{"as_of":"2026-08-08T02:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:068e1d5db7fb8706ce366ce152804c805e63ce0bc55eec3dfbdf975d07a0ff1a","coverage":[{"denominator":66,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":66,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:34:41.770580Z","state":"measured"},{"denominator":66,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":66,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2506.23930/citation-record","integrity":"/paper/2506.23930/integrity","json":"/paper/2506.23930/citation-record.json","paper":"/paper/2506.23930"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.402405Z","title":"Available: https://www.un.org/en/hate-speech/ understanding-hate-speech/what-is-hate-speech#:~:text=To% 20provide%20a%20unified%20framework,person%20or%20a% 20group%20on","venue":null,"work_id":"25cdee12-3093-4fc8-ab4f-d0c2ae095d86","year":null},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.583479Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:62fe066fcc1e35f4471a8d03bb8a08705b35268ececa4b6ee4f86e04045ac4f9","observation_id":"bedfef71-2af4-419a-a516-e2f004cff83c","resolution":{"observed_at":"2026-08-06T21:34:45.408463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.386965Z","title":"Hate speech review in the context of online social networks,","venue":null,"work_id":"6ed309d3-ea0e-4ec2-9681-ef6234d6c8ba","year":2018},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.643793Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:1002878caf48e8bd0239de074d4b321f0df2636efdd2f482bb330ca8641d10f6","observation_id":"1d57a065-fd9d-4248-900a-b6a4124866ec","resolution":{"observed_at":"2026-08-06T21:34:45.391558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.371666Z","title":"Hossain, Oct 2019","venue":null,"work_id":"d80c1f10-b19b-4884-bcd7-124524d35056","year":2019},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.741215Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:8bf35957ea816bf39873b69fb56df58f9995c0da0a74059a4eefe611c08414ab","observation_id":"31202622-76cd-4f56-a2f7-42aefaf6bb16","resolution":{"observed_at":"2026-08-06T21:34:45.376160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.356559Z","title":"Indian mob kills man over beef eating rumour,","venue":null,"work_id":"eb364df4-b7c1-4c30-b611-8881f63db8bf","year":null},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.827466Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:341a19b2a5850aab3d1a9fb1b75411d0adb105b1daa5e721d6b851e354474429","observation_id":"15124a3c-591a-455e-ac40-4d2ea9761958","resolution":{"observed_at":"2026-08-06T21:34:45.361297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.326522Z","title":"Business reputation and social media: A primer on threats and responses,","venue":null,"work_id":"b050b510-8413-4b1a-9469-cc7aa8c32bad","year":2015},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.992896Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:6abd75fffd1160c65405225ba44f67695af74fa1fdb3321567bd7b9171f3a7e9","observation_id":"bccf3d74-ff5f-4b2f-9fd1-13658dfe14c4","resolution":{"observed_at":"2026-08-06T21:34:45.331258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.07676","last_updated":"2021-01-25T10:56:45Z","snapshot_observed_at":"2026-08-07T14:12:26.620672Z","submitted_at":"2020-01-21T17:57:33Z","title":"Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.07676","snapshot_observed_at":"2026-08-06T21:34:37.074157Z","title":"Exploiting cloze questions for few shot text classification and natural language inference,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.074157Z"},"links":{"cited_paper":"/paper/2001.07676","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:de5257fc1ea5fc74d0a00afdacb3f4767fa731f5dd3502b12adec05143a0af0d","observation_id":"dc2d9831-fa31-443e-a1af-9ec4bbdb2dc9","resolution":{"observed_at":"2026-08-06T21:34:37.074157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.311545Z","title":"Prompt learning for low-resource multi-domain fake news detection,","venue":null,"work_id":"1b137110-35ba-4dda-845b-0999dd8088b2","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.169045Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:c5a1d76f4bcb952f9f3746ef21ea4011786510c4fabcad5afbd1f45ab250b7ba","observation_id":"ae06e614-4630-49a0-b321-0047ffc28c65","resolution":{"observed_at":"2026-08-06T21:34:45.316484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.294216Z","title":"Generating monolingual dataset for low resource language bodo from old books using google keep,","venue":null,"work_id":"9b9ad338-a3df-418d-89d9-9a6324fa95d2","year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.240279Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:ec480e7ba450c9f2c2fadc6b56bbc5c6ca4a97b7903a803a29dedde6710f1eb7","observation_id":"7f29d03e-3c4c-4534-a49f-0ce7058b209d","resolution":{"observed_at":"2026-08-06T21:34:45.300299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.279267Z","title":"Prompt-based for low-resource tibetan text