{"id":"https://openalex.org/W7163222964","doi":"https://doi.org/10.48550/arxiv.2606.00523","title":"ProactiveLLM: Learning Active Interaction for Streaming Large Language Models","display_name":"ProactiveLLM: Learning Active Interaction for Streaming Large Language Models","publication_year":2026,"publication_date":"2026-05-30","ids":{"openalex":"https://openalex.org/W7163222964","doi":"https://doi.org/10.48550/arxiv.2606.00523"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.00523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00523","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.00523","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5137684137","display_name":"Junlong Tong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong, Junlong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137645539","display_name":"Yao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137651915","display_name":"Anhao Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Anhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137670219","display_name":"Yingqi Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan, Yingqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137623097","display_name":"Yunpu Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Yunpu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5137674639","display_name":"Xiaoyu Shen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Xiaoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.39879998564720154,"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":0.39879998564720154,"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/T13629","display_name":"Text Readability and Simplification","score":0.1565999984741211,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06960000097751617,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/latency","display_name":"Latency (audio)","score":0.642300009727478},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5181999802589417},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.43209999799728394},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.42089998722076416},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.33410000801086426},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3052999973297119}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8025000095367432},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.642300009727478},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5181999802589417},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4388999938964844},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43209999799728394},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.42089998722076416},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3671000003814697},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33230000734329224},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C74672266","wikidata":"https://www.wikidata.org/wiki/Q815859","display_name":"Language acquisition","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C2777851325","wikidata":"https://www.wikidata.org/wiki/Q7094102","display_name":"Online model","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28200000524520874},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.00523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00523","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.00523","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.00523","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.44068822264671326,"display_name":"Peace, Justice and strong institutions"},{"id":"https://metadata.un.org/sdg/4","score":0.42269232869148254,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Standard":[0],"Large":[1],"Language":[2],"Models":[3],"(LLMs)":[4],"follow":[5],"a":[6,137,173],"read-then-generate":[7],"paradigm,":[8],"causing":[9],"unnecessary":[10],"latency":[11,198],"and":[12,96,117,188,207],"computation.":[13],"Streaming":[14],"LLMs":[15],"alleviate":[16],"this":[17,58],"issue":[18],"by":[19,67,142],"generating":[20],"while":[21,199],"receiving":[22],"inputs,":[23],"but":[24],"still":[25],"struggle":[26],"to":[27,30,73,81,107,121,151],"decide":[28],"when":[29],"interact":[31],"with":[32,136],"the":[33,69,108,119,132,143,153,177],"stream.":[34],"Existing":[35],"methods":[36],"either":[37],"hard-code":[38],"interaction":[39,66,75,197],"timing":[40,50],"or":[41,54,170],"rely":[42],"on":[43],"costly":[44],"external":[45,168],"alignment":[46],"signals,":[47],"such":[48],"as":[49],"labels,":[51],"reasoning":[52],"trajectories,":[53],"stronger":[55],"teachers.":[56],"In":[57],"paper,":[59],"we":[60],"propose":[61],"ProactiveLLM,":[62],"which":[63],"achieves":[64],"active":[65,208],"leveraging":[68],"model's":[70],"endogenous":[71,163],"states":[72],"guide":[74,152],"decisions.":[76],"The":[77,101,129],"model":[78,120],"first":[79],"learns":[80],"perceive":[82],"semantic":[83,124],"sufficiency":[84,164],"from":[85,126],"partial":[86],"inputs":[87,116],"through":[88],"two":[89],"complementary":[90],"training":[91],"mechanisms:":[92],"mask-based":[93],"streaming":[94,115,190],"modeling":[95],"synchronized":[97],"privileged":[98,148],"self-distillation":[99],"(SPSD).":[100],"former":[102],"applies":[103],"monotonic":[104],"random":[105],"masking":[106],"input":[109],"during":[110],"training,":[111],"simulating":[112],"progressively":[113],"revealed":[114],"enabling":[118],"learn":[122],"local":[123],"dependencies":[125],"partial-input":[127],"views.":[128],"latter":[130],"aligns":[131],"partial-context":[133],"student":[134],"view":[135,140],"full-context":[138,149],"teacher":[139],"generated":[141],"same":[144],"evolving":[145],"model,":[146],"allowing":[147],"evidence":[150],"student's":[154],"understanding":[155],"under":[156],"incomplete":[157],"observations.":[158],"Together,":[159],"these":[160],"mechanisms":[161],"induce":[162],"cues":[165],"without":[166],"requiring":[167],"teachers":[169],"annotations,":[171],"providing":[172],"versatile":[174],"foundation":[175],"for":[176,205],"plug-and-play":[178],"integration":[179],"of":[180],"diverse":[181],"decision":[182],"heads.":[183],"Extensive":[184],"evaluation":[185],"across":[186],"text":[187],"speech":[189],"tasks":[191],"confirms":[192],"that":[193],"ProactiveLLM":[194],"significantly":[195],"reduces":[196],"maintaining":[200],"quality,":[201],"validating":[202],"its":[203],"capacity":[204],"dynamic":[206],"interaction.":[209],"Code":[210],"is":[211],"publicly":[212],"available":[213],"at":[214],"https://github.com/EIT-NLP/StreamingLLM/tree/main/ProactiveLLM.":[215]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-03T00:00:00"}
