{"as_of":"2026-08-15T00:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4b4572c9e9388ba7c40a4b2a56a4a516092e0a3b73c5abab4534bb552835f458","coverage":[{"denominator":286,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:31:40.782935Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2506.23990/citation-record","integrity":"/paper/2506.23990/integrity","json":"/paper/2506.23990/citation-record.json","paper":"/paper/2506.23990"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.184739Z","title":"A Graph-Theoretic Embedding- Based Approach for Rumor Detection in Twitter","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.184739Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:1b48bf3b8a4fbafd4c2d1eb7a35bf9120f68679d95420534844e4af45aea6b04","observation_id":"8e863a5b-50ae-4150-a362-2b479b70a0ed","resolution":{"observed_at":"2026-08-06T21:31:35.184739Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.260616Z","title":"Unsupervised Domain Clusters in Pretrained Language Models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.260616Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:c664c678fe48fb3d0b45d49a1ced430674cabd07d06509d698defd8fe7693dea","observation_id":"fe1045fc-b6e5-4707-b192-2fe8dcc5991a","resolution":{"observed_at":"2026-08-06T21:31:35.260616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.06402","last_updated":"2021-09-09T11:41:26Z","snapshot_observed_at":"2026-08-11T10:21:43.755532Z","submitted_at":"2020-09-10T13:39:49Z","title":"Time-Aware Evidence Ranking for Fact-Checking","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.06402","snapshot_observed_at":"2026-08-06T21:31:35.331398Z","title":"Time-Aware Evidence Ranking for Fact- Checking","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.331398Z"},"links":{"cited_paper":"/paper/2009.06402","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:85caf0018fce37651f809bc81251b0cf72730da4183d56a51f0c63146b7364ee","observation_id":"78102dc2-6021-4397-9d09-b94ea6404500","resolution":{"observed_at":"2026-08-06T21:31:35.331398Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.09816","last_updated":"2023-02-15T10:01:31Z","snapshot_observed_at":"2026-08-13T20:43:53.414882Z","submitted_at":"2020-12-17T18:34:45Z","title":"Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.09816","snapshot_observed_at":"2026-08-06T21:31:35.399144Z","title":"Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.399144Z"},"links":{"cited_paper":"/paper/2012.09816","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:e35adc38b6e98ffed8f89d8f425b7ae2b0e6de50e7af3bff35cd4c23696afaf7","observation_id":"14de3fd5-95fe-467c-8942-efefb6e14fdb","resolution":{"observed_at":"2026-08-06T21:31:35.399144Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.443991Z","title":"S., T HORNE , J., V LACHOS , A., C HRISTODOULOPOU - LOS, C., C OCARASCU , O., AND MITTAL , A","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.443991Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:bd061ee6a74d36f6a022c7e8613497eb00e7d2f0980b37254995405995aadca4","observation_id":"90e96357-7dda-4067-953c-5d0762cd6603","resolution":{"observed_at":"2026-08-06T21:31:35.443991Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.505918Z","title":"Construction of the Literature Graph in Semantic Scholar","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.505918Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:e4b76aedea1e24b17c522b23c61ac7c491f629ffe5f03631e911e85bf522ee47","observation_id":"ff52d578-60a4-48cc-a8dd-d061f758bf0a","resolution":{"observed_at":"2026-08-06T21:31:35.505918Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.578512Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.578512Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2aba132f9afb6a620a6dc9c2751c89e2d775de4161a3332498a25edb6fe0c63f","observation_id":"51105446-3b9c-419a-8f5f-b105b93e337a","resolution":{"observed_at":"2026-08-06T21:31:35.578512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.05542","last_updated":"2018-08-08T12:51:21Z","snapshot_observed_at":"2026-08-14T18:43:25.331602Z","submitted_at":"2018-08-08T12:51:21Z","title":"Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthiness","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.05542","snapshot_observed_at":"2026-08-06T21:31:35.660803Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.660803Z"},"links":{"cited_paper":"/paper/1808.05542","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:74691a489c350791b1e4d0eedb0901bec179b89ff496cf0eba09935a8bfeb153","observation_id":"16a3b997-410e-4b50-9860-61493461d102","resolution":{"observed_at":"2026-08-06T21:31:35.660803Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.720088Z","title":"G., L IOMA , C., AND AUGENSTEIN , I","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.720088Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:55f198ca50a5616d67efd2f52941aae33ec169c22c6f175c3092dda096d77bbd","observation_id":"6bb3a664-2530-42f1-bd05-45eb84b5ee44","resolution":{"observed_at":"2026-08-06T21:31:35.720088Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.791169Z","title":"G., L IOMA , C., AND AUGENSTEIN , I","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.791169Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:3eac4ea93245c28c74c75357ffda4c1fa30c1eeeb95b0ae39f44a30dc4a20519","observation_id":"51825670-93c9-4033-be8a-781aa1ebe7f1","resolution":{"observed_at":"2026-08-06T21:31:35.791169Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.859416Z","title":"Generating Label Cohesive and Well- Formed Adversarial Claims","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.859416Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:9364b6e0f340bab613c0acc37ac318aef859833f46ae4ff81e462a730d231baf","observation_id":"a361114d-16ba-45de-aef5-6c183dc3523d","resolution":{"observed_at":"2026-08-06T21:31:35.859416Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:35.916953Z","title":"SemEval 