classification,","venue":null,"work_id":"0c39d307-0cb4-489a-85c4-e25b57a65575","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.343242Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:2b262ce02c01a9bdd11c72a3b0a145767f7ef441dbaf60d421101bf05e4441a1","observation_id":"fdd5fd11-d314-4e1a-9859-932b40dd2f48","resolution":{"observed_at":"2026-08-06T21:34:45.284089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03479","last_updated":"2022-10-07T12:06:04Z","snapshot_observed_at":"2026-07-06T14:01:50.333970Z","submitted_at":"2022-10-07T12:06:04Z","title":"Hate Speech and Offensive Language Detection in Bengali","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03479","snapshot_observed_at":"2026-08-06T21:34:37.448708Z","title":"Hate speech and of- fensive language detection in bengali,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.448708Z"},"links":{"cited_paper":"/paper/2210.03479","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:96597c236be41998d5c16a65b865af05647a4fa5fc529599963b91a8529f0af8","observation_id":"60743ccb-919d-40a3-93bc-19721597f4eb","resolution":{"observed_at":"2026-08-06T21:34:37.448708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.263486Z","title":"Tinyllm efficacy in low-resource language: An experiment on bangla text classification task,","venue":null,"work_id":"6bf519da-3c5d-4ca3-aabc-6c54c92fb7c8","year":2025},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.538189Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:00394f1f96e37d3d1bf65478db1977d6a753290ca4dca21ec063a8982191b1a9","observation_id":"d4b273cb-e4e4-43bd-9412-e237a99a8872","resolution":{"observed_at":"2026-08-06T21:34:45.268717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.247146Z","title":"Using a semi- automatic keyword dictionary for improving violent web site filtering,","venue":null,"work_id":"c827492d-f9bf-4682-b787-1f918f2cda8a","year":2007},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.614639Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:83729b172e5460ae63a37fe9f46a1079c5163334d3cee97acc699cd13d8265b8","observation_id":"74f0596b-9ce2-4225-8da3-150accbfabe7","resolution":{"observed_at":"2026-08-06T21:34:45.252236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.232574Z","title":"Us and them: identifying cyber hate on twitter across multiple protected characteristics,","venue":null,"work_id":"2703c315-dc11-4126-a961-9c5ab04eef86","year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.753844Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:d0adc1c6c2f58c9a45ddd89b085b794d177296ce92185d1ae5d237bd49853659","observation_id":"9d811121-b96e-4979-a3da-c326428677ec","resolution":{"observed_at":"2026-08-06T21:34:45.237652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.08738","last_updated":"2016-08-31T06:28:28Z","snapshot_observed_at":"2026-08-04T18:52:11.177187Z","submitted_at":"2016-08-31T06:28:28Z","title":"A Dictionary-based Approach to Racism Detection in Dutch Social Media","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.08738","snapshot_observed_at":"2026-08-06T21:34:37.855433Z","title":"A dictionary-based approach to racism detection in dutch social media,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.855433Z"},"links":{"cited_paper":"/paper/1608.08738","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:48d3314dd8ad5d4821b1b26e5eb7ed4d58e9126fe0118524eaf4c2805e67bf47","observation_id":"c9ae4cda-ee76-4616-bf26-fcf1f7729d59","resolution":{"observed_at":"2026-08-06T21:34:37.855433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.216827Z","title":"A lexicon-based approach for hate speech detection,","venue":null,"work_id":"be226cac-e1b9-412b-9a55-18e68647d685","year":2015},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.925935Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:3561467093a4ba939051ca50e67d7b60a8ad431a0e4decb22662728aa44d49d7","observation_id":"e8e5b2b9-63c8-49ec-b7f3-e33f8eb7e19c","resolution":{"observed_at":"2026-08-06T21:34:45.221834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.202138Z","title":"Hate speech detection: Challenges and solutions,","venue":null,"work_id":"8caad066-affd-4ba9-8276-7fcf68276292","year":2019},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:37.991039Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:ff9ac9dffd6e0cc115458c1a333e8f5dfcf7267d0b4345163a815523b62a2674","observation_id":"f25f97e8-67ff-4979-871c-48de75ec7dd3","resolution":{"observed_at":"2026-08-06T21:34:45.206777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.10159","last_updated":"2017-09-28T20:31:30Z","snapshot_observed_at":"2026-07-06T06:01:53.369097Z","submitted_at":"2017-09-28T20:31:30Z","title":"A Web of Hate: Tackling Hateful Speech in Online Social Spaces","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.10159","snapshot_observed_at":"2026-08-06T21:34:38.070126Z","title":"A web of hate: Tackling hateful speech in online social spaces,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.070126Z"},"links":{"cited_paper":"/paper/1709.10159","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:a49de2a77aaef069c23982d06f9042269b3e78b94b6ece5a4b533d600f4fd1cb","observation_id":"93004623-7417-4a45-9f35-24d31a2a3dac","resolution":{"observed_at":"2026-08-06T21:34:38.070126Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.188433Z","title":"Detection of hate speech by employing support vector machine with word2vec