{"as_of":"2026-08-16T17:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c7693f4d5f20de10e8f7b3c9ae292185c148441ce1cdd77c0b88e7ad01ae350c","coverage":[{"denominator":45,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":45,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T13:43:01.950337Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.05601/citation-record","integrity":"/paper/1908.05601/integrity","json":"/paper/1908.05601/citation-record.json","paper":"/paper/1908.05601"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:43:03.015884Z","title":"Methods for interpreting and understanding deep neural networks,","venue":null,"work_id":"ec561fb4-970e-40c5-803b-52d3b64b3a18","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.628900Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:6e6701b1bd4da4a96d78e3d9581eb7a143207b29e69661e26fbc225512aede56","observation_id":"9398a4ec-1d00-4f91-99e9-c7fa612facd8","resolution":{"observed_at":"2026-08-14T13:43:03.024624Z","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":"2026-08-14T13:43:02.996229Z","title":"Techniques for interpretable machine learning,","venue":null,"work_id":"2932d16b-771e-4e18-a45c-5830a346569e","year":2019},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.635333Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:6419893fe5e108925e2c3d31736de566e820e51a5d8c97b50ea1b965c7130038","observation_id":"c2c08eb8-4c4f-4423-b833-3097ab08a571","resolution":{"observed_at":"2026-08-14T13:43:03.002671Z","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":"2026-08-14T13:43:02.974630Z","title":"Towards explanation of dnn-based prediction with guided feature inversion,","venue":null,"work_id":"eb8eacbe-79c3-4ee3-87b3-e6188ff1cf67","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.641085Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:1a6038b4a084ea09326a883d1bae624e7a57b0fa4c885ddc52557f33e8e6746e","observation_id":"3982acbc-8eb3-46c3-9d99-a8487aeeeeec","resolution":{"observed_at":"2026-08-14T13:43:02.981394Z","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":"2026-08-14T13:43:02.952116Z","title":"On attribution of recurrent neural network predictions via additive decomposition,","venue":null,"work_id":"51b5f9ef-1566-40c6-930a-7e728ef3fc00","year":2019},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.647675Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:307a862916f0090d1972fc219177bdb07995cd4bcad3ee69c5637e1389bed64f","observation_id":"6526cbda-4820-4619-b4b0-90b9853a620c","resolution":{"observed_at":"2026-08-14T13:43:02.959705Z","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":"2026-08-14T13:43:02.928646Z","title":"Learning credible models,","venue":null,"work_id":"b316e5f2-7b6d-4b83-8f5d-c478486ca872","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.654013Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5ccd9fcb7e8af63877d65c2b607b31618745101b63dc358063d0eb35516c2c9c","observation_id":"43dbd611-4fc8-4678-bc0f-9b0a06ffeda1","resolution":{"observed_at":"2026-08-14T13:43:02.935000Z","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":"2026-08-14T13:43:02.909402Z","title":"Did the model understand the question?","venue":null,"work_id":"16d49075-211a-403d-8dbe-4d06da5629a1","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.659974Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:06df67a81056da880b69d9b30544563000374037a8682f2452876696af22bb29","observation_id":"2811908e-cd5d-42d3-96d5-5123cbe845f8","resolution":{"observed_at":"2026-08-14T13:43:02.915849Z","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":"2026-08-14T13:43:02.889767Z","title":"Does it care what you asked? understanding importance of verbs in deep learning qa system,","venue":null,"work_id":"bbd91f6e-5e99-4df9-86f9-d5d3b9896dfc","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.667146Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:b07b130f46707abdebe0e54a1472a9c432df6d7a0a45fb9ca66e8a2dbd3592c7","observation_id":"d87631ca-c017-4627-91e6-6cc815d83864","resolution":{"observed_at":"2026-08-14T13:43:02.897871Z","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":"2026-08-14T13:43:02.866916Z","title":"Why should i trust you?: Explaining the predictions of any