Latent variable conditional models, including the latent conditional random fields as a special case, are popular models for many natural language processing and vision processing tasks. The computational complexity of the exact decoding/inference in latent conditional random fields is unclear. In this paper, we try to clarify the computational complexity of the exact decoding. We analyze the complexity and demonstrate that it is an NP-hard problem even on a sequential labeling setting. Furthermore, we propose the latent-dynamic inference (LDI-Naive) method and its bounded version (LDI-Bounded), which are able to perform exact-inference or almost-exact-inference by using top-$n$ search and dynamic programming.
Cross-Session Decoding of Neural Spiking Data via Task-Conditioned Latent Alignment
Institute of Automation, Chinese Academy of Sciences（自动化研究所，中国科学院）；Departments of Ophthalmology and Bioengineering, University of Pittsburgh（眼科学与生物工程系，匹兹堡大学）；Inria, CEA, Université Paris-Saclay（法国国家科学研究中心（Inria）、法国国家科学研究中心（CEA）、巴黎萨克雷大学）
EEG-VID: Task-Guided Latent Predictive Pretraining for EEG Decoding and Assistive Target Selection
School of Information and Control Engineering, China University of Mining and Technology（中国矿业大学信息与控制工程学院）；School of Automation and Intelligent Sensing, Shanghai Jiao Tong University（上海交通大学自动化与智能感知学院）；Shanghai Innovation Institute（上海创新研究院）
Generative Sentiment Analysis via Latent Category Distribution and Constrained Decoding
School of Cyber Science and Engineering, Wuhan University（武汉大学网络科学与工程学院）；Beijing Rigour Technology Co., Ltd.（北京睿格科技有限公司）；School of Cyberspace, Hangzhou Dianzi University（杭州电子科技大学网络空间学院）；North China Power Engineering Co., Ltd. of China Power Engineering Consulting Group（中国电力工程顾问集团华北电力工程有限公司）
Delta-JEPA: Learning Action-Sensitive World Models via Latent Difference Decoding
School of Computer Science and Technology, University of Chinese Academy of Sciences（中国科学院大学计算机科学与技术学院）；Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Computer Science and Technology, Harbin Institute of Technology, Weihai（哈尔滨工业大学（威海）计算机科学与技术学院）；Faculty of Computing, Harbin Institute of Technology, Harbin（哈尔滨工业大学计算学部）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）
Anomaly detection in time-series via inductive biases in the latent space of conditional normalizing flows
Department of Computer Science Norwegian University of Science and Technology（挪威科学技术大学计算机科学系）；BCAM – Basque Center for Applied Mathematics University of Coimbra, CISUC/LASI, DEI（巴斯克应用数学中心，科英布拉大学，CISUC/LASI，DEI）；IKERBASQUE — Basque Foundation for Science（巴斯克科学基金会）
Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics
Computer Systems Engineering Dpt., Universidad Politécnica de Madrid, Madrid (Spain)（马德里理工大学计算机系统工程系）；Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul (Korea)（首尔科学技术大学计算机科学与工程系）
本研究评估了时间序列基础模型 MOMENT 在可视化分析任务中潜在空间的解释性，发现微调虽降低了损失但嵌入空间可解释性改善有限，指出基础模型仍需方法改进但显著提升了交互分析效率。
Seeing the imagined: latent functional alignment in visual imagery decoding from fMRI data
Department of Biomedicine and Prevention, University of Rome Tor Vergata（罗马特拉维拉大学生物医学与预防系）；Tether Evo；A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital（马萨诸塞总医院生物医学成像中心）
Empowering LLMs for Structure-Based Drug Design via Exploration-Augmented Latent Inference
College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University（教育部符号计算与知识工程重点实验室）；Department of Computer Science, Aalto University（艾尔沃斯大学计算机科学系）；College of Artificial Intelligence, Jilin University（吉林大学人工智能学院）
Discovering Latent Graphs with GFlowNets for Diverse Conditional Image Generation
Dept. of Computer Science, Stanford University（计算机科学系，斯坦福大学）；Dept. of Psychiatry and Behavioral Sciences, Stanford University（精神病学与行为科学系，斯坦福大学）；Dept. of Biomedical Data Science, Stanford University（生物医学数据科学系，斯坦福大学）；Center for Intelligent Machines, McGill University（智能机器中心，麦吉尔大学）；MILA - Quebec AI institute（魁北克人工智能研究所）
