{"id":"https://openalex.org/W7164205403","doi":"https://doi.org/10.48550/arxiv.2606.09936","title":"One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability","display_name":"One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability","publication_year":2026,"publication_date":"2026-06-07","ids":{"openalex":"https://openalex.org/W7164205403","doi":"https://doi.org/10.48550/arxiv.2606.09936"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.09936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09936","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.2606.09936","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094201981","display_name":"Bhavith Chandra Challagundla","orcid":"https://orcid.org/0009-0002-7103-8009"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Challagundla, Bhavith Chandra","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016193722","display_name":"Shaily Pandey","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pandey, Sanskar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100016488","display_name":"Param Thakkar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thakkar, Param","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138032346","display_name":"Rishikesh Mallagundla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mallagundla, Rishikesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138019181","display_name":"Yugandhar Reddy Gogireddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gogireddy, Yugandhar Reddy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138315429","display_name":"Wenhao Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Wenhao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130243221","display_name":"Hindol Roy Choudhury","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Choudhury, Hindol Roy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095856724","display_name":"Shravani Challagundla","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Challagundla, Shravani","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129362391","display_name":"Mohamed Deraz Nasr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nasr, Mohamed Deraz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138053747","display_name":"Spursh Deshpande","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deshpande, Spursh","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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7608000040054321,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.7608000040054321,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.10429999977350235,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.02500000037252903,"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/interpretability","display_name":"Interpretability","score":0.9261999726295471},{"id":"https://openalex.org/keywords/surprise","display_name":"Surprise","score":0.42590001225471497},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.415800005197525},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.35370001196861267},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.3325999975204468},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.3257000148296356},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3240000009536743},{"id":"https://openalex.org/keywords/computational-model","display_name":"Computational model","score":0.3151000142097473}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9261999726295471},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7594000101089478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5814999938011169},{"id":"https://openalex.org/C2780343955","wikidata":"https://www.wikidata.org/wiki/Q333173","display_name":"Surprise","level":2,"score":0.42590001225471497},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38530001044273376},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35740000009536743},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3497999906539917},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3325999975204468},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.3257000148296356},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3151000142097473},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3140999972820282},{"id":"https://openalex.org/C2781235140","wikidata":"https://www.wikidata.org/wiki/Q275131","display_name":"Scratch","level":2,"score":0.30640000104904175},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.27869999408721924},{"id":"https://openalex.org/C162838799","wikidata":"https://www.wikidata.org/wiki/Q596077","display_name":"Counterexample","level":2,"score":0.2632000148296356},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C2777586403","wikidata":"https://www.wikidata.org/wiki/Q4243098","display_name":"Hook","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2529999911785126},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.09936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09936","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.2606.09936","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.09936","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"World":[0],"models":[1,13,27,129,183],"are":[2,84,184],"now":[3],"built":[4],"on":[5],"substantially":[6],"different":[7],"computational":[8],"substrates.":[9],"Latent":[10],"recurrent":[11,24],"state-space":[12],"such":[14,28,47],"as":[15,29,48],"PlaNet":[16],"and":[17,37,43,73,122,160,180,194,202],"the":[18,116,120,124,189],"Dreamer":[19],"family":[20],"compress":[21],"observations":[22,32],"into":[23,33],"states;":[25],"token-based":[26],"IRIS":[30],"quantize":[31],"a":[34,41,52,77,96,133,146,162],"learned":[35,53],"codebook":[36],"predict":[38,50],"autoregressively":[39],"with":[40,56,100],"transformer;":[42],"joint-embedding":[44],"predictive":[45],"architectures":[46],"I-JEPA":[49],"in":[51],"latent":[54],"space":[55],"no":[57,101],"pixel":[58],"decoder.":[59],"The":[60],"interpretability":[61,142],"methods":[62,154],"applied":[63],"to":[64,211],"these":[65],"models,":[66,121],"including":[67],"probing,":[68],"activation":[69],"patching,":[70],"sparse":[71],"autoencoders,":[72],"surprise":[74],"analysis,":[75],"share":[76],"common":[78],"set":[79,163],"of":[80,103,127,164],"primitives,":[81],"yet":[82],"they":[83],"re-implemented":[85],"from":[86],"scratch":[87],"for":[88],"each":[89,209],"architecture":[90],"because":[91],"existing":[92],"hook-and-cache":[93],"tooling":[94,117],"assumes":[95],"transformer":[97],"language":[98],"model":[99,150],"notion":[102],"actions,":[104],"environment":[105],"steps,":[106],"or":[107],"imagined":[108],"rollouts.":[109],"We":[110,137],"argue":[111],"that":[112,123,178],"this":[113,206],"fragmentation":[114],"reflects":[115],"rather":[118],"than":[119],"shared":[125],"structure":[126],"world":[128,182],"is":[130],"captured":[131],"by":[132],"small":[134],"typed":[135],"interface.":[136],"present":[138],"WorldModelLens,":[139],"an":[140,173],"open-source":[141],"substrate":[143],"organized":[144],"around":[145],"capability-typed":[147],"adapter:":[148],"every":[149],"implements":[151],"four":[152],"required":[153],"(encode,":[155],"transition,":[156],"initial":[157],"state,":[158],"sample)":[159],"declares":[161],"optional":[165],"heads":[166],"(decode,":[167],"reward,":[168],"continue,":[169],"actor,":[170],"critic)":[171],"through":[172],"explicit":[174],"capability":[175],"descriptor,":[176],"so":[177],"reinforcement-learning":[179],"self-supervised":[181],"first-class":[185],"without":[186],"either":[187],"imitating":[188],"other.":[190],"A":[191],"single":[192],"hook":[193],"cache":[195],"layer":[196],"exposes":[197],"time-indexed":[198],"activations,":[199],"imagination":[200],"rollouts,":[201],"intervention":[203],"replay":[204],"over":[205],"interface,":[207],"allowing":[208],"analysis":[210],"be":[212],"written":[213],"once.":[214]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-11T00:00:00"}