classifier,","venue":null,"work_id":"c3b37597-23b1-49f2-b6d7-402807d1b5dc","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.677077Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:ceb1feb3d3d6586528a1cb37e3448c414ee37c213741ee94169f58d55c065d79","observation_id":"a64acb46-1b91-42e0-a35c-064c743408a3","resolution":{"observed_at":"2026-08-14T13:43:02.873921Z","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":"2026-08-14T13:43:02.843291Z","title":"Annotation artifacts in natural language inference data,","venue":null,"work_id":"e368ffde-2633-40d4-8750-261b12d1a3f5","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.684682Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:87c34fe8b85efd059ff39aa118a1a05653067ca3cd82fa334b5d100eafef2305","observation_id":"b49fa706-797f-4dce-be4c-b5860d382410","resolution":{"observed_at":"2026-08-14T13:43:02.849278Z","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":"2026-08-14T13:43:02.826255Z","title":"Man is to computer programmer as woman is to homemaker? debiasing word embeddings,","venue":null,"work_id":"164c9775-57c7-4959-80c8-815c713df962","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.690414Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5eef9ae7188eb5f5f31b50c172a959279aaaa61ce21e71479cf20199018d30c9","observation_id":"97573f56-e70a-443f-ac8d-f5d0dc02b47f","resolution":{"observed_at":"2026-08-14T13:43:02.831596Z","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":"2026-08-14T13:43:02.809832Z","title":"Swag: A large-scale adversarial dataset for grounded commonsense inference,","venue":null,"work_id":"443ebca6-c8d4-4184-85c5-ab1813586197","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.695833Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:9b80481cd300f5631213de8ac38898eb7cc4a5ec95057dd3afda495cb260706d","observation_id":"ce46a128-d364-43a7-856b-705e431ff1a9","resolution":{"observed_at":"2026-08-14T13:43:02.815309Z","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":"2026-08-14T13:43:02.786501Z","title":"Harnessing deep neural networks with logic rules,","venue":null,"work_id":"a8b92072-7ac0-43e7-b3b3-7fe7d2fbc838","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.701565Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:cde342e984ed9688b5ab79c726be7e72108d64d12adddc8d0a55cd170bd92e75","observation_id":"dbee6eb1-2033-4ae6-932b-3caef965ee6f","resolution":{"observed_at":"2026-08-14T13:43:02.795790Z","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":"2026-08-14T13:43:02.761882Z","title":"Knowledgeable reader: Enhancing cloze- style reading comprehension with external commonsense knowledge,","venue":null,"work_id":"9616a0cb-64dd-480f-9788-4ec8b23edc49","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.706525Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:f83d9375e7bb0a2de1a432d8054ebc0fd196f072758d38c861b6cc42a19388fc","observation_id":"f436f5fd-ad9b-4e7f-b3b1-a55df422c657","resolution":{"observed_at":"2026-08-14T13:43:02.767154Z","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":"2026-08-14T13:43:02.745259Z","title":"Rationale-augmented convo- lutional neural networks for text classification,","venue":null,"work_id":"49c38ede-6b4a-4b1c-aec5-065d5e1a61f7","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.711458Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:bc99b857bac255ba07778b43a01baa23fe79ba367b51b48311d76a94a86985c7","observation_id":"fd9e232f-24cb-41fc-8106-ebee45eac9ed","resolution":{"observed_at":"2026-08-14T13:43:02.750827Z","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":"2026-08-14T13:43:02.727704Z","title":"Using annotator rationales to improve machine learning for text categorization,","venue":null,"work_id":"42f021c9-7925-4372-bce6-0d396ba52661","year":2007},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.716953Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:278f4cd14a39a34e3c72005568a182aeeb051b302ce8e44a45064e33df670e62","observation_id":"64e6a360-744e-467b-a040-3ddbcdf85035","resolution":{"observed_at":"2026-08-14T13:43:02.733111Z","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":"2026-08-14T13:43:02.710242Z","title":"Rationalizing neural