2017 Task 10: ScienceIE-Extracting Keyphrases and Relations from Scientific Publications","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:35.916953Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:da0a920959582f4c97ddf027dff022287ad3beb551fe540dbf7fd43458f8205a","observation_id":"a974ce66-0cc2-4a57-aa5e-d4b5179f9fd3","resolution":{"observed_at":"2026-08-06T21:31:35.916953Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.005555Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.005555Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:e281344593445c00156c6daed3672b9082ab7029dbc385acd936f58cecd04019","observation_id":"ed51ab42-ea19-4445-8b6a-405873b018ee","resolution":{"observed_at":"2026-08-06T21:31:36.005555Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.077174Z","title":"Stance Detection with Bidirectional Conditional Encoding","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.077174Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6cdd5a48987d9a1098bc8ddece54e4ab4afd302f01f5f1eb12dd6e4446045a29","observation_id":"76ef21c1-e47d-4eb8-ad41-a68bb684ecc2","resolution":{"observed_at":"2026-08-06T21:31:36.077174Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.136225Z","title":"Multi-Task Learning of Keyphrase Boundary Classi- fication","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.136225Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:26f09ca7c105d5716033b48ae067274cca7928448b4d2db9caa2f439031351e7","observation_id":"34ffc43e-c529-41c0-8f70-efb627a16756","resolution":{"observed_at":"2026-08-06T21:31:36.136225Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.227823Z","title":"A., AND REINECKE , K","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.227823Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:c2ff99cc6ce17975aa02aff9b441e3ccac370cdeeca0d57293032b4625890269","observation_id":"59bc2145-2fc1-411c-8c5d-adb65fa73b07","resolution":{"observed_at":"2026-08-06T21:31:36.227823Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.301169Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.301169Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:01500398ca955672a90f1c7bf16f7857145c54627324c808d1713657720ccd01","observation_id":"d104c163-8e69-4d33-9613-a95dc338883a","resolution":{"observed_at":"2026-08-06T21:31:36.301169Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.384166Z","title":null,"venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.384166Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ad1ebf6136c6aa912e113b5ecae216e6c234b91673df03c660d5e01bccf5f82b","observation_id":"3528c1ae-94e3-4df6-b310-53bd099eaab1","resolution":{"observed_at":"2026-08-06T21:31:36.384166Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.470446Z","title":"D., W RIGHT , D., K ATSIS, Y., KIM, H.-C., S WAFFORD , A","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.470446Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ac71cd01572e79459c31bab0955cacfe5d2f7f0a8023d23034d2caed4c45694e","observation_id":"9f7f23bc-1eba-415b-aeea-93270157a6be","resolution":{"observed_at":"2026-08-06T21:31:36.470446Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.579518Z","title":"M., M ASON , W","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.579518Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:9300d69769e7d75d12c491d61e58bcbaab8c8401c056d5ce9fed91d0583258e1","observation_id":"3b5f0ce6-f119-4d2c-8693-be0f8f1ff404","resolution":{"observed_at":"2026-08-06T21:31:36.579518Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.635225Z","title":"R., M ÀRQUEZ , L., M OSCHITTI , A., AND NAKOV, P","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.635225Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:58c57dd7bb128ede8cfa9695e992033efc701189286f2e08667165e0089b8d19","observation_id":"e055ab92-e2db-4376-bdf1-7b458242589f","resolution":{"observed_at":"2026-08-06T21:31:36.635225Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.693091Z","title":"CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.693091Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:3e2b8f3d67731f8c1a2edc35cc65216405701511a9b40ac81a18d67f60cdaa62","observation_id":"729abbde-b03b-48a7-8862-82c4c0df8dae","resolution":{"observed_at":"2026-08-06T21:31:36.693091Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.744540Z","title":"Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.744540Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:efb8f6e086253752bef7a6d1278f53ee0431f39ac3bb253e4995e1e37a85e721","observation_id":"2136d1f1-52f4-43c4-8ce4-2183093437be","resolution":{"observed_at":"2026-08-06T21:31:36.744540Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.805106Z","title":"L., K OMPA, B., S CHMALTZ , A., F RIED, I., W EBER , G","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.805106Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:8c559028915add12a7f41bf3c5c3ff6fca1095395d9c9c9d23bd88e1ee1196fa","observation_id":"8403d0f7-a02d-4248-982e-b6e5bdbe7756","resolution":{"observed_at":"2026-08-06T21:31:36.805106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.04820","last_updated":"2020-05-18T10:33:23Z","snapshot_observed_at":"2026-08-14T18:00:34.754841Z","submitted_at":"2018-11-12T16:00:36Z","title":"Learning from positive and unlabeled data: a survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.04820","snapshot_observed_at":"2026-08-06T21:31:36.871560Z","title":"Learning from positive and unlabeled data: A