{"id":"https://openalex.org/W4415538819","doi":"https://doi.org/10.1145/3746027.3755865","title":"Neural Additive Adapters for Interpretable Nutrition Prediction","display_name":"Neural Additive Adapters for Interpretable Nutrition Prediction","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538819","doi":"https://doi.org/10.1145/3746027.3755865"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3755865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755865","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3755865","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054276608","display_name":"Vitalii Emelianov","orcid":"https://orcid.org/0000-0002-0828-156X"},"institutions":[{"id":"https://openalex.org/I129043915","display_name":"University of Udine","ror":"https://ror.org/05ht0mh31","country_code":"IT","type":"education","lineage":["https://openalex.org/I129043915"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Vitalii Emelianov","raw_affiliation_strings":["Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy","institution_ids":["https://openalex.org/I129043915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005142628","display_name":"Niki Martinel","orcid":"https://orcid.org/0000-0002-6962-8643"},"institutions":[{"id":"https://openalex.org/I129043915","display_name":"University of Udine","ror":"https://ror.org/05ht0mh31","country_code":"IT","type":"education","lineage":["https://openalex.org/I129043915"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Niki Martinel","raw_affiliation_strings":["Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Computer Science and Physics, University of Udine, Udine, Italy","institution_ids":["https://openalex.org/I129043915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054276608"],"corresponding_institution_ids":["https://openalex.org/I129043915"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16337049,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9062","last_page":"9070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9850000143051147,"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":0.9850000143051147,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9599999785423279,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9584000110626221,"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/generalization","display_name":"Generalization","score":0.6488000154495239},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5024999976158142},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.42910000681877136},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4041000008583069},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3774999976158142},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.26899999380111694}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6262000203132629},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5253999829292297},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5180000066757202},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5024999976158142},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.42910000681877136},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4041000008583069},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3774999976158142},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C2987718291","wikidata":"https://www.wikidata.org/wiki/Q2095","display_name":"Food products","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3755865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755865","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:air.uniud.it:11390/1308572","is_oa":true,"landing_page_url":"https://hdl.handle.net/11390/1308572","pdf_url":null,"source":{"id":"https://openalex.org/S4306401163","display_name":"Institutional Research Information System (University of Udine)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I129043915","host_organization_name":"University of Udine","host_organization_lineage":["https://openalex.org/I129043915"],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3746027.3755865","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755865","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W12634471","https://openalex.org/W2000105909","https://openalex.org/W2166163519","https://openalex.org/W2183341477","https://openalex.org/W2466671568","https://openalex.org/W2616247523","https://openalex.org/W3137125108","https://openalex.org/W3159481202","https://openalex.org/W4313156423","https://openalex.org/W4376870287","https://openalex.org/W4387961644","https://openalex.org/W4389082898","https://openalex.org/W4394597976","https://openalex.org/W4405481086","https://openalex.org/W4409347607"],"related_works":[],"abstract_inverted_index":{"We":[0,28,58],"study":[1],"how":[2],"large":[3],"vision":[4],"models":[5,114],"(LVMs)":[6],"can":[7],"predict":[8],"food":[9,100],"nutrition":[10,31,44,52,67,74],"through":[11],"lightweight":[12,104],"and":[13,40,118],"interpretable":[14,62,93],"adapters---the":[15],"machine":[16],"learning":[17],"modules":[18],"the":[19,42,49,66,77,88,112,116,119],"predictions":[20],"of":[21,51,72,90],"which":[22],"could":[23],"be":[24],"understood":[25],"by":[26,37],"humans.":[27],"introduce":[29],"novel":[30,92],"adapters":[32,94],"that":[33],"use":[34,59],"features":[35],"extracted":[36],"pre-trained":[38],"LVMs":[39,97],"output":[41],"so-called":[43],"maps.":[45,78],"Nutrition":[46],"maps":[47],"indicate":[48],"concentration":[50],"values":[53],"per":[54],"each":[55],"image":[56],"location.":[57],"such":[60],"an":[61],"representation":[63],"to":[64],"obtain":[65],"targets":[68],"as":[69],"a":[70],"sum":[71],"all":[73],"concentrations":[75],"on":[76,115],"To":[79],"understand":[80],"our":[81,91],"approach's":[82],"generalization":[83],"capability,":[84],"we":[85],"systematically":[86],"analyze":[87],"behavior":[89],"leveraging":[95],"different":[96,99],"with":[98],"image-nutrition":[101],"datasets.":[102],"Our":[103],"approach":[105],"delivers":[106],"better":[107],"or":[108],"on-par":[109],"performance":[110],"than":[111],"state-of-the-art":[113],"Nutrition5k":[117],"Nutritionverse-Real":[120],"benchmarks.":[121],"The":[122],"code":[123],"is":[124],"provided":[125],"at":[126],"https://github.com/vitaly-emelianov/nutrition-adapters.":[127]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-25T00:00:00"}