model,","venue":null,"work_id":"4a5006a5-cf71-4970-8595-731350b983fb","year":2021},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.143798Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:3e16e33e776355f96fc5c4f4f04bf539a44f36a54423cbdde968c8c50bc34b6e","observation_id":"0a5f98aa-5d4e-4685-9c72-9655f39d7f66","resolution":{"observed_at":"2026-08-06T21:34:45.192771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T21:34:38.228587Z","title":"Hateful symbols or hateful people? predictive features for hate speech detection on twitter,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.228587Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:4b3b38dcc7273db2400f902d86748d9ad4cde678795898dd95251bd12d0a8cf4","observation_id":"b70a75f8-dfd3-4524-a3b4-7bc5ea762e9b","resolution":{"observed_at":"2026-08-06T21:34:38.228587Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.164926Z","title":"Svm for hate speech and offensive content detection","venue":null,"work_id":"ab4afeac-6736-419c-9aed-18cd8712a11d","year":2021},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.282205Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:eed6f853747d53bacf9ebb18af80552bec2f5ec6d24604cc497cfb165e6081d0","observation_id":"86def259-a6fa-4e85-b75e-dd91bf63f7ab","resolution":{"observed_at":"2026-08-06T21:34:45.169051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.150673Z","title":"A comparison of event models for naive bayes text classification,","venue":null,"work_id":"9f36f7c1-a158-42cb-a683-83c62ef944e8","year":1998},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.362253Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:5afb93412f771e0a767f9e47f3c9a2c36bd495f6eaee74eb4e408d0366598660","observation_id":"5d68d925-2b5e-4744-b9bb-0ebf73a7b2d8","resolution":{"observed_at":"2026-08-06T21:34:45.155437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.135456Z","title":"A survey on hate speech detection and sentiment analysis using machine learning and deep learning models,","venue":null,"work_id":"2226a1ea-cce0-4686-9180-905d05860151","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.448929Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:38b660ee14e7991ef73f499e9bf55ed3abf7581c8e1acbed133b4b7f2e9fc95f","observation_id":"be4940ad-a1b4-4891-9b96-beafab5e0434","resolution":{"observed_at":"2026-08-06T21:34:45.139997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.120667Z","title":"Im- proving random forest method to detect hatespeech and offensive word,","venue":null,"work_id":"daa7efa9-d9e2-4c93-a60b-e278c7a2bcaa","year":2019},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.530818Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:4e9357b88f4d3d3e9520660c416a3292684086c5d066e72c837784b65748561b","observation_id":"3d99c5fb-0d36-4153-b3fc-91408e43cd4e","resolution":{"observed_at":"2026-08-06T21:34:45.125033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.105194Z","title":"But i did not mean it!—intent classification of racist posts on tumblr,","venue":null,"work_id":"6c3032e6-68e6-4bd9-8e18-531b3c632bb9","year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.623654Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:9c322cc7c05146cd0dd27fd1d37a600cd6adb46e7f6893962c01bf0963345d87","observation_id":"b54a1a06-7b63-454b-bf5e-466025a928ab","resolution":{"observed_at":"2026-08-06T21:34:45.110976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.090736Z","title":"Decision trees and random forests: Machine learning techniques to classify rare events,","venue":null,"work_id":"35101f5b-b36f-41ae-a64e-49320c537523","year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.701750Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:e29862f3cdff16582b73d275cd2c4289a5d4ba7a2f796189700e7366b1b0655e","observation_id":"1ebc768d-c13f-4c5a-8c9a-314b4abe3fc0","resolution":{"observed_at":"2026-08-06T21:34:45.095396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.077146Z","title":"Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making,","venue":null,"work_id":"282c75a6-0281-4c08-b1b6-eb7ad6320aa0","year":2015},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.780875Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:6e701d28f7cac3814ec2f72e31660d887aeb3f1c0bed5da9f77a19977c5f5b0c","observation_id":"686bb51b-03bb-47a8-9b91-46bff0798005","resolution":{"observed_at":"2026-08-06T21:34:45.081704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.063360Z","title":"Using convolutional neural networks to classify hate-speech,","venue":null,"work_id":"862df8ce-563d-403f-b26a-87f221ad22c0","year":2017},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.849908Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:23a64710260a311672441280b2e74a0eaa6f9f2224d739b676084c1335a639f4","observation_id":"165890e7-d2a8-4da0-b660-fd38d0b80cc3","resolution":{"observed_at":"2026-08-06T21:34:45.067928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.12448","last_updated":"2020-08-28T02:44:17Z","snapshot_observed_at":"2026-07-06T09:50:50.792396Z","submitted_at":"2020-08-28T02:44:17Z","title":"QutNocturnal@HASOC'19: CNN for Hate Speech and Offensive Content Identification in Hindi Language","version":1},"cited_work":{"arxiv_id":"2008.12448","doi":null,"metadata_source":"pith","pith_arxiv_id":"2008.12448","snapshot_observed_at":"2026-08-06T21:34:43.195773Z","title":"QutNocturnal@HASOC'19: CNN for