survey","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.871560Z"},"links":{"cited_paper":"/paper/1811.04820","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:b5b487b2693137b2ca72c19a8da382f377d68f758a39da8d1e775188abc5709b","observation_id":"6eda7842-a828-47fa-9fc9-f827e701533d","resolution":{"observed_at":"2026-08-06T21:31:36.871560Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:36.950184Z","title":"SciBERT: A Pretrained Language Model for Scientific Text","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:36.950184Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:b9e0bc739bac574c8aeefbe7fe14a894e709a2a50d3a6c49d8c5770a9b48df1d","observation_id":"dffdcf94-2794-49fd-bc85-1f403d8fffa0","resolution":{"observed_at":"2026-08-06T21:31:36.950184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05150","last_updated":"2020-12-02T17:52:35Z","snapshot_observed_at":"2026-07-31T17:17:17.205582Z","submitted_at":"2020-04-10T17:54:09Z","title":"Longformer: The Long-Document Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05150","snapshot_observed_at":"2026-08-06T21:31:37.082011Z","title":"E., AND COHAN , A","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.082011Z"},"links":{"cited_paper":"/paper/2004.05150","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:0a3b7c5abb4e6193b79a3f1cb4cf2a4edbf3023d0b49ab357c8a51fbbdf5af13","observation_id":"11fce6b6-5894-41ac-9791-a01ca6902be2","resolution":{"observed_at":"2026-08-06T21:31:37.082011Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.254918Z","title":"NLTK: The Natural Language Toolkit","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.254918Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:53bd2cc697b0bee93cd53c1277f1574efb4d1edac64fb0033e54c516298a7ee1","observation_id":"ddfe4559-060d-4995-8325-2bfb1d73b2c1","resolution":{"observed_at":"2026-08-06T21:31:37.254918Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.428266Z","title":"J., G IBSON , B., J OSEPH , M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.428266Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a589e0496946380eb73d2cc69945064452c05267c6796f516d263ecd180af827","observation_id":"5134b888-2ad1-4f43-afc9-b2d962aa7834","resolution":{"observed_at":"2026-08-06T21:31:37.428266Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.498896Z","title":"Biographies, Bollywood, Boom-Boxes and Blenders: Domain Adaptation for Sentiment Classification","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.498896Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:833dcf857888d18a60105efa832491ba7fd2de705a71dd1134847a1f5ac1475c","observation_id":"f290205a-fa63-4177-9bf3-84c1fcc501b0","resolution":{"observed_at":"2026-08-06T21:31:37.498896Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.560366Z","title":"Domain Adaptation with Structural Cor- respondence Learning","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.560366Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:38e3676c0ce6db71a6d4d07ef47b30dc58fec8afc8d678112a695710cb992661","observation_id":"acaa0220-d8da-4389-9113-0e6e69318f90","resolution":{"observed_at":"2026-08-06T21:31:37.560366Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.624531Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.624531Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:70590b3b4438753c9438ca4faa29f6bfd677b8ecd49186fdf1fbbed56f4dcb06","observation_id":"6429b0d9-17b7-4b53-a0f4-cdaedeaada25","resolution":{"observed_at":"2026-08-06T21:31:37.624531Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.724970Z","title":"The Unified Medical Language System (UMLS): integrating biomedical terminology","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.724970Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:3826fcf53c03a86b534191fd3bba9634bbb511df78ea4799d85ca0aeea0f4a02","observation_id":"7e907dc5-679e-4e4f-8a69-98055a4e8f41","resolution":{"observed_at":"2026-08-06T21:31:37.724970Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.816444Z","title":"Explainable assess- ment of healthcare articles with QA","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.816444Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:e182f2341686a0896be89d66197314afc1ba1eafe83ffac0fe2a3783889f7ab3","observation_id":"f6c0b2e4-7f53-42e1-91dc-a5627ce92874","resolution":{"observed_at":"2026-08-06T21:31:37.816444Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.909503Z","title":"Enriching Word Vectors with Subword Information","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.909503Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:4a445a5eda0f92d613f43c937edfc537ad9fe64410331c59f052b14ea7451e57","observation_id":"3e8844b3-af25-41ee-8133-2f8fca04983e","resolution":{"observed_at":"2026-08-06T21:31:37.909503Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:37.986402Z","title":"Inducing Relational Knowledge from BERT","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:37.986402Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:498536a89de33c44f44de1c3539318fe5326467b1887978b0b0ebfd5ad59846f","observation_id":"382198ef-fb4e-412b-8fbf-7c2307ff4c9a","resolution":{"observed_at":"2026-08-06T21:31:37.986402Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.025056Z","title":"R., A NGELI , G., P OTTS , C., AND MANNING , C","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.025056Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:254a91d9ac3d8260bc5f241a537717d91df0e3835749ff6517b0109f12c1d63a","observation_id":"0e938f0c-87dd-4af5-afa7-643627eaebbe","resolution":{"observed_at":"2026-08-06T21:31:38.025056Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.096021Z","title":"C., C HALLENGER , A., B OIVIN , J., B OTT, L., C HAMBERS , C","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.096021Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a14a7c80d85c7c6f0316500ee39ae633e8dca1ad50bec40e6ac45cfddcd2ff64","observation_id":"319b7119-ce6f-452b-8636-f1760927a374","resolution":{"observed_at":"2026-08-06T21:31:38.096021Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.159239Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.159239Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:47ee8be4aa95f0287bd13d578d46a8d7fc6c6dd6a6c7844af1f17666d286e65e","observation_id":"9cf0adae-1a2c-4424-8c3a-f5929abe94dd","resolution":{"observed_at":"2026-08-06T21:31:38.159239Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.237711Z","title":"S., I OANNIDIS , J., M OKRYSZ , C., N OSEK , B","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.237711Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:c7347e7c281baa834ebb9fae91c2b5d3764bab211c781dc4978220abcde2fbde","observation_id":"e192fda3-a627-4399-a443-562bbb83b941","resolution":{"observed_at":"2026-08-06T21:31:38.237711Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.254094Z","title":"YAKE! Keyword extraction from single documents using multiple local features.Inf","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.254094Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:06c4af3dcc418bd64e93f3bf67894cc61160397da1222aed60eda2836d9dffa3","observation_id":"dea98d87-8d36-4dae-b030-69b2c67786b7","resolution":{"observed_at":"2026-08-06T21:31:38.254094Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.355895Z","title":"Pubmed: the bibliographic database","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.355895Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:81cdf6069af7fcbd0869e39eb23d28e8d09b0c2f5e21fd43a1dd6e979aad3a83","observation_id":"cc332759-647d-4b21-9e53-89e8e231b11c","resolution":{"observed_at":"2026-08-06T21:31:38.355895Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.406703Z","title":"Multilevel Bayesian Models of Categorical Data Annotation","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.406703Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:52a152eaf9c792c1ff1d3583f4b80a7700ca666728ea79e5ca7be9c4bef3f8b6","observation_id":"c7fd8504-3d7c-492d-b6e1-5d40a78acd32","resolution":{"observed_at":"2026-08-06T21:31:38.406703Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.555472Z","title":"SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.555472Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:71924713f5f0b3922cd87d02cde1a5d364a6b5ccd0adc2d3a6cd2db263b1eb8f","observation_id":"cb2bf29e-c51d-4d04-a501-ef6f6fa8339c","resolution":{"observed_at":"2026-08-06T21:31:38.555472Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.696145Z","title":"K., F EIGENBLAT , G., H OVY, E","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.696145Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:b61e5f9c142294c4e81b05096d445c9c7f1bec6d9e190ef3a0cc753a7898ec58","observation_id":"1db32501-6a77-41ac-bf53-7487fdea2126","resolution":{"observed_at":"2026-08-06T21:31:38.696145Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.774152Z","title":"Decon- textualization: Making Sentences Stand-Alone","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.774152Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:f661fa04cf97ae7c280a26b490f48622d25b4f70153062a33a77e8d5010b1c8e","observation_id":"19ae7c82-fc2d-4183-9ad6-0510a54d363c","resolution":{"observed_at":"2026-08-06T21:31:38.774152Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.908736Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.908736Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:980844933748beb31fae74a9f847f08f216752525863239e7494a19b668e9d24","observation_id":"25e2a297-8d50-4598-bad4-0224f873e27d","resolution":{"observed_at":"2026-08-06T21:31:38.908736Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:38.943177Z","title":"Structural Scaffolds for Citation Intent Classification in Scientific Publications","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:38.943177Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:5c11d9d350aef4998605e14b5783dd8bacff9cd7541648903ed25d28b0a333d1","observation_id":"21a2c5c3-229c-4059-9492-b6c2e638f546","resolution":{"observed_at":"2026-08-06T21:31:38.943177Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.139842Z","title":"SPECTER: Document- level representation learning using citation-informed transformers","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.139842Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:58769462fc9b8ad5d4d67116745e0df39c287046c8ad4b4c82e632b755348f8c","observation_id":"db54222c-f0a5-443b-90b9-5124f4a3e39d","resolution":{"observed_at":"2026-08-06T21:31:39.139842Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.296781Z","title":"A supervised approach to extractive summarisation of scientific papers","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.296781Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ee026ea421e9bd0902665554b60634ae53f97a019670a7811b9f5062b7284330","observation_id":"d8701a84-a636-40c8-9352-5d7b370cebfd","resolution":{"observed_at":"2026-08-06T21:31:39.296781Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.366165Z","title":"Science reporting to the public: Does the message get twisted? CMAJ 170, 9 (2004), 1415–1416","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.366165Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:81c1dfe2949c18089d07d8de7d5ef8a9ef3805d9e34321d843ef3a0e19daf336","observation_id":"3f139284-6e7f-4f13-93ae-3e5c4cb54b66","resolution":{"observed_at":"2026-08-06T21:31:39.366165Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.457941Z","title":"Supervised Learning of Universal Sentence Representations from Natural Language Inference