{"id":"https://openalex.org/W4416749205","doi":"https://doi.org/10.1109/iros60139.2025.11246909","title":"Enhanced Motion Forecasting with Plug-and-Play Multimodal Large Language Models","display_name":"Enhanced Motion Forecasting with Plug-and-Play Multimodal Large Language Models","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416749205","doi":"https://doi.org/10.1109/iros60139.2025.11246909"},"language":"en","primary_location":{"id":"doi:10.1109/iros60139.2025.11246909","doi":"https://doi.org/10.1109/iros60139.2025.11246909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246909","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.17274","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110725449","display_name":"Katie Z Luo","orcid":"https://orcid.org/0009-0008-5797-534X","observed_orcids":["https://orcid.org/0009-0008-5797-534X"]},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katie Luo","raw_affiliation_strings":["Cornell University,Computer and Information Sciences Department"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University,Computer and Information Sciences Department","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019481782","display_name":"Jingwei Ji","orcid":"https://orcid.org/0000-0001-8815-3017","observed_orcids":["https://orcid.org/0000-0001-8815-3017","https://orcid.org/0000-0002-9527-8296"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jingwei Ji","raw_affiliation_strings":["Waymo LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waymo LLC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100604494","display_name":"Tong He","orcid":"https://orcid.org/0000-0003-2772-9320","observed_orcids":["https://orcid.org/0000-0003-2772-9320"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tong He","raw_affiliation_strings":["Waymo LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waymo LLC","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100700826","display_name":"Runsheng Xu","orcid":"https://orcid.org/0000-0001-7375-9833","observed_orcids":["https://orcid.org/0000-0001-7375-9833"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Runsheng Xu","raw_affiliation_strings":["Waymo LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waymo LLC","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yichen Xie","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yichen Xie","raw_affiliation_strings":["UC Berkeley"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UC Berkeley","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081024054","display_name":"Dragomir Anguelov","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dragomir Anguelov","raw_affiliation_strings":["Waymo LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waymo LLC","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110774377","display_name":"Mingxing Tan","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mingxing Tan","raw_affiliation_strings":["Waymo LLC"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Waymo LLC","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8731,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.6858886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"12510","last_page":"12517"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9848999977111816,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0015999999595806003,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.00139999995008111,"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/motion-prediction","display_name":"motion prediction","score":0.9610000252723694},{"id":"https://openalex.org/keywords/autonomous-driving","display_name":"autonomous driving","score":0.6919999718666077},{"id":"https://openalex.org/keywords/multimodal-large-language-models","display_name":"multimodal large language models","score":0.9340000152587891},{"id":"https://openalex.org/keywords/behavior-prediction","display_name":"behavior prediction","score":0.6830000281333923},{"id":"https://openalex.org/keywords/zero-shot-reasoning","display_name":"zero-shot reasoning","score":0.6859999895095825},{"id":"https://openalex.org/keywords/waymo-open-dataset","display_name":"Waymo Open