{"id":"https://openalex.org/W7167911677","doi":"https://doi.org/10.1145/3805712.3809681","title":"Modular Representation Compression: Adapting LLM Representations for Efficient and Effective Recommendation","display_name":"Modular Representation Compression: Adapting LLM Representations for Efficient and Effective Recommendation","publication_year":2026,"publication_date":"2026-07-10","ids":{"openalex":"https://openalex.org/W7167911677","doi":"https://doi.org/10.1145/3805712.3809681"},"language":null,"primary_location":{"id":"doi:10.1145/3805712.3809681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809681","pdf_url":null,"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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805712.3809681","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013513956","display_name":"Yunjia Xi","orcid":"https://orcid.org/0000-0001-6883-881X"},"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"]},{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunjia Xi","raw_affiliation_strings":["Tencent Youtu Lab, Shanghai, China and Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-6883-881X","affiliations":[{"raw_affiliation_string":"Tencent Youtu Lab, Shanghai, China and Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930","https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034417837","display_name":"Menghui Zhu","orcid":"https://orcid.org/0000-0002-8567-2185"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menghui Zhu","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8567-2185","affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shanghai, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036057873","display_name":"Jianghao Lin","orcid":"https://orcid.org/0000-0002-8953-3203"},"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":"Jianghao Lin","raw_affiliation_strings":["Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8953-3203","affiliations":[{"raw_affiliation_string":"Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427434","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0003-3750-2533"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Chen","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3750-2533","affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shanghai, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054330014","display_name":"Ruiming Tang","orcid":"https://orcid.org/0000-0002-9224-2431"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiming Tang","raw_affiliation_strings":["Huawei Noah's Ark Lab, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9224-2431","affiliations":[{"raw_affiliation_string":"Huawei Noah's Ark Lab, Shanghai, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064534815","display_name":"Yong Yu","orcid":"https://orcid.org/0000-0003-4457-2820"},"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":"Yong Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4457-2820","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090720315","display_name":"Weinan Zhang","orcid":"https://orcid.org/0000-0002-0127-2425"},"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":"Weinan Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0127-2425","affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94538888,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2027","last_page":"2038"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6121000051498413,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6121000051498413,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.06159999966621399,"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/T14347","display_name":"Big Data and Digital Economy","score":0.029600000008940697,"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/modular-design","display_name":"Modular design","score":0.7253999710083008},{"id":"https://openalex.org/keywords/modularity","display_name":"Modularity (biology)","score":0.7006000280380249},{"id":"https://openalex.org/keywords/counterintuitive","display_name":"Counterintuitive","score":0.5579000115394592},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4875999987125397},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4156999886035919},{"id":"https://openalex.org/keywords/lift","display_name":"Lift (data mining)","score":0.41280001401901245},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.375},{"id":"https://openalex.org/keywords/rotation-formalisms-in-three-dimensions","display_name":"Rotation formalisms in three dimensions","score":0.34220001101493835}],"concepts":[{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.7253999710083008},{"id":"https://openalex.org/C2779478453","wikidata":"https://www.wikidata.org/wiki/Q6889748","display_name":"Modularity (biology)","level":2,"score":0.7006000280380249},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6913999915122986},{"id":"https://openalex.org/C101097943","wikidata":"https://www.wikidata.org/wiki/Q5176983","display_name":"Counterintuitive","level":2,"score":0.5579000115394592},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4875999987125397},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4156999886035919},{"id":"https://openalex.org/C139002025","wikidata":"https://www.wikidata.org/wiki/Q3001212","display_name":"Lift (data mining)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3955000042915344},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.375},{"id":"https://openalex.org/C171018156","wikidata":"https://www.wikidata.org/wiki/Q7370306","display_name":"Rotation formalisms in three dimensions","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.2919999957084656},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2842000126838684},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C100980136","wikidata":"https://www.wikidata.org/wiki/Q4668956","display_name":"Malleability","level":4,"score":0.2752000093460083},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C2781121602","wikidata":"https://www.wikidata.org/wiki/Q3504403","display_name":"Modular neural network","level":4,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805712.3809681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809681","pdf_url":null,"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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805712.3809681","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805712.3809681","pdf_url":null,"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 49th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4634098410606384,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1638081485","https://openalex.org/W2027461913","https://openalex.org/W2069870183","https://openalex.org/W2127176025","https://openalex.org/W2136189984","https://openalex.org/W2177066871","https://openalex.org/W2723293840","https://openalex.org/W2793768763","https://openalex.org/W2898085636","https://openalex.org/W2946044191","https://openalex.org/W2964182926","https://openalex.org/W2964184826","https://openalex.org/W2973171206","https://openalex.org/W3093945404","https://openalex.org/W4379382506","https://openalex.org/W4385562639","https://openalex.org/W4396722619","https://openalex.org/W4396723256","https://openalex.org/W4396734745","https://openalex.org/W4396757491","https://openalex.org/W4396758737","https://openalex.org/W4396843692","https://openalex.org/W4400118952","https://openalex.org/W4400524512","https://openalex.org/W4400606525","https://openalex.org/W4400909953","https://openalex.org/W4401042618","https://openalex.org/W4402671936","https://openalex.org/W4403220034","https://openalex.org/W4403577471","https://openalex.org/W4404639422","https://openalex.org/W4412394824","https://openalex.org/W7133214597"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"large":[1],"language":[2],"models":[3],"(LLMs)":[4],"have":[5,13],"advanced":[6],"recommendation":[7,83],"systems":[8],"(RSs),":[9],"and":[10,32,45,115,147,176,190],"recent":[11],"works":[12],"begun":[14],"to":[15,18,30,52,120,134,154,162,166,180],"explore":[16],"how":[17],"integrate":[19],"LLMs":[20,28,41,76,109],"into":[21],"industrial":[22],"RSs.":[23],"While":[24],"most":[25],"approaches":[26],"deploy":[27],"offline":[29],"generate":[31],"pre-cache":[33],"augmented":[34],"representations":[35,39,55,71],"for":[36],"RSs,":[37],"high-dimensional":[38],"from":[40,72,79],"introduce":[42],"substantial":[43],"storage":[44],"computational":[46],"costs.":[47],"Thus,":[48,127],"it":[49],"is":[50],"crucial":[51],"compress":[53,95],"LLM":[54,153],"effectively.":[56],"However,":[57],"we":[58,128],"identify":[59],"a":[60,158,197,207],"counterintuitive":[61],"phenomenon":[62],"during":[63],"representation":[64],"compression:":[65],"Mid-layer":[66],"Representation":[67,131],"Advantage":[68],"(MRA),":[69],"where":[70],"middle":[73],"layers":[74,81],"of":[75,139],"outperform":[77],"those":[78],"final":[80,87,98,118],"in":[82,122,201],"tasks.":[84,182],"This":[85],"degraded":[86],"layer":[88,119],"renders":[89],"existing":[90],"compression":[91,146],"methods,":[92],"which":[93],"typically":[94],"on":[96,105],"the":[97,117,123,137,152],"layer,":[99],"suboptimal.":[100],"We":[101],"interpret":[102],"this":[103],"based":[104],"modularity":[106,114,138],"theory":[107],"that":[108,186],"develop":[110],"spontaneous":[111],"internal":[112],"functional":[113],"force":[116],"specialize":[121],"proxy":[124],"training":[125],"task.":[126],"propose":[129],"Modular":[130,142,170],"Compression":[132],"(MARC)":[133],"explicitly":[135,144],"control":[136],"LLMs.":[140],"First,":[141],"Adjustment":[143],"introduces":[145],"task":[148],"adaptation":[149],"modules,":[150],"enabling":[151],"operate":[155],"strictly":[156],"as":[157],"representation-learning":[159],"module.":[160],"Next,":[161],"ground":[163],"each":[164],"module":[165],"its":[167],"specific":[168],"task,":[169],"Task":[171],"Decoupling":[172],"uses":[173],"information":[174],"constraints":[175],"different":[177],"network":[178],"structures":[179],"decouple":[181],"Extensive":[183],"experiments":[184],"validate":[185],"MARC":[187,195],"addresses":[188],"MRA":[189],"produces":[191],"efficient":[192],"representations.":[193],"Notably,":[194],"achieved":[196],"2.82%":[198],"eCPM":[199],"lift":[200],"an":[202],"online":[203],"A/B":[204],"test":[205],"within":[206],"large-scale":[208],"commercial":[209],"search":[210],"advertising":[211],"scenario.":[212]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-07-11T00:00:00"}
