{"id":"https://openalex.org/W7126401435","doi":"https://doi.org/10.18653/v1/2024.findings-eacl.55","title":"Probing Critical Learning Dynamics of PLMs for Hate Speech Detection","display_name":"Probing Critical Learning Dynamics of PLMs for Hate Speech Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W7126401435","doi":"https://doi.org/10.18653/v1/2024.findings-eacl.55"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2024.findings-eacl.55","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.55","pdf_url":"https://aclanthology.org/2024.findings-eacl.55.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2024.findings-eacl.55.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108334303","display_name":"Sarah Masud","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sarah Masud","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124612561","display_name":"Mohammad Shibly Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammad Aflah Khan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124690660","display_name":"Vikram Goyal","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vikram Goyal","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066369545","display_name":"Md Shad Akhtar","orcid":"https://orcid.org/0000-0002-2033-2382"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Md Shad Akhtar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5124639621","display_name":"Tanmoy Chakraborty","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tanmoy Chakraborty","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57256159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"826","last_page":"845"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.7545999884605408,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.7545999884605408,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.06210000067949295,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.014299999922513962,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dynamics","display_name":"Dynamics (music)","score":0.44670000672340393},{"id":"https://openalex.org/keywords/voice-activity-detection","display_name":"Voice activity detection","score":0.38929998874664307},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.34299999475479126},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.28060001134872437},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.2687000036239624}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5435000061988831},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4481000006198883},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.44670000672340393},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.38929998874664307},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.34299999475479126},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3391999900341034},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.27799999713897705},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2687000036239624},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2024.findings-eacl.55","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.55","pdf_url":"https://aclanthology.org/2024.findings-eacl.55.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2024.findings-eacl.55","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2024.findings-eacl.55","pdf_url":"https://aclanthology.org/2024.findings-eacl.55.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EACL 2024","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.4810488522052765,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7126401435.pdf","grobid_xml":"https://content.openalex.org/works/W7126401435.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Despite":[0],"the":[1,35,63,79,90,101,108],"widespread":[2],"adoption,":[3],"there":[4],"is":[5],"a":[6,84],"lack":[7],"of":[8,15,42,65,82,92,103],"research":[9,28],"into":[10,51,99],"how":[11],"various":[12],"critical":[13],"aspects":[14,41],"pretrained":[16,54],"language":[17],"models":[18,105],"(PLMs)":[19],"affect":[20],"their":[21,57],"performance":[22],"in":[23,45],"hate":[24,46,115],"speech":[25,47,116],"detection.Through":[26],"five":[27],"questions,":[29],"our":[30],"findings":[31],"and":[32,62,89,106],"recommendations":[33],"lay":[34],"groundwork":[36],"for":[37,74,110,113],"empirically":[38],"investigating":[39],"different":[40,53],"PLMs'":[43],"use":[44,102],"detection.We":[48],"deep":[49],"dive":[50],"comparing":[52],"models,":[55],"evaluating":[56],"seed":[58],"robustness,":[59],"finetuning":[60],"settings,":[61],"impact":[64],"pretraining":[66,87],"data":[67],"collection":[68],"time.Our":[69],"analysis":[70],"reveals":[71],"early":[72],"peaks":[73],"downstream":[75],"tasks":[76],"during":[77,95],"pretraining,":[78],"limited":[80],"benefit":[81],"employing":[83],"more":[85],"recent":[86],"corpus,":[88],"significance":[91],"specific":[93],"layers":[94],"finetuning.We":[96],"further":[97],"call":[98],"question":[100],"domain-specific":[104],"highlight":[107],"need":[109],"dynamic":[111],"datasets":[112],"benchmarking":[114],"detection.":[117]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-02T00:00:00"}