{"id":"https://openalex.org/W4416017642","doi":"https://doi.org/10.1145/3746252.3761389","title":"Querier-Aware LLM: Generating Personalized Responses to the Same Query from Different Queriers","display_name":"Querier-Aware LLM: Generating Personalized Responses to the Same Query from Different Queriers","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416017642","doi":"https://doi.org/10.1145/3746252.3761389"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761389","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109578074","display_name":"Hang Zeng","orcid":"https://orcid.org/0009-0009-6841-9872"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hang Zeng","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103086027","display_name":"Chaoyue Niu","orcid":"https://orcid.org/0000-0002-1650-4233"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaoyue Niu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059190563","display_name":"Fan Wu","orcid":"https://orcid.org/0000-0003-0965-9058"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Wu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020976131","display_name":"Chengfei Lv","orcid":"https://orcid.org/0009-0000-4918-7425"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengfei Lv","raw_affiliation_strings":["Alibaba Group, Hangzhou, Zhejiang, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, Zhejiang, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100428808","display_name":"Guihai Chen","orcid":"https://orcid.org/0000-0002-6934-1685"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guihai Chen","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109578074"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17562852,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4024","last_page":"4035"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.3919999897480011,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.3919999897480011,"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/T10028","display_name":"Topic Modeling","score":0.30640000104904175,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.1071000024676323,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/personalization","display_name":"Personalization","score":0.6280999779701233},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.5541999936103821},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4991999864578247},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4860000014305115},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.46810001134872437},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4498000144958496},{"id":"https://openalex.org/keywords/query-language","display_name":"Query language","score":0.4480000138282776},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.44209998846054077},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.41339999437332153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8149999976158142},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.6280999779701233},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.5541999936103821},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4991999864578247},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4860000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47909998893737793},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.46810001134872437},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4498000144958496},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.4480000138282776},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4366999864578247},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4309000074863434},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.41339999437332153},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.39969998598098755},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C44083865","wikidata":"https://www.wikidata.org/wiki/Q3853443","display_name":"Mean reciprocal rank","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.3749000132083893},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.37389999628067017},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.336899995803833},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.26170000433921814},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2549999952316284},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761389","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761389","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2890394457","https://openalex.org/W2892816441","https://openalex.org/W2962739339","https://openalex.org/W2963825865","https://openalex.org/W2964352131","https://openalex.org/W2965718149","https://openalex.org/W3108655343","https://openalex.org/W3153128630","https://openalex.org/W3168255966","https://openalex.org/W4214480085","https://openalex.org/W4225824663","https://openalex.org/W4313483544","https://openalex.org/W4361193900","https://openalex.org/W4382202741","https://openalex.org/W4385570019","https://openalex.org/W4385571282","https://openalex.org/W4385734157","https://openalex.org/W4386044041","https://openalex.org/W4388488609","https://openalex.org/W4389156999","https://openalex.org/W4389518937","https://openalex.org/W4389518991","https://openalex.org/W4389519254","https://openalex.org/W4389519488","https://openalex.org/W4389524521","https://openalex.org/W4390307246","https://openalex.org/W4396758712","https://openalex.org/W4396820243","https://openalex.org/W4399553892","https://openalex.org/W4400064841","https://openalex.org/W4401834466","https://openalex.org/W4402670540","https://openalex.org/W4402671806","https://openalex.org/W4402671884","https://openalex.org/W4402684061","https://openalex.org/W4402954178","https://openalex.org/W4404782947"],"related_works":[],"abstract_inverted_index":{"Existing":[0],"work":[1],"on":[2,89,97],"large":[3],"language":[4],"model":[5,47],"(LLM)":[6],"personalization":[7],"assigned":[8],"different":[9,33,41,80],"responding":[10],"roles":[11],"to":[12,163,174],"LLMs,":[13],"but":[14],"overlooked":[15],"the":[16,37,68,72,84,94,102,112,152],"diversity":[17,88],"of":[18,28,71,79,86,104,114,154,161],"queriers.":[19,42,81],"In":[20],"this":[21],"work,":[22],"we":[23,92,120],"propose":[24],"a":[25,45,50,55,123],"new":[26],"form":[27],"querier-aware":[29,118],"LLM":[30],"personalization,":[31,119],"generating":[32],"responses":[34],"even":[35],"for":[36,117],"same":[38,73],"query":[39,87,98],"from":[40,126,172],"We":[43,58],"design":[44,149],"dual-tower":[46],"architecture":[48],"with":[49,63,177],"cross-querier":[51],"general":[52],"encoder":[53],"and":[54,100,128,141,168],"querier-specific":[56],"encoder.":[57],"further":[59],"apply":[60],"contrastive":[61,105],"learning":[62,106],"multi-view":[64],"augmentation,":[65],"pulling":[66,76],"close":[67],"dialogue":[69],"representations":[70],"querier,":[74],"while":[75],"apart":[77],"those":[78],"To":[82,110],"mitigate":[83],"impact":[85],"querier-contrastive":[90],"learning,":[91],"cluster":[93],"dialogues":[95],"based":[96],"similarity":[99],"restrict":[101],"scope":[103],"within":[107],"each":[108],"cluster.":[109],"address":[111],"lack":[113],"datasets":[115],"designed":[116],"also":[121],"build":[122],"multi-querier":[124],"dataset":[125],"English":[127],"Chinese":[129],"scripts,":[130],"as":[131,133],"well":[132],"WeChat":[134],"records,":[135],"called":[136],"MQDialog,":[137],"containing":[138],"173":[139],"queriers":[140],"12":[142],"responders.":[143],"Extensive":[144],"evaluations":[145],"demonstrate":[146],"that":[147],"our":[148],"significantly":[150],"improves":[151],"quality":[153],"personalized":[155],"response":[156],"generation,":[157],"achieving":[158],"relative":[159],"improvement":[160],"8.4%":[162],"48.7%":[164],"in":[165],"ROUGE-L":[166],"scores":[167],"winning":[169],"rates":[170],"ranging":[171],"54%":[173],"82%":[175],"compared":[176],"various":[178],"baseline":[179],"methods.":[180]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-08T00:00:00"}