predictions,","venue":null,"work_id":"8a2d7be8-17d6-4a18-8a77-10d483798670","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.722919Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:96f45bfbe3cd211bd7a55090464b3cb863013d93793cb971765612fd434d3e67","observation_id":"85a30795-218f-4cf1-aefd-4bb9bd079dab","resolution":{"observed_at":"2026-08-14T13:43:02.716160Z","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":"2026-08-14T13:43:02.691897Z","title":"Annotator rationales for visual recogni- tion,","venue":null,"work_id":"401df473-9ba9-401c-bf34-fc9ce35ab28b","year":2011},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.733065Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:1d4a026a4d6263a98a15b6bf34742321148871244327d3a199a24ad77d0a41cc","observation_id":"fe50bf51-b741-492e-941d-ab1e3a28f3c3","resolution":{"observed_at":"2026-08-14T13:43:02.697390Z","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":"2026-08-14T13:43:02.674808Z","title":"Why is that relevant? collecting annotator rationales for relevance judgments,","venue":null,"work_id":"a38644fc-ed77-4b62-bb37-d5a4268c0498","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.740295Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:b36c9de348f486307ef505b36af5368828ff89f2f0be6facabbc474df8c6608d","observation_id":"8ae775d4-4f36-4340-830a-ef5f101cde79","resolution":{"observed_at":"2026-08-14T13:43:02.679758Z","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":"1702.08608","last_updated":"2017-03-02T19:32:10Z","snapshot_observed_at":"2026-08-13T03:10:58.738032Z","submitted_at":"2017-02-28T02:19:20Z","title":"Towards A Rigorous Science of Interpretable Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.08608","snapshot_observed_at":"2026-08-14T13:43:01.747387Z","title":"Towards a rigorous science of interpretable machine learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.747387Z"},"links":{"cited_paper":"/paper/1702.08608","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:3632894eba89085872667c2e9776c6da348cdc9c97f82972f846b804d7efa373","observation_id":"a6144d7c-4145-4371-8c7a-dfdf3504985a","resolution":{"observed_at":"2026-08-14T13:43:01.747387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.06831","last_updated":"2019-08-15T21:13:50Z","snapshot_observed_at":"2026-08-14T16:05:34.661041Z","submitted_at":"2019-07-16T04:25:39Z","title":"Evaluating Explanation Without Ground Truth in Interpretable Machine Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.06831","snapshot_observed_at":"2026-08-14T13:43:01.753992Z","title":"Evaluating explanation without ground truth in interpretable machine learning,","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.753992Z"},"links":{"cited_paper":"/paper/1907.06831","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5b386b004480866f2e4f84f5143bccd1a59dd3b58f6c3d0be195b0e22efa71f9","observation_id":"d2e34ff0-179d-4709-928d-f16bda6e0e87","resolution":{"observed_at":"2026-08-14T13:43:01.753992Z","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":"2026-08-14T13:43:02.655662Z","title":"Representation interpretation with spatial encoding and multimodal analytics,","venue":null,"work_id":"4803dde1-2aaa-440b-9bca-45e4dd944a7e","year":2019},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.761343Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:6278c9c86191243bfc0e40a5e0b8bede7669859729cb84b7390d30542f9d2a8e","observation_id":"d5e88078-87ef-4679-b73d-086f79be2548","resolution":{"observed_at":"2026-08-14T13:43:02.662550Z","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":"2026-08-14T13:43:02.631390Z","title":"Don’t just assume; look and answer: Overcoming priors for visual question answering,","venue":null,"work_id":"25a59469-0a76-471a-b790-855bedd1a078","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.770460Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:72c7f4965c70889c2771b60601fc73c998a356812f142581b08ca2b26137d9d3","observation_id":"ca09b4b7-1cc0-4c90-a2ab-6d2336e49fc5","resolution":{"observed_at":"2026-08-14T13:43:02.640757Z","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":"2026-08-14T13:43:02.607562Z","title":"Women also snowboard: Overcoming bias in captioning models,","venue":null,"work_id":"dd33c65b-dad0-4e02-8aeb-42ca736ffeb0","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.781181Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:6cdad671fca057f197751c0e951c50e49bf369075cc1996f23d1155bb656f775","observation_id":"669e311d-a5cf-476b-b1f9-22fe7bebeedf","resolution":{"observed_at":"2026-08-14T13:43:02.615464Z","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":"2026-08-14T13:43:02.586411Z","title":"Overcoming