Hate Speech and Offensive Content Identification in Hindi Language","venue":"cs.CL","work_id":"7543d177-68b0-491f-a515-01f7e10c09e1","year":2020},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:38.926293Z"},"links":{"cited_paper":"/paper/2008.12448","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:6b2aa4e9f2d86afb4e1b447df32d5683c556915cdbc3b9cc59dfbc031baab53d","observation_id":"56058f5e-28d2-422c-9942-62ae89621f83","resolution":{"observed_at":"2026-08-06T21:34:43.310225Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.049207Z","title":"Hate speech detection using attention-based lstm,","venue":null,"work_id":"32311f14-5c6e-47f5-8b50-c7ea42b9ef28","year":2018},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.006800Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:7ddda68a1cae5816ceb29e8df7bf5c1aa133e33acb2ee426589524476ffb18cb","observation_id":"a9dccea8-ab23-4d78-a331-982f23422afc","resolution":{"observed_at":"2026-08-06T21:34:45.053803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.035598Z","title":"Detection of hate speech and offensive language in twitter data using lstm model,","venue":null,"work_id":"622b3fec-e962-4999-ac77-6625e4d8a550","year":2020},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.094386Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:6d8b896632cfa61ebd0aaaf1ba2d6a6ba64ce95d2e710292029d60e1fd0706a7","observation_id":"45b3a008-e0f4-4cf8-bacb-d48350ab143d","resolution":{"observed_at":"2026-08-06T21:34:45.040113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.020874Z","title":"Deep learning for hate speech detection in tweets,","venue":null,"work_id":"d9cd6c2c-de11-4978-8993-d9fd1178169e","year":2017},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.161579Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:eaad8a7471122efe6c4c55f042a7e8bd832e1f418d9e1addde396ee92c04f9a6","observation_id":"7facfda6-366f-4112-bf60-bd6eeeea8412","resolution":{"observed_at":"2026-08-06T21:34:45.025219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.08815","last_updated":"2017-07-27T02:38:59Z","snapshot_observed_at":"2026-08-02T18:14:57.891554Z","submitted_at":"2016-10-27T14:50:43Z","title":"A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.08815","snapshot_observed_at":"2026-08-06T21:34:39.227664Z","title":"A deeper look into sarcastic tweets using deep convolutional neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.227664Z"},"links":{"cited_paper":"/paper/1610.08815","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:489c47f1d8eba6b476965f910a6f4ed0d79ae851a5505620b36f1830e7061b55","observation_id":"be987b15-b26d-474e-ad0b-82138eb6da71","resolution":{"observed_at":"2026-08-06T21:34:39.227664Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11406","last_updated":"2024-07-23T06:20:32Z","snapshot_observed_at":"2026-08-05T13:01:03.473798Z","submitted_at":"2024-02-18T00:04:40Z","title":"Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection","version":3},"cited_work":{"arxiv_id":"2402.11406","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.11406","snapshot_observed_at":"2026-08-06T21:34:43.010216Z","title":"Don't Go To Extremes: Revealing the Excessive Sensitivity and Calibration Limitations of LLMs in Implicit Hate Speech Detection","venue":"cs.CL","work_id":"58bff322-9e5b-45c5-b3eb-9bb282069b39","year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.299231Z"},"links":{"cited_paper":"/paper/2402.11406","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:9c106c14471b355718eb83d9831617d54c85899e30d3ecb58463c0d3045f8215","observation_id":"0c0342ba-96d3-4682-b533-82a72dc7fad4","resolution":{"observed_at":"2026-08-06T21:34:43.058076Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.17336","last_updated":"2024-09-30T21:25:23Z","snapshot_observed_at":"2026-08-05T17:39:59.419266Z","submitted_at":"2024-03-26T02:47:42Z","title":"Don't Listen To Me: Understanding and Exploring Jailbreak Prompts of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.17336","snapshot_observed_at":"2026-08-06T21:34:39.370338Z","title":"Don’t listen to me: Understanding and exploring jailbreak prompts of large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.370338Z"},"links":{"cited_paper":"/paper/2403.17336","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:cf1dd0b06277a77f54dc6a2fda47bca9a5af751397fa214b4103c2e2b4c8dad3","observation_id":"b14625b6-8bce-4ea8-a972-2cfa29434d39","resolution":{"observed_at":"2026-08-06T21:34:39.370338Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.005619Z","title":"Many-shot jailbreaking,","venue":null,"work_id":"9b58f559-fe39-4e0e-89a0-f12629204f4a","year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.460041Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:c2bb8607dffaddfdf215edc2defeee4ee5bcc1ac1364ec880871d0f7f144e08a","observation_id":"7c5779b4-2c49-44e3-84ce-2303002e17f5","resolution":{"observed_at":"2026-08-06T21:34:45.009945Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00234","last_updated":"2024-10-05T11:47:02Z","snapshot_observed_at":"2026-07-06T14:36:25.690733Z","submitted_at":"2022-12-31T15:57:09Z","title":"A Survey on In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00234","snapshot_observed_at":"2026-08-06T21:34:39.539189Z","title":"A survey on in-context