Dataset","score":0.9070000052452087},{"id":"https://openalex.org/keywords/nuscenes","display_name":"nuScenes","score":1.0}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7829999923706055},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.7360000014305115},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6463000178337097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5446000099182129},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.49639999866485596},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.41110000014305115},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3285999894142151},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.28519999980926514},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.2685999870300293},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.2612000107765198},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.2596000134944916}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iros60139.2025.11246909","doi":"https://doi.org/10.1109/iros60139.2025.11246909","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11246909","pdf_url":null,"source":{"id":"https://openalex.org/S4393918188","display_name":"IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":"2153-0858","issn":["2153-0858"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1","norway-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2510.17274","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17274","pdf_url":"https://arxiv.org/pdf/2510.17274","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.17274","doi":"https://doi.org/10.48550/arxiv.2510.17274","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.17274","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.17274","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.17274","pdf_url":"https://arxiv.org/pdf/2510.17274","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320308335","display_name":"American Association of University Women","ror":"https://ror.org/05hrczs03"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416749205.pdf","grobid_xml":"https://content.openalex.org/works/W4416749205.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2794787653","https://openalex.org/W2925148167","https://openalex.org/W2940718442","https://openalex.org/W2943516367","https://openalex.org/W2949708697","https://openalex.org/W2963759562","https://openalex.org/W2968008415","https://openalex.org/W2980160556","https://openalex.org/W3090789587","https://openalex.org/W3108486966","https://openalex.org/W3125926538","https://openalex.org/W3156216502","https://openalex.org/W3214950490","https://openalex.org/W4294016731","https://openalex.org/W4312894406","https://openalex.org/W4383172002","https://openalex.org/W4385346108","https://openalex.org/W4386076400","https://openalex.org/W4390041933","https://openalex.org/W4390872108","https://openalex.org/W4390873481","https://openalex.org/W4401386967","https://openalex.org/W4401416505","https://openalex.org/W4402772377","https://openalex.org/W4402781630","https://openalex.org/W4403853618","https://openalex.org/W4404350186","https://openalex.org/W4404769984","https://openalex.org/W4404820176"],"related_works":["https://openalex.org/W6979275462","https://openalex.org/W4405254198","https://openalex.org/W4383172002","https://openalex.org/W4405785518","https://openalex.org/W4416749619","https://openalex.org/W4386083117","https://openalex.org/W4390872108","https://openalex.org/W7139052593","https://openalex.org/W4414879644","https://openalex.org/W4281965085"],"abstract_inverted_index":{"Current":[0],"autonomous":[1],"driving":[2],"systems":[3],"rely":[4],"on":[5,55,130],"specialized":[6],"models":[7,46,51,135],"for":[8],"perceiving":[9],"and":[10,68,88,142],"predicting":[11],"motion,":[12],"which":[13],"demonstrate":[14],"reliable":[15],"performance":[16,148],"in":[17,114],"standard":[18],"conditions.":[19],"However,":[20],"generalizing":[21],"cost-effectively":[22],"to":[23,66,75,81,95,110,124],"diverse":[24],"real-world":[25],"scenarios":[26],"remains":[27],"a":[28,38,62],"significant":[29,112],"challenge.":[30],"To":[31],"address":[32],"this,":[33],"we":[34],"propose":[35],"Plug-and-Forecast":[36],"(PnF),":[37],"plug-and-play":[39],"approach":[40,129],"that":[41,58],"augments":[42],"existing":[43,97],"motion":[44,115,133],"forecasting":[45,134],"with":[47],"multimodal":[48],"large":[49],"language":[50,60],"(MLLMs).":[52],"PnF":[53],"builds":[54],"the":[56,104,137,143],"insight":[57],"natural":[59],"provides":[61],"more":[63],"effective":[64],"way":[65],"describe":[67],"handle":[69],"complex":[70],"scenarios,":[71],"enabling":[72],"quick":[73],"adaptation":[74],"targeted":[76],"behaviors.":[77],"We":[78,126],"design":[79],"prompts":[80],"extract":[82],"structured":[83],"scene":[84],"understanding":[85],"from":[86],"MLLMs":[87,109],"distill":[89],"this":[90],"information":[91],"into":[92],"learnable":[93],"embeddings":[94],"augment":[96],"behavior":[98],"prediction":[99,116],"models.":[100],"Our":[101],"method":[102],"leverages":[103],"zero-shot":[105],"reasoning":[106],"capabilities":[107],"of":[108],"achieve":[111],"improvements":[113,149],"performance,":[117],"while":[118],"requiring":[119],"no":[120],"fine-tuning\u2014making":[121],"it":[122],"practical":[123],"adopt.":[125],"validate":[127],"our":[128],"two":[131],"state-of-the-art":[132],"using":[136],"Waymo":[138],"Open":[139],"Motion":[140],"Dataset":[141],"nuScenes":[144],"Dataset,":[145],"demonstrating":[146],"consistent":[147],"across":[150],"both":[151],"benchmarks.":[152]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2025-11-28T00:00:00"}
