{"id":"https://openalex.org/W7153731836","doi":"https://doi.org/10.1145/3772363.3798809","title":"Diegetic Explanations for Uncertain Sensing: Materializing Confidence and Jitter in Generative Visual Feedback","display_name":"Diegetic Explanations for Uncertain Sensing: Materializing Confidence and Jitter in Generative Visual Feedback","publication_year":2026,"publication_date":"2026-04-13","ids":{"openalex":"https://openalex.org/W7153731836","doi":"https://doi.org/10.1145/3772363.3798809"},"language":null,"primary_location":{"id":"doi:10.1145/3772363.3798809","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772363.3798809","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 Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3772363.3798809","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5078204315","display_name":"Zhijun Ma","orcid":"https://orcid.org/0000-0002-8091-3760"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Zhijun Ma","raw_affiliation_strings":["Computational Media and Arts Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8091-3760","affiliations":[{"raw_affiliation_string":"Computational Media and Arts Thrust, Information Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China","institution_ids":["https://openalex.org/I37987034","https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5078204315"],"corresponding_institution_ids":["https://openalex.org/I37987034","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.81903046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11883","display_name":"Embodied and Extended Cognition","score":0.12970000505447388,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11883","display_name":"Embodied and Extended Cognition","score":0.12970000505447388,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10803","display_name":"Innovative Human-Technology Interaction","score":0.060600001364946365,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.04089999943971634,"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/jitter","display_name":"Jitter","score":0.48910000920295715},{"id":"https://openalex.org/keywords/visual-feedback","display_name":"Visual feedback","score":0.4632999897003174},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4519999921321869},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.38679999113082886},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.30399999022483826},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2994000017642975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6075000166893005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5788000226020813},{"id":"https://openalex.org/C134652429","wikidata":"https://www.wikidata.org/wiki/Q1052698","display_name":"Jitter","level":2,"score":0.48910000920295715},{"id":"https://openalex.org/C3020716817","wikidata":"https://www.wikidata.org/wiki/Q4132092","display_name":"Visual feedback","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4616999924182892},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4519999921321869},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.38679999113082886},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.33410000801086426},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.30399999022483826},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2689000070095062},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C186886427","wikidata":"https://www.wikidata.org/wiki/Q5441213","display_name":"Feedback loop","level":2,"score":0.26030001044273376},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3772363.3798809","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772363.3798809","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 Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3772363.3798809","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3772363.3798809","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 Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2017131938","https://openalex.org/W2017310186","https://openalex.org/W2082131394","https://openalex.org/W2099001635","https://openalex.org/W2163419627","https://openalex.org/W2795973510","https://openalex.org/W2999765337","https://openalex.org/W3030234902","https://openalex.org/W3119394424","https://openalex.org/W3201014845","https://openalex.org/W4225137238","https://openalex.org/W4319074048","https://openalex.org/W4388706588","https://openalex.org/W4396218845","https://openalex.org/W4396917396","https://openalex.org/W4412652612","https://openalex.org/W4416251448"],"related_works":[],"abstract_inverted_index":{"In":[0,85],"exhibition":[1],"environments,":[2],"camera-based":[3],"affect":[4,69],"sensing":[5,45,102],"is":[6],"inherently":[7],"uncertain.":[8,130],"Conventional":[9],"systems":[10,139],"communicate":[11],"uncertainty":[12,46,59],"via":[13],"explicit":[14,92],"warnings":[15],"or":[16,96],"numerical":[17],"indicators,":[18],"which":[19],"can":[20],"interrupt":[21],"experience":[22],"in":[23,137],"immersive":[24],"installations.":[25],"We":[26,57,131],"present":[27],"the":[28,48,127],"generative":[29,33],"display,":[30],"a":[31,38,67,86],"public-facing":[32],"audiovisual":[34],"system,":[35],"and":[36,62,71,105,121,146],"introduce":[37],"diegetic,":[39],"seamful":[40],"explanation":[41],"approach":[42],"that":[43,78,108],"communicates":[44],"through":[47],"artwork\u2019s":[49],"own":[50],"\"atmospheric\"":[51],"behavior":[52],"rather":[53],"than":[54],"overlay":[55],"UI.":[56],"operationalize":[58],"using":[60],"confidence":[61],"short-window":[63],"jitter":[64],"signals":[65],"from":[66],"face-derived":[68],"model":[70],"map":[72],"them":[73],"to":[74],"graded":[75],"material":[76],"dynamics":[77],"are":[79],"compatible":[80],"with":[81,144],"multiple":[82],"front-end":[83],"styles.":[84],"qualitative":[87],"study":[88],"participants":[89],"experienced":[90],"either":[91],"textual":[93],"status":[94],"prompts":[95],"diegetic":[97,109],"aesthetic":[98],"cues":[99],"under":[100],"comparable":[101,112],"conditions.":[103],"Observations":[104],"interviews":[106],"suggest":[107],"explanations":[110,141],"support":[111],"state":[113],"awareness":[114],"while":[115],"preserving":[116],"immersion,":[117],"prompting":[118],"self-initiated":[119],"adjustments":[120],"encouraging":[122],"anthropomorphic":[123],"attributions":[124],"such":[125],"as":[126],"system\u201chesitating\u201d":[128],"when":[129],"discuss":[132],"implications":[133],"for":[134],"explainable":[135],"interaction":[136],"sensing-based":[138],"where":[140],"must":[142],"coexist":[143],"aesthetics":[145],"flow.":[147]},"counts_by_year":[],"updated_date":"2026-04-14T06:02:45.956762","created_date":"2026-04-13T00:00:00"}