learning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.539189Z"},"links":{"cited_paper":"/paper/2301.00234","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:439eca43c729d0572e01879f83c6e2db190fdcf7afc6421f89082214fe590dfb","observation_id":"be2bf6df-f551-4dd7-a165-c585fd4fbe52","resolution":{"observed_at":"2026-08-06T21:34:39.539189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07702","last_updated":"2024-03-14T02:07:11Z","snapshot_observed_at":"2026-08-02T18:42:43.546865Z","submitted_at":"2023-08-15T11:08:30Z","title":"Better Zero-Shot Reasoning with Role-Play Prompting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07702","snapshot_observed_at":"2026-08-06T21:34:39.594919Z","title":"Better zero-shot reasoning with role-play prompting,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.594919Z"},"links":{"cited_paper":"/paper/2308.07702","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:31181f71ca32af2e963e565a9f2e87fb93142203367d9785e6bb00feba40fc67","observation_id":"a57cdfbd-c276-4dde-ab81-0386013695d7","resolution":{"observed_at":"2026-08-06T21:34:39.594919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.902222Z","title":"Respectful or toxic? using zero-shot learning with language models to detect hate speech,","venue":null,"work_id":"dc3b251c-9ec3-41cd-a51b-cb3df3bffa36","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.659497Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:7a4ef6eb5f86a5b3f7e5d0da4460a3318cdfc361c7ab38149856ca17cb9d224b","observation_id":"b7b01fa9-4ba7-4c80-a0c6-36dd698722f2","resolution":{"observed_at":"2026-08-06T21:34:44.995477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.765470Z","title":"Leveraging zero and few-shot learning for enhanced model generality in hate speech detection in spanish and english,","venue":null,"work_id":"6733a404-26d7-47bd-b834-b450d151c9dd","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.752676Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:ad13d4ce22b1a3aa2cbfef3d1208ed0c92cde39d1085197e66930fa1579705f8","observation_id":"cd1b96c0-77c5-48d4-96c3-03aac848f324","resolution":{"observed_at":"2026-08-06T21:34:44.839071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.15099","last_updated":"2024-05-10T17:01:55Z","snapshot_observed_at":"2026-07-06T17:07:28.222329Z","submitted_at":"2023-12-22T22:34:49Z","title":"Moderating New Waves of Online Hate with Chain-of-Thought Reasoning in Large Language Models","version":2},"cited_work":{"arxiv_id":"2312.15099","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.15099","snapshot_observed_at":"2026-08-06T21:34:42.764459Z","title":"Moderating New Waves of Online Hate with Chain-of-Thought Reasoning in Large Language Models","venue":"cs.CL","work_id":"c2eb56f7-da42-4fb1-a65d-9ed250fb6fde","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.828704Z"},"links":{"cited_paper":"/paper/2312.15099","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:fc2671d2243280fb00240497c0b177edf98a493cedaf6a564e4f7398379cf24e","observation_id":"8deb7eab-8437-4511-9d2b-51e039fb0c58","resolution":{"observed_at":"2026-08-06T21:34:42.876707Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.625368Z","title":"Hypernymy detection for low-resource languages: A study for hindi, bengali, and amharic,","venue":null,"work_id":"f7d1efe8-f25f-416c-bc72-aac1d1477a1b","year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.912145Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:a3780465dca5c6042ed77cbd5bd8deabb8e86abb0aca16f6a953960cfc9b3b20","observation_id":"ac128618-86fd-428c-9b68-3c40acc7e832","resolution":{"observed_at":"2026-08-06T21:34:44.700761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.07847","last_updated":"2024-01-15T17:23:02Z","snapshot_observed_at":"2026-08-07T01:49:43.185361Z","submitted_at":"2024-01-15T17:23:02Z","title":"Milestones in Bengali Sentiment Analysis leveraging Transformer-models: Fundamentals, Challenges and Future Directions","version":1},"cited_work":{"arxiv_id":"2401.07847","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.07847","snapshot_observed_at":"2026-08-06T21:34:42.674020Z","title":"Milestones in Bengali Sentiment Analysis leveraging Transformer-models: Fundamentals, Challenges and Future Directions","venue":"cs.CL","work_id":"a584c422-35f0-47de-b71c-e980d90331c1","year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:39.978605Z"},"links":{"cited_paper":"/paper/2401.07847","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:4301b445b34d05de9788c2c565b51d754ad66ff3cfbe0b58abbafae610ab8a97","observation_id":"f560e2e0-031a-43d6-a0b6-b4e2044aa4c9","resolution":{"observed_at":"2026-08-06T21:34:42.697602Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.480863Z","title":"A dataset of Hindi-English code-mixed social media text for hate speech detection,","venue":null,"work_id":"e5b7240e-b85a-4fef-98df-7d96b12869b0","year":2018},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.082246Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:7a70e16e9448f1116a28ce27d476f675c48ae633038e90e698d30b065eb2cec1","observation_id":"873c0836-8b0e-46bf-807f-531d518b92a5","resolution":{"observed_at":"2026-08-06T21:34:44.540536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.335672Z","title":"Navigating linguistic