0-49d5-8cc2-434acfca3181","year":2018},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.576432Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:66d34119988984096b41695b9736319c28ca473e0202e5b025e7c1a575560e0b","observation_id":"3e98fe5a-9c21-4667-8704-c5e3564fc60a","resolution":{"observed_at":"2026-08-14T14:36:12.820314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.05179","last_updated":"2017-06-11T11:51:06Z","snapshot_observed_at":"2026-08-14T21:06:19.917688Z","submitted_at":"2017-04-18T02:42:17Z","title":"SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.05179","snapshot_observed_at":"2026-08-14T14:36:12.579984Z","title":"Searchqa: A new Q&A dataset augmented with context from a search engine,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.579984Z"},"links":{"cited_paper":"/paper/1704.05179","citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:fe51ddd3255c0381421d7357280ffe9a9aac0d8190c831e29e1694fcbe99a6db","observation_id":"c8697ea0-7320-4ed8-846d-197dce37e1b3","resolution":{"observed_at":"2026-08-14T14:36:12.579984Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.805546Z","title":"Using tf-idf to determine word relevance in document queries,","venue":null,"work_id":"10492cb2-162f-4cdc-abd7-59474e89f182","year":2003},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.583606Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:9b7825d846c12b12f2fdfd53f01f742174c3c25e9e0b21e4db61712c8089aeb0","observation_id":"9c5ac1dd-ed3b-4ed7-b8d9-66461ff2b104","resolution":{"observed_at":"2026-08-14T14:36:12.809898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.795116Z","title":"The probabilistic rele- vance framework: Bm25 and beyond,","venue":null,"work_id":"b1af452d-fc75-4363-a048-d574367c8c91","year":2009},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.587930Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:300a822db532b85e6bdc9c5a2a2d69426cc460f72fd1ced4835275d7f218c314","observation_id":"02f7df26-63fc-45b7-a946-5adf8ffe8eff","resolution":{"observed_at":"2026-08-14T14:36:12.799148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.783988Z","title":"The Kaldi speech recognition toolkit,","venue":null,"work_id":"99396bbc-ca72-4da1-98e0-bab3c5755844","year":2011},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.591714Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:4c5326ed5a06f0494819306459aa2dce78aa465f98b943bcf9811f41a90d4bcb","observation_id":"29c87b14-46a5-4b77-b4f8-def4ca212d73","resolution":{"observed_at":"2026-08-14T14:36:12.787377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.773755Z","title":"Deep unordered composition rivals syntactic methods for text classification,","venue":null,"work_id":"7d0882db-4ea4-4765-856f-81a0bb167922","year":2015},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.594758Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:a2d78d0d0ebd6ef635a34808a9dcbd3da12c69f26aa0005314bf9b2949c0fda1","observation_id":"82c290ac-8dad-4e8e-a0e8-c964f70ba74e","resolution":{"observed_at":"2026-08-14T14:36:12.777352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.761763Z","title":"Automatic differentiation in pytorch,","venue":null,"work_id":"d8e6bf18-daa2-478c-9a02-bb7c16d198f2","year":2017},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.598428Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:82f4fe5eb515ec5a22730a3f34b100220e272437095c81fc28af639d265b5c29","observation_id":"e71793c1-b793-470d-b3c3-18c4a1d15f6d","resolution":{"observed_at":"2026-08-14T14:36:12.765829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.750410Z","title":"Unsupervised training of acoustic models for large vocabulary continuous speech recogni- tion,","venue":null,"work_id":"d2e0caf8-4f51-43e6-a938-7fb06f50a05c","year":2004},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.602255Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:0d02542fcc1e77ebb1819335749502b60d977b3c11cb9e4751b8d24f4a4181f5","observation_id":"e673a72c-3532-426f-8a87-4e911ef044e6","resolution":{"observed_at":"2026-08-14T14:36:12.753972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.737824Z","title":"Unsupervised feature learning for audio classification using convolutional deep belief networks,","venue":null,"work_id":"e0beb756-367e-4c82-9681-20d7294f96b3","year":2009},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.605742Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:da25d2da47b6817ff4fa6688c37e1e32826cd69b1080c8e60e2e872378e79e47","observation_id":"4009c955-ed10-4938-8883-6e09e551f321","resolution":{"observed_at":"2026-08-14T14:36:12.742427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.723811Z","title":"BLEU: a method for automatic evaluation of machine translation,","venue":null,"work_id":"48b096f5-7b35-4b53-9b2e-06a43c3651b5","year":2002},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.609553Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:f2a53896248017280e81403058d70f3c3cba223fd5503ef22e874b2260e1744a","observation_id":"4feb80e2-cc12-4f92-ae98-706aee214763","resolution":{"observed_at":"2026-08-14T14:36:12.728197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.712754Z","title":"A mathematical theory of communication,","venue":null,"work_id":"af3cf214-1bd9-4df9-8f58-4f3e0c847096","year":1948},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.613316Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:ebc691ae5aae198c0ce3aabb578007642e11edff17aa8e6922d1060d33fb6009","observation_id":"ed18fc2a-5957-4bfc-85c3-438ba394e775","resolution":{"observed_at":"2026-08-14T14:36:12.716720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.700440Z","title":null,"venue":null,"work_id":"f0d963c8-53fd-42fd-bcd7-e425c122fc1b","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.617275Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:f5c93befd004416aa92945fedd6cd6fcb9ca1354ad49bb04f00fad6bf360b4d6","observation_id":"6c8d541a-ac11-4e38-99a8-ecbe460bedce","resolution":{"observed_at":"2026-08-14T14:36:12.703974Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.688046Z","title":"This network only sees the word vectors when consuming the lattice structure","venue":null,"work_id":"affaf867-8b63-471f-9ad4-3fd1156fdf4c","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.620843Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:e45fb999f67a5d5977bc8994fa8ee3cfd962487dad08377fd4423420dd1a9403","observation_id":"b32caa0d-066c-4518-b0c1-d10d14c2ab8d","resolution":{"observed_at":"2026-08-14T14:36:12.691744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T14:36:12.676127Z","title":"The confidences are concatenated to the word vector inputs","venue":null,"work_id":"138a427e-30d1-4dfa-984f-aa0676574bee","year":null},"citing_paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T14:36:12.623865Z"},"links":{"citing_paper":"/paper/1908.02914"},"observation_digest":"sha256:e11c16e5b653386f8e86eb0f0f400c8ec413995ae2003abeb414613d5141dea0","observation_id":"b3698923-8aab-4304-8d6a-e2bcb6f533d3","resolution":{"observed_at":"2026-08-14T14:36:12.680468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.02914","last_updated":"2019-08-08T03:31:11Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T06:16:25.524366Z","submitted_at":"2019-08-08T03:31:11Z","title":"Mitigating Noisy Inputs for Question Answering"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":2,"verified_exact":0,"verified_fuzzy":29},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 1 inbound Pith citation observation for arXiv:1908.02914."}