{"id":"https://openalex.org/W4416037069","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.189","title":"CIE: Controlling Language Model Text Generations Using Continuous Signals","display_name":"CIE: Controlling Language Model Text Generations Using Continuous Signals","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416037069","doi":"https://doi.org/10.18653/v1/2025.emnlp-main.189"},"language":null,"primary_location":{"id":"doi:10.18653/v1/2025.emnlp-main.189","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.189","pdf_url":"https://aclanthology.org/2025.emnlp-main.189.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":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/2025.emnlp-main.189.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072439636","display_name":"Vinay Samuel","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]},{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vinay Samuel","raw_affiliation_strings":["Carnegie Mellon University","University of Maryland , College Park ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]},{"raw_affiliation_string":"University of Maryland , College Park ,","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059967242","display_name":"Harshita Diddee","orcid":"https://orcid.org/0000-0002-0852-7371"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harshita Diddee","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395391","display_name":"Yiming Zhang","orcid":"https://orcid.org/0009-0000-9289-6227"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yiming Zhang","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022994077","display_name":"Daphne Ippolito","orcid":"https://orcid.org/0000-0001-9328-8995"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daphne Ippolito","raw_affiliation_strings":["Carnegie Mellon University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.29194307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3815","last_page":"3825"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.2305999994277954,"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/T10028","display_name":"Topic Modeling","score":0.2305999994277954,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.2160000056028366,"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/T12031","display_name":"Speech and dialogue systems","score":0.16590000689029694,"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/language-model","display_name":"Language model","score":0.4796999990940094},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3752000033855438},{"id":"https://openalex.org/keywords/language-identification","display_name":"Language identification","score":0.3221000134944916},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.29260000586509705},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.27630001306533813}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6456000208854675},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4846999943256378},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4797999858856201},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.4796999990940094},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C129792486","wikidata":"https://www.wikidata.org/wiki/Q1050419","display_name":"Language identification","level":3,"score":0.3221000134944916},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3206000030040741},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3077999949455261},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2025.emnlp-main.189","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.189","pdf_url":"https://aclanthology.org/2025.emnlp-main.189.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":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2025.emnlp-main.189","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2025.emnlp-main.189","pdf_url":"https://aclanthology.org/2025.emnlp-main.189.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":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416037069.pdf","grobid_xml":"https://content.openalex.org/works/W4416037069.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Aligning":[0],"language":[1,29,46,63,100],"models":[2],"(LMs)":[3],"with":[4],"user":[5,13],"intent":[6],"is":[7,133],"becoming":[8],"increasingly":[9],"relevant":[10],"to":[11,23,53,75,127],"enhance":[12],"experience.This":[14],"calls":[15],"for":[16,33],"designing":[17],"methods":[18,152,155],"that":[19,30,47,87,92,132,156],"can":[20,124],"allow":[21],"users":[22],"control":[24,56,67,84,130,148,159],"the":[25,28,36,39,42,45,114,158],"properties":[26],"of":[27,38,44,117],"LMs":[31],"generate,":[32],"example,":[34],"controlling":[35,113],"length":[37],"generation":[40],"or":[41,65,102,153],"complexity":[43],"gets":[48],"chosen.Most":[49],"existing":[50,104],"work":[51],"attempts":[52],"integrate":[54],"users'":[55],"by":[57],"conditioning":[58],"LM":[59,123],"generations":[60],"on":[61],"natural":[62,99],"prompts":[64],"discrete":[66,163],"signals,":[68,85],"which":[69],"are":[70,80],"often":[71],"brittle":[72],"and":[73,138],"hard":[74],"scale.In":[76],"this":[77],"work,":[78],"we":[79,119],"interested":[81],"in":[82,97,106,112],"continuous":[83],"ones":[86],"exist":[88],"along":[89],"a":[90,98,109,129,136,139,162],"spectrum":[91],"can't":[93],"easily":[94],"be":[95,125],"captured":[96],"prompt":[101],"via":[103],"techniques":[105],"conditional":[107],"generation.Through":[108],"case":[110],"study":[111],"precise":[115],"responselength":[116],"generations,":[118],"demonstrate":[120],"how":[121],"an":[122],"finetuned":[126],"expect":[128],"vector":[131],"interpolated":[134],"between":[135],"\"low\"":[137],"\"high\"":[140],"token":[141],"embedding.Our":[142],"method":[143],"more":[144],"reliably":[145],"exerts":[146],"response-length":[147],"than":[149],"in-context":[150],"learning":[151],"fine-tuning":[154],"represent":[157],"signal":[160],"as":[161],"signal.":[164]},"counts_by_year":[],"updated_date":"2026-08-23T07:36:19.812096","created_date":"2025-11-08T00:00:00"}