diversity: In-context learning and prompt engineering for subjectivity analysis in low-resource languages,","venue":null,"work_id":"5414b9ac-91ea-4238-9fd8-be99b7dc5129","year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.176101Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:efde039e2444d6a5bf70ba0131ec8e95ff0b93a23b6c2c48c60f40bbb7cbc036","observation_id":"91e61f4a-423d-4e43-b4e1-4f96d100b349","resolution":{"observed_at":"2026-08-06T21:34:44.407536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02243","last_updated":"2019-06-05T18:40:53Z","snapshot_observed_at":"2026-07-06T07:58:15.564292Z","submitted_at":"2019-06-05T18:40:53Z","title":"Energy and Policy Considerations for Deep Learning in NLP","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.02243","snapshot_observed_at":"2026-08-06T21:34:40.263128Z","title":"Energy and policy considerations for deep learning in nlp,","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.263128Z"},"links":{"cited_paper":"/paper/1906.02243","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:68e1a3ac7c3c4ffaa814ba1c88f05ec5f45db4104ad47d31bf005bb5ccce8450","observation_id":"89011bb4-bfbc-494d-affe-044de4534c7d","resolution":{"observed_at":"2026-08-06T21:34:40.263128Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.193364Z","title":"Towards climate awareness in NLP research,","venue":null,"work_id":"0b04845d-99a8-4487-a40c-565f4d0ea137","year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.354119Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:19ba961b96de73f30be8b07d8deb8c56fd86a255e8115a3b38d9efa05d9193f7","observation_id":"21bfb8ad-9d64-4f92-9111-c70d557374d6","resolution":{"observed_at":"2026-08-06T21:34:44.250339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.01256","last_updated":"2024-02-05T11:13:59Z","snapshot_observed_at":"2026-07-06T16:42:12.176043Z","submitted_at":"2023-11-02T14:16:48Z","title":"An energy-based comparative analysis of common approaches to text classification in the Legal domain","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.01256","snapshot_observed_at":"2026-08-06T21:34:40.437209Z","title":"An energy-based comparative analysis of common approaches to text classification in the legal domain,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.437209Z"},"links":{"cited_paper":"/paper/2311.01256","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:9e008e0e0112785e124299384eed9aac887f431e596df7637a0bf0ddca359f49","observation_id":"f1d7cce9-fc1f-47b1-9c7a-db6afa2b173e","resolution":{"observed_at":"2026-08-06T21:34:40.437209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.00372","last_updated":"2022-06-01T10:10:15Z","snapshot_observed_at":"2026-07-06T13:16:16.926712Z","submitted_at":"2022-06-01T10:10:15Z","title":"BD-SHS: A Benchmark Dataset for Learning to Detect Online Bangla Hate Speech in Different Social Contexts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.00372","snapshot_observed_at":"2026-08-06T21:34:40.522421Z","title":"Bd-shs: A benchmark dataset for learning to detect online bangla hate speech in different social contexts,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.522421Z"},"links":{"cited_paper":"/paper/2206.00372","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:e6abc406e971c4bcee9708c192d9585470ce5916d2b9804e3636baad2a52943c","observation_id":"c7a94f3e-0f51-4fc6-aed2-e8d98cbdbe81","resolution":{"observed_at":"2026-08-06T21:34:40.522421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:44.065189Z","title":"A curated dataset for hate speech detection on social media text,","venue":null,"work_id":"aabafab8-dca1-48a0-be0d-6a0236823cd3","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.590370Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:0dce35ed180af307449b346dc2081cc189eba5a253251deaf915526a715348e9","observation_id":"16b7e5a2-e7c3-43df-b572-569ff5c15924","resolution":{"observed_at":"2026-08-06T21:34:44.127574Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.19559","last_updated":"2024-03-28T16:44:14Z","snapshot_observed_at":"2026-07-06T17:52:38.371963Z","submitted_at":"2024-03-28T16:44:14Z","title":"Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.19559","snapshot_observed_at":"2026-08-06T21:34:40.688200Z","title":"Improving adversarial data collection by supporting annotators: Lessons from gahd, a german hate speech dataset,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.688200Z"},"links":{"cited_paper":"/paper/2403.19559","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:84a1d1ce70880410b8566fb3c5d83955f026f22649008678d7a4877aa0e918fc","observation_id":"6463418e-e551-4d00-95ef-31f43fd23aed","resolution":{"observed_at":"2026-08-06T21:34:40.688200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.00328","last_updated":"2022-04-30T19:09:09Z","snapshot_observed_at":"2026-07-06T13:05:26.571347Z","submitted_at":"2022-04-30T19:09:09Z","title":"HateCheckHIn: Evaluating Hindi Hate Speech Detection Models","version":1},"cited_work":{"arxiv_id":"2205.00328","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.00328","snapshot_observed_at":"2026-08-06T21:34:42.367933Z","title":"HateCheckHIn: Evaluating Hindi Hate Speech Detection