Data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.457941Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:8f09289784422c4cc3728da6a5b98ea6fc56a40ea6446e92718320524e620884","observation_id":"fd8ce4a4-8fe2-486a-b809-009fe429564d","resolution":{"observed_at":"2026-08-06T21:31:39.457941Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.603607Z","title":"The PASCAL Recognising Textual Entailment Challenge","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.603607Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:c35f97eb7565801e334e5061a94eaf63aae166f5b61d72fd96a9fb6ea85a4c47","observation_id":"ea0b10df-bfd3-45cd-98d2-3f4892e1bc00","resolution":{"observed_at":"2026-08-06T21:31:39.603607Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.691003Z","title":"Ginger cannot cure cancer: Battling fake health news with a comprehensive data repository","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.691003Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:5cc9aff9f09049bf7c94c7fb40e93d08bd561fe608dd692516101d9bfdc89af4","observation_id":"4c0359d5-2716-4e0f-ab91-485d8990bf5c","resolution":{"observed_at":"2026-08-06T21:31:39.691003Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.766669Z","title":"We Can Explain Y our Research in Layman’s Terms: Towards Automating Science Journalism at Scale","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.766669Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:92685e63af3a9e418346936ce7c51a96992f06c453642d56d0c11618e0669f56","observation_id":"3bff89b0-ae18-4e53-a933-953a1f82584c","resolution":{"observed_at":"2026-08-06T21:31:39.766669Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:39.896747Z","title":"Frustratingly Easy Domain Adaptation","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:39.896747Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6ba939a8548ffc247301929c397492620a03b7eecfcb0cb82e3bf302180182e8","observation_id":"353e5291-b505-466c-bfb1-042cbea7c288","resolution":{"observed_at":"2026-08-06T21:31:39.896747Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.012470Z","title":"P ., AND SKENE , A","venue":null,"work_id":null,"year":1979},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.012470Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:621099fbcd927411f7043e4f31cb70858e8eeee8cbd87e73848d08073965faa3","observation_id":"b7f0fbd6-915a-4152-a6c3-d3868082e3d8","resolution":{"observed_at":"2026-08-06T21:31:40.012470Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.121238Z","title":"Positive and Unlabeled Examples Help Learning","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.121238Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:1ade66e9387446b59a7c5f60a7f72595fe5c30001332834f29d17fd3b5277407","observation_id":"75f9dc21-6336-4ba1-9364-15d94e9e67d3","resolution":{"observed_at":"2026-08-06T21:31:40.121238Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.233965Z","title":"E., AND QUATTROCIOCCHI , W","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.233965Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2d64b7e3ca53be8b55e7549576f956eeea214fc222ccc2bcd4d43491e5717df9","observation_id":"200431ce-ac82-4510-8b31-124cf082ca09","resolution":{"observed_at":"2026-08-06T21:31:40.233965Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.02922","last_updated":"2018-09-11T00:38:25Z","snapshot_observed_at":"2026-08-14T18:31:08.502760Z","submitted_at":"2018-09-09T05:03:34Z","title":"Transforming Question Answering Datasets Into Natural Language Inference Datasets","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.02922","snapshot_observed_at":"2026-08-06T21:31:40.355060Z","title":"Transforming Question Answering Datasets Into Natural Language Inference Datasets","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.355060Z"},"links":{"cited_paper":"/paper/1809.02922","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:d782696825e7b59465efe4d2090c2ea21cbfe720ef255e6b02e18e0c0a6eaadd","observation_id":"2d8fa9ec-ec65-42ca-a20c-5f3d3c86bbae","resolution":{"observed_at":"2026-08-06T21:31:40.355060Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.535706Z","title":"PAC Learning From Positive Statistical Queries","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.535706Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ad4c16baef5ff7f3b7d60ca9c23f45d267517bb131fba04ba8d9646007ff5599","observation_id":"b614938c-ba0d-4387-849f-37d208d0d7fe","resolution":{"observed_at":"2026-08-06T21:31:40.535706Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.567100Z","title":"BERT: Pre-Training of Deep Bidi- rectional Transformers for Language Understanding","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.567100Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:34c35ece498268fef9758ecb789f65d27e28ddb882898752e6e9816390c01ce3","observation_id":"e72f89ac-91cc-43ba-9a34-ccf45e276e15","resolution":{"observed_at":"2026-08-06T21:31:40.567100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.06486","last_updated":"2021-11-23T01:12:57Z","snapshot_observed_at":"2026-08-13T19:40:20.871855Z","submitted_at":"2021-04-13T19:59:34Z","title":"MS2: Multi-Document Summarization of Medical Studies","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.06486","snapshot_observed_at":"2026-08-06T21:31:40.600678Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.600678Z"},"links":{"cited_paper":"/paper/2104.06486","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a2417f7aa63d49694b5836346f392216cc6874934ff265be6121d23c3ce1211c","observation_id":"33d64a73-0aca-45c4-81c1-c3cf2c2361f1","resolution":{"observed_at":"2026-08-06T21:31:40.600678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.03905","last_updated":"2019-12-21T13:02:43Z","snapshot_observed_at":"2026-08-14T17:04:47.288979Z","submitted_at":"2019-03-10T02:48:46Z","title":"Semantics Preserving Adversarial