{"id":"W4417142339","doi":"10.48550/arxiv.2512.05343","title":"SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling","year":2025,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"3D Shape Modeling and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Nvidia; National Science Foundation","keywords":"Generative grammar; Object (grammar); Interface (matter); Key (lock); Range (aeronautics); Geometric primitive; User interface; Geometric modeling; Fidelity","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001828713,0.001381026,0.0007334932,0.0008489803,0.0005042576,0.002390103,0.003686049,0.001448927,0.01824168],"category_scores_gemma":[0.007904472,0.0008836557,0.001463288,0.0005397494,0.002117556,0.002182455,0.005243725,0.002065345,0.004637116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007048482,"about_ca_system_score_gemma":0.0007361255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001929136,"about_ca_topic_score_gemma":0.002789238,"domain_scores_codex":[0.998861,0.0002817734,0.00006006866,0.0002190657,0.0005079256,0.00007021378],"domain_scores_gemma":[0.9969165,0.001521901,0.0001317275,0.0009991126,0.0002698655,0.000160914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006692337,0.0002959997,0.003196476,0.0006596881,0.0001716567,0.0007481122,0.001497791,0.3586508,0.05206487,0.1130683,0.03291807,0.4360591],"study_design_scores_gemma":[0.00008084931,0.00007776544,0.0002109632,0.00004585086,0.00001687752,0.0001987005,0.00007299384,0.9157952,0.01951007,0.03291893,0.03102271,0.00004917002],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003058481,0.00009124031,0.9766252,0.00007054405,0.00005106587,0.0000552572,0.0001425056,0.01739881,0.002506913],"genre_scores_gemma":[0.2277565,0.000270133,0.7471943,0.000349989,0.00007445316,0.0004087338,0.001184804,0.01647477,0.006286343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01824168,"threshold_uncertainty_score":0.06102449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02568873452817434,"score_gpt":0.1659235039447409,"score_spread":0.1402347694165666,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}