language priors in visual question answering with adversarial regularization,","venue":null,"work_id":"2fc8ecc8-2aeb-4355-9d82-0205abcfbb1f","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.790361Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:a056a04a05df38c28dee373bb0b7d776f71932500b8bfc066871e370f6b740e7","observation_id":"d1accdcc-a105-4644-9705-b9a9c3fcff03","resolution":{"observed_at":"2026-08-14T13:43:02.593799Z","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":"2026-08-14T13:43:02.565196Z","title":"Know what you don’t know: Unan- swerable questions for squad,","venue":null,"work_id":"2184cff1-ba72-41f5-bc98-0e4295c94d1c","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.798345Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5a447b40b134b85b382ddeaee561963f6b7607746db4c13794c86e3ef686e1d1","observation_id":"6a68f736-d8f4-4743-baf5-709280fdfe44","resolution":{"observed_at":"2026-08-14T13:43:02.572358Z","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":"2026-08-14T13:43:02.529498Z","title":"Sequence classification with human attention,","venue":null,"work_id":"bb84f554-6b95-4473-a95d-5755efb1781e","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.806239Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:44ed60b31d40b19e5ddeba0f3183e443c953423eb23dbcc0f98c428b4182e972","observation_id":"e8feac95-5715-49e2-ac77-3a59048bd545","resolution":{"observed_at":"2026-08-14T13:43:02.546113Z","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":"2026-08-14T13:43:02.502518Z","title":"Deriving machine attention from human rationales,","venue":null,"work_id":"0f9f81c6-174c-4ead-8b1f-731ef35d76e7","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.811862Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:86696f5194cb658e33a135b0ceb14d90d9ec08c36e48db34f40176ab51b1261b","observation_id":"665bac2c-3242-415f-a81d-fc05136a7eb6","resolution":{"observed_at":"2026-08-14T13:43:02.509750Z","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":"1612.08220","last_updated":"2017-01-10T01:40:51Z","snapshot_observed_at":"2026-08-14T21:23:47.203647Z","submitted_at":"2016-12-24T21:36:07Z","title":"Understanding Neural Networks through Representation Erasure","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.08220","snapshot_observed_at":"2026-08-14T13:43:01.820689Z","title":"Understanding neural networks through representation erasure,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.820689Z"},"links":{"cited_paper":"/paper/1612.08220","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:a2663f471d330e50aec17818c1d080e3b74c96e005c1c2a2d032f45f82b96fc1","observation_id":"dff11c80-30d8-4965-86cd-55047b353cda","resolution":{"observed_at":"2026-08-14T13:43:01.820689Z","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":"2026-08-14T13:43:02.474354Z","title":"Representation of linguistic form and function in recurrent neural networks,","venue":null,"work_id":"7fe76cde-72ae-4188-ba8f-301ecf85bdb7","year":2017},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.829589Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:556a7dffc2c999935062c14d554926e534d74e35f6fd31cfc0df1933d435c475","observation_id":"7aca45db-bb34-4d89-9086-13dca70963cc","resolution":{"observed_at":"2026-08-14T13:43:02.481373Z","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":"2026-08-14T13:43:02.444927Z","title":"Interpretable structure induc- tion via sparse attention,","venue":null,"work_id":"f3d5d3a7-e982-4c95-aea7-ac6a9b0fc6ae","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.844903Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5c6707411372edaf640e0c8f7ed7a4f511d8777fbf7f07b72c255029f226f30b","observation_id":"f9aa8bbb-95f1-42f2-897d-e25b4ce6883a","resolution":{"observed_at":"2026-08-14T13:43:02.456917Z","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":"2026-08-14T13:43:02.420638Z","title":"Sparse and constrained attention for neural machine