{"id":"https://openalex.org/W7164919719","doi":"https://doi.org/10.48550/arxiv.2606.15898","title":"VL2Spike: Spike-driven Distillation from VLMs for Low-Power Visual Perception in Embodied AI","display_name":"VL2Spike: Spike-driven Distillation from VLMs for Low-Power Visual Perception in Embodied AI","publication_year":2026,"publication_date":"2026-06-14","ids":{"openalex":"https://openalex.org/W7164919719","doi":"https://doi.org/10.48550/arxiv.2606.15898"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.15898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15898","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,"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":null,"license_id":null,"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.2606.15898","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056678476","display_name":"Zinan Liu","orcid":"https://orcid.org/0000-0001-6874-6050"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109538974","display_name":"Eric Zheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Eric","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043879030","display_name":"Soumyaratna Debnath","orcid":"https://orcid.org/0000-0002-3690-7216"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Debnath, Soumyaratna","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138703513","display_name":"Hao Shi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shi, Hao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100925927","display_name":"Ling Xiao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiao, Ling","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138709548","display_name":"Lin Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lin","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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.583299994468689,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.583299994468689,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.11779999732971191,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.08160000294446945,"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/leverage","display_name":"Leverage (statistics)","score":0.6534000039100647},{"id":"https://openalex.org/keywords/embodied-cognition","display_name":"Embodied cognition","score":0.5389000177383423},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5260000228881836},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.46950000524520874},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4602000117301941},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.44760000705718994},{"id":"https://openalex.org/keywords/spike","display_name":"Spike (software development)","score":0.4406999945640564},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4278999865055084},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4219000041484833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7117999792098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6563000082969666},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6534000039100647},{"id":"https://openalex.org/C100609095","wikidata":"https://www.wikidata.org/wiki/Q1335050","display_name":"Embodied cognition","level":2,"score":0.5389000177383423},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5260000228881836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4869999885559082},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.46950000524520874},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4602000117301941},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.44760000705718994},{"id":"https://openalex.org/C2781390188","wikidata":"https://www.wikidata.org/wiki/Q25203449","display_name":"Spike (software development)","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4278999865055084},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4219000041484833},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4115000069141388},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.382099986076355},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.33660000562667847},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C2777206241","wikidata":"https://www.wikidata.org/wiki/Q194431","display_name":"Paragraph","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C2777508537","wikidata":"https://www.wikidata.org/wiki/Q7936620","display_name":"Visual reasoning","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28189998865127563},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26339998841285706},{"id":"https://openalex.org/C2778251979","wikidata":"https://www.wikidata.org/wiki/Q7936617","display_name":"Visual processing","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25540000200271606},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.15898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15898","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.15898","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.15898","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,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.8281272649765015,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Spiking":[0],"neural":[1],"networks":[2],"(SNNs)":[3],"are":[4,43],"brain-inspired,":[5],"event-driven":[6],"models":[7,28,69,123],"that":[8,105,193,208],"compute":[9],"with":[10,29,111,147,200,217,234],"sparse":[11],"spikes,":[12],"which":[13,158],"enables":[14],"highly":[15],"efficient":[16],"visual":[17,79,154,230],"perception":[18,244],"in":[19,245],"resource-constrained":[20],"embodied":[21,246],"AI":[22],"models.":[23,114],"The":[24],"emergence":[25],"of":[26,38,121,237],"Spiking-Transformer":[27],"spike":[30,155,169,180,187],"self-attention":[31],"has":[32],"substantially":[33],"improved":[34],"the":[35,52,118],"learning":[36,119],"capacity":[37,120,227],"pure":[39],"SNNs.":[40],"Although":[41],"SNNs":[42],"energy":[44,220],"efficient,":[45],"their":[46,126],"performance":[47],"is":[48,83],"still":[49],"limited":[50],"by":[51],"spike-based":[53,100],"architecture":[54],"and":[55,168,171,179,198],"optimization":[56],"challenges,":[57],"as":[58],"standard":[59],"gradient":[60],"descent":[61],"rules":[62],"cannot":[63],"be":[64],"directly":[65],"applied.":[66],"Recently,":[67],"vision-language":[68],"(VLMs)":[70],"have":[71],"shown":[72],"rich":[73],"multi-modal":[74,107],"knowledge":[75,101,108],"representation":[76],"capabilities":[77],"for":[78,88,242],"perception.":[80,137],"Thus,":[81],"it":[82],"promising":[84],"to":[85],"leverage":[86],"VLMs":[87,110],"better":[89],"Spikformer":[90,113,122],"training.":[91],"To":[92,145],"this":[93],"end,":[94],"we":[95,150],"present":[96],"VL2Spike,":[97],"a":[98,131,185,235],"novel":[99,186],"distillation":[102,191],"(KD)":[103],"framework":[104],"bridges":[106],"from":[109],"compact":[112],"This":[115],"design":[116,184],"enhances":[117],"while":[124],"preserving":[125],"energy-efficiency":[127],"merits,":[128],"thereby":[129],"offering":[130],"practical":[132],"pathway":[133],"toward":[134],"low-power":[135,243],"robotic":[136,229],"Our":[138],"VL2Spike":[139,209],"brings":[140],"two":[141],"key":[142],"technical":[143],"contributions.":[144],"align":[146],"spiking":[148],"dynamics,":[149],"first":[151],"propose":[152],"spatial-temporal":[153],"(SVS)":[156],"distillation,":[157],"achieves":[159,210],"(1)":[160],"shared":[161],"manifold":[162],"alignment":[163],"between":[164],"VLM":[165,202],"image":[166],"features":[167],"tokens,":[170],"(2)":[172],"warm-started":[173],"temporal":[174],"consistency":[175],"on":[176,228],"membrane":[177],"potentials":[178],"rates.":[181],"We":[182],"then":[183],"prototype-guided":[188],"linguistic":[189],"(SPL)":[190],"strategy":[192],"aligns":[194],"Spikformer's":[195],"class":[196],"prototypes":[197],"logits":[199],"promptable":[201],"text":[203],"embeddings.":[204],"Extensive":[205],"experiments":[206],"show":[207],"6.81%":[211],"gain":[212,236],"across":[213],"three":[214],"static":[215],"datasets":[216],"only":[218],"15.7%":[219],"consumption.":[221],"It":[222],"also":[223],"exhibits":[224],"strong":[225],"generalization":[226],"place":[231],"recognition":[232],"(VPR)":[233],"6.63%,":[238],"highlighting":[239],"its":[240],"potential":[241],"AI.":[247]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-17T00:00:00"}