{"id":"https://openalex.org/W7166816700","doi":"https://doi.org/10.48550/arxiv.2606.30937","title":"No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation","display_name":"No Adaptation Without Observation: Observability-Constrained Test-Time Prompt Tuning for LiDAR Semantic Segmentation","publication_year":2026,"publication_date":"2026-06-29","ids":{"openalex":"https://openalex.org/W7166816700","doi":"https://doi.org/10.48550/arxiv.2606.30937"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.30937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30937","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.2606.30937","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109670911","display_name":"Linlian Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Linlian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048815238","display_name":"Wentao Ju","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ju, Wentao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115403757","display_name":"Sadman Rakib Pinon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pinon, Sadman Rakib","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139777938","display_name":"Jianwei Xian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xian, Jianwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064393186","display_name":"Zhixiang Chi","orcid":"https://orcid.org/0000-0003-4560-4986"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chi, Zhixiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139818482","display_name":"Xinxin Zuo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zuo, Xinxin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139765244","display_name":"Yang Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yang","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/T10036","display_name":"Advanced Neural Network Applications","score":0.5562999844551086,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5562999844551086,"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":0.1306000053882599,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.0658000037074089,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8615000247955322},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7008000016212463},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5958999991416931},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.592199981212616},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.536300003528595},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.36890000104904175},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.367900013923645},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.3646000027656555}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8615000247955322},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7820000052452087},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7008000016212463},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5958999991416931},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.592199981212616},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.536300003528595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515999972820282},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40529999136924744},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.37770000100135803},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.35040000081062317},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34369999170303345},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.32899999618530273},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3021000027656555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2784000039100647},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.2770000100135803},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.273499995470047},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.30937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30937","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.2606.30937","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.30937","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"LiDAR":[0,38,75,142],"semantic":[1,76,135],"segmentation":[2,149],"often":[3],"degrades":[4],"under":[5,48,151],"real-world":[6],"deployment":[7,152],"due":[8],"to":[9,37,94,101,113],"evolving":[10],"sensing":[11,82],"conditions,":[12],"while":[13],"collecting":[14],"new":[15],"annotations":[16],"for":[17,74],"retraining":[18],"is":[19,40,45,99],"impractical.":[20],"Test-time":[21],"adaptation":[22,146],"(TTA)":[23],"updates":[24,54,131],"model":[25],"parameters":[26,58],"online":[27,130],"using":[28],"pseudo-label":[29,43],"supervision,":[30],"but":[31],"directly":[32],"applying":[33],"standard":[34,141],"TTA":[35],"strategies":[36],"data":[39],"challenging.":[41],"Because":[42],"reliability":[44,83],"spatially":[46],"heteroscedastic":[47],"range-dependent":[49],"sparsity":[50],"and":[51,63,88,91,148],"occlusion,":[52],"uniform":[53],"on":[55,140],"globally":[56,119],"shared":[57,120],"can":[59],"inject":[60],"unstable":[61],"gradients":[62],"destabilize":[64],"adaptation.":[65],"We":[66],"propose":[67],"a":[68,107],"geometry-constrained":[69],"test-time":[70],"prompt":[71,103],"tuning":[72],"framework":[73],"segmentation.":[77],"Our":[78],"method":[79],"estimates":[80],"per-location":[81],"from":[84,117],"depth-consistent":[85],"beam":[86],"terminations":[87],"neighborhood":[89],"support,":[90],"uses":[92],"it":[93],"reweight":[95],"spatial":[96,111],"supervision.":[97],"Adaptation":[98],"confined":[100],"lightweight":[102],"adapters":[104],"inserted":[105],"into":[106],"frozen":[108],"backbone,":[109],"with":[110],"gating":[112],"prevent":[114],"unreliable":[115],"regions":[116],"perturbing":[118],"representations.":[121],"A":[122],"temporally":[123],"smoothed":[124],"prototype":[125],"alignment":[126],"strategy":[127],"further":[128],"stabilizes":[129],"by":[132],"accumulating":[133],"reliable":[134],"evidence":[136],"over":[137],"time.":[138],"Experiments":[139],"benchmarks":[143],"demonstrate":[144],"improved":[145],"stability":[147],"performance":[150],"variations":[153],"without":[154],"additional":[155],"annotations.":[156]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-02T00:00:00"}