Models","venue":"cs.CL","work_id":"ce3c6aa6-fc55-4d56-851b-071b28ce878b","year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.745599Z"},"links":{"cited_paper":"/paper/2205.00328","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:10ed271f704b0398a7f98ab38f1f930f323b0a6ee5efa55db59f0abd953dfe6e","observation_id":"63b14173-5fb9-4530-b2e7-3af7cb2c8f5e","resolution":{"observed_at":"2026-08-06T21:34:42.417825Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.00405","last_updated":"2021-12-01T13:44:04Z","snapshot_observed_at":"2026-08-04T17:10:43.005023Z","submitted_at":"2021-01-31T07:56:08Z","title":"BNLP: Natural language processing toolkit for Bengali language","version":2},"cited_work":{"arxiv_id":"2102.00405","doi":null,"metadata_source":"pith","pith_arxiv_id":"2102.00405","snapshot_observed_at":"2026-08-06T21:34:42.246762Z","title":"BNLP: Natural language processing toolkit for Bengali language","venue":"cs.CL","work_id":"f9c9ba06-375a-41a9-ac5e-30d001663300","year":2021},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.846766Z"},"links":{"cited_paper":"/paper/2102.00405","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:9e8c0ec21de59e53a2ef926b95df0ec6730370e3fbe4fb6ed4cb8cba8c67ca2e","observation_id":"815461da-5b1d-4d71-a117-88a01ae3426a","resolution":{"observed_at":"2026-08-06T21:34:42.301177Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:43.959012Z","title":"Computers’ interpre- tations of knowledge representation using pre-conceptual schemas: an approach based on the bert and llama 2-chat models,","venue":null,"work_id":"d682fdb7-0e2b-4c5d-a3e0-e1226ee33f3c","year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.921130Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:d5b2b1e21a46b6524e8c7a5fb58ee9754800847ab7f4cb7faae203e9e9be00a4","observation_id":"ea0a5344-2fd7-4d1d-8267-c01841b3f2fb","resolution":{"observed_at":"2026-08-06T21:34:44.000116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:43.930206Z","title":"Google translate","venue":null,"work_id":"929b0aba-7eff-4f2d-8dbe-52a3dc0ad7a6","year":null},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:40.994749Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:bff36d9e4ceb863b1511e66f56398e7a9bd2d520aa1ee8bbf17b7598b002db6e","observation_id":"a955ef85-d1a6-4350-a04c-b913f2398b1c","resolution":{"observed_at":"2026-08-06T21:34:43.947555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.04512","last_updated":"2024-12-29T06:29:14Z","snapshot_observed_at":"2026-07-31T08:39:18.535760Z","submitted_at":"2024-09-06T17:15:17Z","title":"Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages","version":2},"cited_work":{"arxiv_id":"2409.04512","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.04512","snapshot_observed_at":"2026-08-06T21:34:42.111853Z","title":"Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages","venue":"cs.CL","work_id":"73ee6f1e-5382-4cd6-a5e7-3ad28d1f4a62","year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.059363Z"},"links":{"cited_paper":"/paper/2409.04512","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:6f79a31aba891a3a542d1066e562c9ac49ce7f1431e837f8d9714e19ddb17326","observation_id":"031b3f91-b603-4a8b-a670-e3f3c077f92e","resolution":{"observed_at":"2026-08-06T21:34:42.165552Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-06T21:34:41.145478Z","title":"Llama 2: Open foundation and fine-tuned chat models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.145478Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:89cc45bf0fcbdc0a6c583472b5fb0f6207c1fc86528a2ffcfbf0fbc1877a60ba","observation_id":"0b491711-6151-47ab-86ad-d5e42cb95a25","resolution":{"observed_at":"2026-08-06T21:34:41.145478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:43.716781Z","title":"Sentencepiece: A simple and language independent subword tokenizer and detokenizer for neural text processing,","venue":null,"work_id":"03c6fb92-d72c-49e8-8dfe-5681cd64b6fd","year":2018},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.203070Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:af049b9590a176362a6013d923f22ae92729ae97383ba12b1dfba080efb148e7","observation_id":"344a3bf3-f203-41e6-bc0b-308794abbcaf","resolution":{"observed_at":"2026-08-06T21:34:43.819281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:43.509888Z","title":"Available: https://huggingface.co/meta-llama/ Llama-2-7b-chat-hf","venue":null,"work_id":"8a3ff82a-6523-4ca9-b810-842622fd2560","year":null},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.288054Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:aae7044bbc342e7664d66da25dfe6b976a689b67d07d09963eee6b32c7037ce1","observation_id":"5c3a2e56-b65b-4f2d-b0c0-6ed26fb28929","resolution":{"observed_at":"2026-08-06T21:34:43.602877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T21:34:41.371716Z","title":"Large language models are zero-shot reasoners,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.371716Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:e62420e3dc0e99f964347359c0fe73f5ef43647e2e2f86075cf4f4e0ab7d4878","observation_id":"d7716bd8-2019-4761-8538-4511466cf611","resolution":{"observed_at":"2026-08-06T21:34:41.371716Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16369","last_updated":"2025-07-02T07:27:32Z","snapshot_observed_at":"2026-08-07T21:23:08.873449Z","submitted_at":"2024-04-25T07:15:23Z","title":"Don't