translation,","venue":null,"work_id":"0040856f-a18e-4a9f-81a1-f22fb8659ca2","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.850565Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:d389d0bb4f44ae68733dad7c8ede4462e49b03e0e87f4501edd52250452e045e","observation_id":"af9c35bb-1ed1-4fee-ae83-959b52b0ce25","resolution":{"observed_at":"2026-08-14T13:43:02.426960Z","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":"1606.03490","last_updated":"2017-03-06T08:51:10Z","snapshot_observed_at":"2026-08-14T21:53:14.447761Z","submitted_at":"2016-06-10T21:28:47Z","title":"The Mythos of Model Interpretability","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.03490","snapshot_observed_at":"2026-08-14T13:43:01.856386Z","title":"The mythos of model interpretability,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.856386Z"},"links":{"cited_paper":"/paper/1606.03490","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:053635b6c4f26e8d1ec0938cc71c538d6ae39f43ffccdb56f38f1f5b05ed99d2","observation_id":"103196ff-25d5-402c-ba14-72bff3336875","resolution":{"observed_at":"2026-08-14T13:43:01.856386Z","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":"2026-08-14T13:43:02.394004Z","title":"Convolutional neural networks for sentence classification,","venue":null,"work_id":"e3ea6414-e227-4742-a069-d3ddf59cec36","year":2014},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.862725Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:f452eabaf07d13012300d24edfaa7a600fcd065f516884baaa140b3c26ca8a2d","observation_id":"fc543a8e-fa96-459c-91f4-d07173d1cade","resolution":{"observed_at":"2026-08-14T13:43:02.402932Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:43:01.870256Z","title":"Long short-term memory,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.870256Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:321fd41942373377f1dc0375a6bba704d24369f526e3d70f3539ae833ad3b19e","observation_id":"990acce9-1962-455f-990f-61feca43b289","resolution":{"observed_at":"2026-08-14T13:43:01.870256Z","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":"2026-08-14T13:43:02.357809Z","title":"A structured self-attentive sentence embedding,","venue":null,"work_id":"29cd05ff-2645-4977-a9e1-9f74fcaee6c1","year":2017},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.876267Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:be51f24685b3ce9a2bb04d9ed6efc15a5f90955d7366757b44165d87e1d40b6a","observation_id":"fef57d69-b41b-4186-ab95-6f2ee507b2f8","resolution":{"observed_at":"2026-08-14T13:43:02.363156Z","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":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-08-14T22:57:08.956233Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-14T13:43:01.883934Z","title":"Distilling the knowledge in a neural network,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.883934Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:e9ebf57ce934e5e04d858450915c30b8d2b5dc7c9238eb374c392089bfad64c0","observation_id":"a0360e56-1f23-4dc5-8c11-a7c595ec1cc2","resolution":{"observed_at":"2026-08-14T13:43:01.883934Z","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":"2026-08-14T13:43:02.338655Z","title":"A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts,","venue":null,"work_id":"e2b6d0fb-56bc-4e9d-a978-e15f44b41cc4","year":2004},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.892795Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:004e8e638f7ab01732af4bf2175250d1369ea44eaa265ac502a57c5bedb3b338","observation_id":"833cfa16-fc50-43ff-b612-531238a7bb54","resolution":{"observed_at":"2026-08-14T13:43:02.344649Z","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":"2026-08-14T13:43:02.315072Z","title":"Learning attitudes and attributes from multi-aspect reviews,","venue":null,"work_id":"d60ed392-3993-447c-bdef-1d0dfe091569","year":2012},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.899030Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:e60195504249d0abe1bf8a2562c7635306cce8d9010127d030ababb3f251a4dd","observation_id":"7dc29e53-3d23-4f49-aed6-a65ea321803d","resolution":{"observed_at":"2026-08-14T13:43:02.322977Z","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":"2026-08-14T13:43:02.288926Z","title":"Improving neural machine translation models with monolingual