Learning","version":5},"cited_work":{"arxiv_id":"1903.03905","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.03905","snapshot_observed_at":"2026-08-06T21:31:42.292117Z","title":"Semantics Preserving Adversarial Learning","venue":"stat.ML","work_id":"12f77fc0-4b00-458e-8d06-ab2357d1c459","year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.611465Z"},"links":{"cited_paper":"/paper/1903.03905","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6576326807fd47dec0f8ba7d9979dcc233a2eb90676f21e6331594e4edee267d","observation_id":"17103ccb-55c7-4ae3-9589-8a8345b3dde7","resolution":{"observed_at":"2026-08-06T21:31:42.297099Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T21:31:40.618447Z","title":"I., L EAMAN , R., AND LU, Z","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.618447Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:824b632b09fe19932eadfb4dce232dcb0583f633bc208515a49197b593f72acb","observation_id":"f800b85e-8161-4fd7-be9d-bbda781d498e","resolution":{"observed_at":"2026-08-06T21:31:40.618447Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.623029Z","title":"Semi-supervised Domain Adaptation with Instance Constraints","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.623029Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ff037b955e7248e89c43288d66d456f12e97232cbcb96e14866881fa96d8f30d","observation_id":"762f8f3b-a01a-4da5-af12-c506a02446d6","resolution":{"observed_at":"2026-08-06T21:31:40.623029Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.628103Z","title":"C., N IU, G., AND SUGIYAMA , M","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.628103Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:b8b984f1b6fb1490c204ad4cd75ee0421c3b77c6f2986e84a91f397f56d5fa93","observation_id":"7b7690e4-568c-43fa-b6b3-9c3ce8202a31","resolution":{"observed_at":"2026-08-06T21:31:40.628103Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.632634Z","title":"Question Generation for Question Answer- ing","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.632634Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:f3209c337baa36c4e1243e32e8ef504f8c88bbc82f37e6030ae6eb3834fbfcbc","observation_id":"a11e240e-652b-4cae-ae66-955720e17b63","resolution":{"observed_at":"2026-08-06T21:31:40.632634Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.00537","last_updated":"2018-09-03T10:29:09Z","snapshot_observed_at":"2026-08-14T18:33:47.097850Z","submitted_at":"2018-09-03T10:29:09Z","title":"Crowdsourcing Semantic Label Propagation in Relation Classification","version":1},"cited_work":{"arxiv_id":"1809.00537","doi":null,"metadata_source":"pith","pith_arxiv_id":"1809.00537","snapshot_observed_at":"2026-08-06T21:31:42.270356Z","title":"Crowdsourcing Semantic Label Propagation in Relation Classification","venue":"cs.CL","work_id":"772fd722-a6aa-49cc-9015-7ff3aeea4cee","year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.637328Z"},"links":{"cited_paper":"/paper/1809.00537","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:44d58c0e36c845357e60b9f5fc365b744fa38d00227da5bdb1dfe89e3c51a38d","observation_id":"2435b784-8efe-4750-bb16-ebf79ef9cf45","resolution":{"observed_at":"2026-08-06T21:31:42.275081Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T21:31:40.642513Z","title":"HotFlip: White-Box Adversarial Examples for Text Classification","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.642513Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6e8b68f3b7f8295bd96fcd02c0956b26015b3c9a5ba878f345a1885bc499841a","observation_id":"1921c19b-01af-46bd-b36a-4d144b4addfe","resolution":{"observed_at":"2026-08-06T21:31:40.642513Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.646772Z","title":"Learning Classifiers From Only Positive and Unlabeled Data","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.646772Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:3a6851b0eef751561358103cc8cf843bfe537285d34a01ad37dd59fc57730e08","observation_id":"44d792b9-9ef4-4895-8bc0-c273db87623a","resolution":{"observed_at":"2026-08-06T21:31:40.646772Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.651370Z","title":"Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.651370Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:628f8fc2aa34f9ab87b27dbaa37c8fa32fd8ab27ebcc62bd73ff7c3096282831","observation_id":"02b55e05-4f08-4ad8-8113-f9abc9c202dd","resolution":{"observed_at":"2026-08-06T21:31:40.651370Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.657176Z","title":"U., P ING , Z., L I, Y., XU, Y., ET AL","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.657176Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:26f88d69c82a6677ddbf8f457d8f069f35933ade4a0576db8193333e40d61d56","observation_id":"c9c0573d-2ee4-477f-bb56-3f49595e3382","resolution":{"observed_at":"2026-08-06T21:31:40.657176Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.661721Z","title":"A High-Quality Gold Standard for Citation- Based Tasks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.661721Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:dd220c19d9609a961ee91db4600ee98b89e874bec0043c625e65ae3228cd34b8","observation_id":"edcbe5e7-2109-4f38-bf8e-04f86d552edf","resolution":{"observed_at":"2026-08-06T21:31:40.661721Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.666591Z","title":"To Cite, or Not to Cite? Detecting Citation Contexts in Text","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.666591Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a3db2a6d29ccf250356d612b48d5203a617602d6590d967878620252f8ac8627","observation_id":"97c84085-dc5a-4d70-a3f0-67fc73dcb7a2","resolution":{"observed_at":"2026-08-06T21:31:40.666591Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.670964Z","title":"R., AND MANNING , C","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.670964Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:dd06112c115815a45a326f3ea570ae371392d5886290c32fd962e8c6a692ba22","observation_id":"717ed8da-42bc-4bde-8bc6-9d5a3ebb55e9","resolution":{"observed_at":"2026-08-06T21:31:40.670964Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.675209Z","title":"Communicating uncertainty: Fulfilling the duty to inform","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.675209Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:1443c34e2a7374b9a0ee741a6aca5900ef5c13a743af675615ba1b4f56d318fc","observation_id":"5aa447b4-93ff-4e0c-a0c3-76ff2087b53f","resolution":{"observed_at":"2026-08-06T21:31:40.675209Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.679983Z","title":"Beyond Black & White: Leveraging Annotator Disagreement via Soft-Label Multi-Task Learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.679983Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:acf932774507ab5fb74915a9c1d06a3b383f7d89647cc4e4bf4eee2e19f8c83b","observation_id":"2d8a5e77-f9c6-49c5-9a23-c57573b86567","resolution":{"observed_at":"2026-08-06T21:31:40.679983Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.684677Z","title":"Linear mixed-effects model","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.684677Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:4ed121fc98976ad603cf9ea1c36bbb2ab0c84aec0c1169ba5e10b3f3e3e5c6f4","observation_id":"f0129803-83a7-4c54-9940-e9e9b6b11275","resolution":{"observed_at":"2026-08-06T21:31:40.684677Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.689285Z","title":"Unsupervised Domain Adaptation by Backpropagation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.689285Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:543c91144632dd3a733b8a0cadb5ec127555020c25fa1ba190a29fe0e07e14af","observation_id":"cacfad0d-b54f-41d5-95cf-669206c57c00","resolution":{"observed_at":"2026-08-06T21:31:40.689285Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.693858Z","title":"PPDB: The paraphrase database","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.693858Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6144ed9a541146919372aa50182066705ec5dfaf5c5a4515d6ed5406e65db6ac","observation_id":"e01c8f7e-1264-4186-9bb7-b12cbe9c1069","resolution":{"observed_at":"2026-08-06T21:31:40.693858Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.04618","last_updated":"2019-10-10T14:48:22Z","snapshot_observed_at":"2026-07-06T08:28:25.794772Z","submitted_at":"2019-10-10T14:48:22Z","title":"Universal Adversarial Perturbation for Text Classification","version":1},"cited_work":{"arxiv_id":"1910.04618","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.04618","snapshot_observed_at":"2026-08-06T21:31:42.248756Z","title":"Universal Adversarial Perturbation for Text Classification","venue":"cs.CL","work_id":"597ffdf1-7057-4174-995a-7d1911a26ca8","year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.698693Z"},"links":{"cited_paper":"/paper/1910.04618","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:78fe9e49917e587a1111d3a9a1700dcb0d43e8d5bacd86ff9cf6a3de0525e021","observation_id":"fa74187c-fa82-4481-a30f-ef87686d690a","resolution":{"observed_at":"2026-08-06T21:31:42.253384Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-06T21:31:40.703136Z","title":"A Context-Aware Approach for Detecting Worth-Checking Claims in Political Debates","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.703136Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a92c024a38b2c86f65d2a850557d1e86d7de79902d1bfd248e0325e406d1eceb","observation_id":"c41dd484-00c2-49c6-9b5f-e95860c5fb38","resolution":{"observed_at":"2026-08-06T21:31:40.703136Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.707849Z","title":"I., L IU, V., H UANG , S., L EE, J., AND CHILTON , L","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.707849Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:1038c716daf373b28c13019d523469ceddb6c530d425aa6bfdfb8e86b1445db2","observation_id":"ca5b3fbe-5e1e-48a8-949b-dcc08760e45a","resolution":{"observed_at":"2026-08-06T21:31:40.707849Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.712805Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.712805Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:fabd6d85d5a2a0cb94ebbbd5d3dbdae6580059da630c5e53aa619e935de4be85","observation_id":"a6f3a752-53f5-452e-a661-ca832be03e3a","resolution":{"observed_at":"2026-08-06T21:31:40.712805Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.717242Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.717242Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:3bbc63617c59ec0b41cc2639627f3adcfcbb8c782d8eeb4ded75b8d661cb6d56","observation_id":"a33bf995-2c80-493c-af3a-e8b352df082c","resolution":{"observed_at":"2026-08-06T21:31:40.717242Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.722220Z","title":"J., S HLENS , J., AND SZEGEDY, C","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.722220Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:78ca9899ac49f21dcb55eed6a21a27fa970b62bd8ad1872a082000729fcf74ff","observation_id":"cb21b35a-c8b8-4532-a900-09acee5cc341","resolution":{"observed_at":"2026-08-06T21:31:40.722220Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.726884Z","title":"L., Z HOU, K., P ATEL, K., H ASHIMOTO , T., AND BERNSTEIN , M","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.726884Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2cac21f6360b334fd52bf000cae1ee8002edd094e27578b23af2cd73826a6058","observation_id":"c9f8c8b7-bf12-436d-b4f9-f399c9e722c3","resolution":{"observed_at":"2026-08-06T21:31:40.726884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.00501","last_updated":"2022-05-01T16:08:48Z","snapshot_observed_at":"2026-08-13T15:52:31.126596Z","submitted_at":"2022-05-01T16:08:48Z","title":"Is