Say No: Jailbreaking LLM by Suppressing Refusal","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16369","snapshot_observed_at":"2026-08-06T21:34:41.418171Z","title":"Don’t say no: Jailbreaking llm by suppressing refusal,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.418171Z"},"links":{"cited_paper":"/paper/2404.16369","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:1bc5fba88ff2829fe3a47c70aee9317d293dc4479c86a583c6b022776f673288","observation_id":"36a7ccd1-900a-40af-92c3-8adda79cb4ea","resolution":{"observed_at":"2026-08-06T21:34:41.418171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.02802","last_updated":"2024-12-03T20:07:41Z","snapshot_observed_at":"2026-08-06T02:45:33.117867Z","submitted_at":"2024-12-03T20:07:41Z","title":"Flattering to Deceive: The Impact of Sycophantic Behavior on User Trust in Large Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.02802","snapshot_observed_at":"2026-08-06T21:34:41.494909Z","title":"Flattering to deceive: The impact of sycophantic behavior on user trust in large language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.494909Z"},"links":{"cited_paper":"/paper/2412.02802","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:9acf04e65070681b4f3d4cb60c70db3e278239f57cdc7d51be719ef8545c4f29","observation_id":"41ced416-2657-4ece-8c9c-b1bbb4e81b9c","resolution":{"observed_at":"2026-08-06T21:34:41.494909Z","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":"2026-08-06T21:34:41.548803Z","title":"Language models are few-shot learners,","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.548803Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:17b76d689a589c24917f876941425bc19390034ee18606f573e4a1d7ebee12db","observation_id":"da7c1749-0a11-4001-ad89-35f7bc6e16e3","resolution":{"observed_at":"2026-08-06T21:34:41.548803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.01300","last_updated":"2020-12-02T16:10:54Z","snapshot_observed_at":"2026-07-06T10:20:00.293892Z","submitted_at":"2020-12-02T16:10:54Z","title":"Learning from others' mistakes: Avoiding dataset biases without modeling them","version":1},"cited_work":{"arxiv_id":"2012.01300","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.01300","snapshot_observed_at":"2026-08-06T21:34:41.927091Z","title":"Learning from others' mistakes: Avoiding dataset biases without modeling them","venue":"cs.CL","work_id":"b848316a-fd5a-4227-99a8-92e6260ab588","year":2020},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.624775Z"},"links":{"cited_paper":"/paper/2012.01300","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:01de34f1f9e07724ff864b77e52bf6c165377ed13584fa71232a92a0d1fc53a4","observation_id":"f7e14ac7-bada-4836-b94c-e790f90a5c83","resolution":{"observed_at":"2026-08-06T21:34:41.989811Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03729","last_updated":"2024-04-01T20:56:11Z","snapshot_observed_at":"2026-08-07T10:09:54.492727Z","submitted_at":"2024-01-08T08:28:08Z","title":"The Butterfly Effect of Altering Prompts: How Small Changes and Jailbreaks Affect Large Language Model Performance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03729","snapshot_observed_at":"2026-08-06T21:34:41.685451Z","title":"The butterfly effect of altering prompts: How small changes and jailbreaks affect large language model perfor- mance,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.685451Z"},"links":{"cited_paper":"/paper/2401.03729","citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:4480010bcf7c24eacf3af5f931de1c047b87f233a63ae369604a5ca38c0a99d0","observation_id":"82edd1f4-63aa-4f5d-b684-a8351c01cf05","resolution":{"observed_at":"2026-08-06T21:34:41.685451Z","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":"2026-08-06T21:34:41.770580Z","title":"mlco2/codecarbon: v2.4.1,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:41.770580Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:c9c96d3163a3b5ffd8b7aad7fe9c0fd51d4828f196b59e569f541b3e213d6c23","observation_id":"03faa283-0c0a-4144-99fc-b4a400fd64a9","resolution":{"observed_at":"2026-08-06T21:34:41.770580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:34:45.341859Z","title":"Available: https://www.aljazeera.com/news/2015/10/1/ indian-mob-kills-man-over-beef-eating-rumour","venue":null,"work_id":"e1c23331-66ed-4810-85e6-8f05d36aedbf","year":2015},"citing_paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages","version":1},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-06T21:34:36.900186Z"},"links":{"citing_paper":"/paper/2506.23930"},"observation_digest":"sha256:f537c109b2e0e7fac91170f78842e2f8b0d3fa29d5bfa25c6ad0a948749125fd","observation_id":"ab030972-1ab9-486d-8afb-da1fc485656e","resolution":{"observed_at":"2026-08-06T21:34:45.346902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.23930","last_updated":"2025-06-30T14:59:25Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T01:18:18.154813Z","submitted_at":"2025-06-30T14:59:25Z","title":"Leveraging the Potential of Prompt Engineering for Hate Speech Detection in Low-Resource Languages"},"reference_resolution":{"displayed":66,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":20,"verified_exact":8,"verified_fuzzy":38},"total_outbound_references":66},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2506.23930."}