data,","venue":null,"work_id":"488bcbfe-502e-49f1-a4b8-a4479b2029d9","year":2016},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.908399Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:b2106394a45dda93e7b61260ae97c4fca592d0577a77b49adb2b5fda8b4f0914","observation_id":"8ab4671b-d419-4aac-b4fb-f4649586a963","resolution":{"observed_at":"2026-08-14T13:43:02.295790Z","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":"1804.06189","last_updated":"2018-04-17T12:16:25Z","snapshot_observed_at":"2026-08-14T19:25:06.811024Z","submitted_at":"2018-04-17T12:16:25Z","title":"Investigating Backtranslation in Neural Machine Translation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.06189","snapshot_observed_at":"2026-08-14T13:43:01.917049Z","title":"Investigating backtranslation in neural machine translation,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.917049Z"},"links":{"cited_paper":"/paper/1804.06189","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:5ee2cf18421370d579764dc87d05b8bc7480d512fa3a5b93319a168cb6a2f529","observation_id":"9e76bc8c-2bff-40b8-a472-fea2bda7ad84","resolution":{"observed_at":"2026-08-14T13:43:01.917049Z","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":"2026-08-14T13:43:02.264730Z","title":"Distributed representations of words and phrases and their composition- ality,","venue":null,"work_id":"f14517d1-63a5-42e3-812b-f016c87296f9","year":2013},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.924392Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:6739de4412d4996aa72bd1c88db4b9dd3e784f178c1f49e841e0c69c5a69b228","observation_id":"b605116c-3a03-4736-b472-cabeec635abe","resolution":{"observed_at":"2026-08-14T13:43:02.270807Z","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":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-14T18:51:16.666127Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-14T13:43:01.930840Z","title":"Adam: A method for stochastic optimization,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.930840Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:c1202e0caf3525d68f813732fe3286e0f6b69421c3b0a2709b64e492cd1018fc","observation_id":"c0a36f56-8645-402d-9024-b50e5b236361","resolution":{"observed_at":"2026-08-14T13:43:01.930840Z","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":"2026-08-14T13:43:02.243924Z","title":"Dropout: a simple way to prevent neural networks from overfit- ting,","venue":null,"work_id":"871edad3-b97c-4cc7-8a5f-63cbe3fee63b","year":2014},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.937472Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:3116417a01b7ac9581de02370a65129259dacd30ac5da6df375a6667c1cafef2","observation_id":"00b2a2ac-e2ff-46b0-a1f8-dfdb4cc7916c","resolution":{"observed_at":"2026-08-14T13:43:02.250245Z","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":"2026-08-14T13:43:02.220490Z","title":"Adversarially regularising neural nli models to integrate logical background knowledge,","venue":null,"work_id":"ca4224d7-e9ac-41ba-b99d-07e6e1b6d2ac","year":2018},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.944830Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:b5cffb6fdc105957cec83e13ced63d2f58c4ab47779eb6b9fab6f78d160d88f0","observation_id":"d7dd4adb-1de6-4e88-97d4-2b61f72967c9","resolution":{"observed_at":"2026-08-14T13:43:02.227664Z","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":"2026-08-14T13:43:02.199389Z","title":"Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales,","venue":null,"work_id":"3e6988df-61ee-4b32-9ac4-4bd259f26d58","year":2005},"citing_paper":{"arxiv_id":"1908.05601","last_updated":"2019-08-13T12:57:26Z","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T13:43:01.950337Z"},"links":{"citing_paper":"/paper/1908.05601"},"observation_digest":"sha256:8117cad6a523c1743cc64c9ec13f258e558a361010ec2d56736118cf6012516a","observation_id":"79ed63a0-f779-407c-8625-de65d3f20868","resolution":{"observed_at":"2026-08-14T13:43:02.207333Z","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":"1908.05601","last_updated":"2019-08-13T12:57:26Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T13:34:56.837451Z","submitted_at":"2019-08-13T12:57:26Z","title":"Learning Credible Deep Neural Networks with Rationale Regularization"},"reference_resolution":{"displayed":45,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":37},"total_outbound_references":45},"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 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:1908.05601."}