Your Toxicity My Toxicity? Exploring the Impact of Rater Identity on Toxicity Annotation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.00501","snapshot_observed_at":"2026-08-06T21:31:40.731773Z","title":"Is Y our Toxicity My Toxicity? Exploring the Impact of Rater Identity on Toxicity Annotation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.731773Z"},"links":{"cited_paper":"/paper/2205.00501","citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:1e864877ee54c8d27e546fca0eaa15dfead3d96068b9b9a3e1f8f5a039d497cd","observation_id":"940d35f8-2060-4e5f-aa56-c993adaa1e51","resolution":{"observed_at":"2026-08-06T21:31:40.731773Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.736662Z","title":"The Rise of Fact-Checking Sites in Europe","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.736662Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:62458efca167a9b6b2e7dba9b508e36697f7c27c6369479f024627b4e7bee5eb","observation_id":"0dcc95b9-2871-4579-b885-547428521d38","resolution":{"observed_at":"2026-08-06T21:31:40.736662Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.741547Z","title":"Part-of-Speech Tagging for Twitter with Adversarial Neural Networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.741547Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:7914ac45c87915c95a5d8c71d036a4168ba908fc542962802ea00ad0744af604","observation_id":"fe3b4378-bfa7-4bc2-9f90-27587df2e6d9","resolution":{"observed_at":"2026-08-06T21:31:40.741547Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.746248Z","title":"Multi-Source Domain Adaptation with Mixture of Experts","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.746248Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:09afaf59eefb61eb3fbcdcef7946fe006f9b5b7c0acda79d120f024db35a6aad","observation_id":"b08d5b42-0252-4e70-9579-198c903616b6","resolution":{"observed_at":"2026-08-06T21:31:40.746248Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.750640Z","title":"S., AND VLACHOS , A","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.750640Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:a03ac3a3511733f43b82815c7d00553bf2ee2675f4c10f323e26f4f54aecef7c","observation_id":"996965c8-54c4-4f43-a1ba-ae5a14f2d896","resolution":{"observed_at":"2026-08-06T21:31:40.750640Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.755656Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.755656Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2d37124922eefdb33db4d86e24f7f8bd3996acba93ce0de392adc816ca707673","observation_id":"f8dd9863-e818-4068-95f0-8d3b2a947913","resolution":{"observed_at":"2026-08-06T21:31:40.755656Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.760220Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.760220Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:52683e24ff67d80e6a34d1670c990ec951560d60ace2bbbed0d7fcb89806c3ca","observation_id":"57e3b274-89bd-449b-a463-93a34f0bc953","resolution":{"observed_at":"2026-08-06T21:31:40.760220Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.764335Z","title":"Unsupervised Domain Adaptation of Contextualized Embed- dings: A Case Study in Early Modern English","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.764335Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:6e94b14b09801144f4167ca55a123d277379e94770e8ac561f64374ba4de6e60","observation_id":"ef3133b6-4c87-4ee0-934b-6e5b67e36126","resolution":{"observed_at":"2026-08-06T21:31:40.764335Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.769443Z","title":"Neural Check-Worthiness Ranking With Weak Supervision: Finding Sentences for Fact-Checking","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.769443Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2805eb197a037ca1dfdb6eb4603874c1526cf718153e20600dc1f87464f01605","observation_id":"d5acaa70-d0a8-4d1a-9441-3d67da44e651","resolution":{"observed_at":"2026-08-06T21:31:40.769443Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.774257Z","title":"A Survey on Stance Detection for Mis- and Disinformation Identification, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.774257Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:ccd9380ea3573f09afafb9181d7b62b320b88dfdfd658a5b56f74e48d75a1027","observation_id":"bda4494d-f087-4e71-bd9c-5b7b18d7e4ba","resolution":{"observed_at":"2026-08-06T21:31:40.774257Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.778568Z","title":"Cross-Domain Label- Adaptive Stance Detection","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.778568Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:2928790e16729144ebfe8b6f8e15929707dcdc52940f5d76674fe955068a922b","observation_id":"dcc1d3ff-69db-45da-9fca-6a8883ae889a","resolution":{"observed_at":"2026-08-06T21:31:40.778568Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:31:40.782935Z","title":"Few-Shot Cross-Lingual Stance Detection with Sentiment-Based Pre-Training","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-06T21:31:40.782935Z"},"links":{"citing_paper":"/paper/2506.23990"},"observation_digest":"sha256:dfc2618f616a191d1324a246367729e2acc0747a468c776dda0ee44233d56ccb","observation_id":"aedad9f7-da0f-41c0-840f-b1bb107883ac","resolution":{"observed_at":"2026-08-06T21:31:40.782935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.23990","last_updated":"2025-06-30T15:55:10Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-14T06:44:03.414206Z","submitted_at":"2025-06-30T15:55:10Z","title":"Machine Understanding of Scientific Language"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":97,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":286},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 100 of 286 outbound references and 0 inbound Pith citation observations for arXiv:2506.23990."}