{"paper":{"title":"The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chen Gao, Chenglin Wu, Chengming Xu, Cheng Tan, Cheng Yang, Guanting Dong, Guibin Zhang, Haojie Huang, Huacan Wang, Jiale Tao, Jiangning Zhang, Jiayi Zhang, Jie Xu, Kaituo Feng, Kelu Yao, Kun Wang, Ronghao Chen, Ruqi Huang, Shuicheng Yan, Siyuan Ma, Tao Jin, Tianyu Fu, Wenqi Ren, Xiangyu Yue, Xiaobin Hu, Xiaogang Xu, Xinlei Yu, Yanwei Fu, Yongbo He, Yong Liu, Youxing Li, Yue Liao, Yue Ma, Yu-Gang Jiang, Yu Wang, Zhangquan Chen, Zhe Cao, Zhucun Xue, Zikun Su","submitted_at":"2026-04-02T13:36:37Z","abstract_excerpt":"Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an increasing body of work shows that many critical internal processes are more naturally carried out in continuous latent space than in human-readable verbal traces. This shift is driven by the structural limitations of explicit-space computation, including linguistic redundancy, discretization bottlenecks, sequential inefficiency, and semantic loss. This survey aims to provide a unified and up-to-date landscape of latent"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.02029","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2604.02029/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}