{"id":"https://openalex.org/W6940826299","doi":"https://doi.org/10.1145/3714394.3756289","title":"Can Large Language Models Identify Materials from Radar Signals?","display_name":"Can Large Language Models Identify Materials from Radar Signals?","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W6940826299","doi":"https://doi.org/10.1145/3714394.3756289"},"language":"en","primary_location":{"id":"doi:10.1145/3714394.3756289","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3714394.3756289","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":"Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3714394.3756289","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiangyou Zhu","orcid":"https://orcid.org/0000-0003-1512-6784"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiangyou Zhu","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongyu Deng","orcid":"https://orcid.org/0009-0003-5935-9050"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyu Deng","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":null,"display_name":"He Chen","orcid":"https://orcid.org/0000-0001-8886-9680"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He Chen","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong SAR, China"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":1.9408,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90219644,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1486","last_page":"1492"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10451","display_name":"Mycorrhizal Fungi and Plant Interactions","score":0.5636000037193298,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10451","display_name":"Mycorrhizal Fungi and Plant Interactions","score":0.5636000037193298,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.09430000185966492,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10825","display_name":"Plant Pathogens and Fungal Diseases","score":0.043800000101327896,"subfield":{"id":"https://openalex.org/subfields/1307","display_name":"Cell Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6503999829292297},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5060999989509583},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4875999987125397},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.48429998755455017},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.4731000065803528},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.36340001225471497},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.35510000586509705}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6764000058174133},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6503999829292297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5072000026702881},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5060999989509583},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4875999987125397},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.48429998755455017},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.4731000065803528},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.36340001225471497},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35190001130104065},{"id":"https://openalex.org/C84236424","wikidata":"https://www.wikidata.org/wiki/Q1028695","display_name":"Fire-control radar","level":5,"score":0.32690000534057617},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C161475128","wikidata":"https://www.wikidata.org/wiki/Q6746448","display_name":"Man-portable radar","level":5,"score":0.296999990940094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2921999990940094},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2842000126838684},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.2662000060081482},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2653000056743622}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3714394.3756289","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3714394.3756289","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":"Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2508.03120","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2508.03120","pdf_url":"https://arxiv.org/pdf/2508.03120","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3714394.3756289","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3714394.3756289","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":"Companion of the 2025 ACM International Joint Conference on Pervasive and Ubiquitous Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5011051893234253,"id":"https://metadata.un.org/sdg/4","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":{"Accurately":[0],"identifying":[1,59],"the":[2,60,101,124,131,152,157,192,206,218,225,234],"material":[3,35,61,111,240,267],"composition":[4,62,112],"of":[5,63,105,127,159,186,258],"objects":[6],"is":[7,120,227],"a":[8,30,172,184,199,256],"critical":[9],"capability":[10],"for":[11,34,265],"AI":[12],"robots":[13],"powered":[14],"by":[15],"large":[16],"language":[17],"models":[18],"(LLMs)":[19],"to":[20,40,73,83,108,123,140,155,162,204,213,229],"perform":[21,230],"context-aware":[22],"manipulation.":[23],"Radar":[24],"technologies":[25,53],"(e.g.,":[26],"millimeter-wave":[27],"radar)":[28],"offer":[29],"promising":[31],"sensing":[32],"modality":[33],"recognition":[36,241],"tasks,":[37],"providing":[38],"robustness":[39],"lighting":[41],"conditions":[42],"and":[43,77,130,215],"high":[44],"spatial":[45],"resolution.":[46],"When":[47],"combined":[48],"with":[49,208],"deep":[50,85],"learning,":[51],"radar":[52,115,128,142,167,180,236,245],"have":[54,136],"demonstrated":[55],"strong":[56,263],"potential":[57,264],"in":[58],"various":[64],"objects.":[65],"However,":[66],"existing":[67],"radar-based":[68],"solutions":[69],"are":[70],"often":[71],"constrained":[72],"closed-set":[74],"object":[75],"categories":[76],"typically":[78],"require":[79],"task-specific":[80],"data":[81,143,182],"collection":[82],"train":[84],"learning":[86],"models,":[87],"largely":[88],"limiting":[89],"their":[90],"practical":[91],"applicability.":[92],"This":[93],"raises":[94],"an":[95],"important":[96],"question:":[97],"Can":[98],"we":[99,149,170,197],"leverage":[100],"powerful":[102],"reasoning":[103,232],"capabilities":[104],"pre-trained":[106,134],"LLMs":[107,135,161],"directly":[109,165,242],"infer":[110],"from":[113,166,243],"raw":[114,141,181,244],"signals?":[116],"Answering":[117],"this":[118,223],"question":[119],"non-trivial":[121],"due":[122],"inherent":[125],"redundancy":[126],"signals":[129],"fact":[132],"that":[133,177,190,250],"no":[137],"prior":[138],"exposure":[139],"during":[144],"training.":[145],"To":[146],"address":[147],"this,":[148],"introduce":[150,171],"LLMaterial,":[151],"first":[153],"study":[154],"investigate":[156],"feasibility":[158],"using":[160],"identify":[163],"materials":[164],"signals.":[168,246],"First,":[169],"physics-informed":[173],"signal":[174],"processing":[175],"pipeline":[176],"distills":[178],"high-redundancy":[179],"into":[183],"set":[185],"compact":[187],"intermediate":[188,220],"parameters":[189],"encapsulate":[191],"material's":[193],"intrinsic":[194],"characteristics.":[195],"Second,":[196],"adopt":[198],"retrieval-augmented":[200],"generation":[201],"(RAG)":[202],"strategy":[203],"provide":[205],"LLM":[207,226],"domain-specific":[209],"knowledge,":[210],"enabling":[211],"it":[212],"interpret":[214],"reason":[216],"over":[217],"extracted":[219],"parameters.":[221],"Leveraging":[222],"integration,":[224],"empowered":[228],"step-by-step":[231],"on":[233],"condensed":[235],"features,":[237],"achieving":[238],"open-set":[239],"Preliminary":[247],"results":[248],"show":[249],"LLMaterial":[251],"can":[252],"effectively":[253],"distinguish":[254],"among":[255],"variety":[257],"common":[259],"materials,":[260],"highlighting":[261],"its":[262],"real-world":[266],"identification":[268],"applications.":[269]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-30T23:08:21.542490","created_date":"2025-10-10T00:00:00"}