Low-Latency Latent Planning

Follow this topic Ask about this topic

Momentum

6 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

Jul 6Week of Sep 21

Latest papers 39

All topics

CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization
Sep 30, 2026Morgan Byrd, Robert Wright, Sehoon HaLatent World Models Controllability
Georgia Institute of Technology, Atlanta, GA, 30308, USA · Georgia Tech Research Institute, Atlanta, GA, 30308, USA
Anisotropic Representations Improve Planning in JEPA World Models
Sep 29, 2026Mingu Kang, Yoori Oh, Sookyung Kim +1Latent World Models Low-Latency Latent Planning
Seoul National University · Ewha Womans University
DSWM: Decomposed Spatio-Temporal World Model for Demand-Driven UAV Base Station Repositioning
Sep 29, 2026Shengjie Zhong, Zhongliang Zhao, Jingxuan Chen +4Unmanned Aerial Vehicles Low-Latency Latent Planning
School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
Control-Geometry Straightening for Sampling-Based Latent Planning
Sep 28, 2026Ziang Fu, Ning NingLow-Latency Latent Planning Latent World Models
Texas A&M University
LRC-JEPA: Disentangling Dynamics and Residual Context for Efficient World Models
Sep 28, 2026Luzhe Huang, Lei Chu, Jingyi Liang +1Latent World Models Low-Latency Latent Planning
Independent researcher
Beyond One-Step Accuracy: State-Affine Latent Transition for Reliable Visual Planning
Sep 27, 2026Boyuan Zhang, Yingjun Du, Xiantong Zhen +1Low-Latency Latent Planning Latent World Models
UCAS-Terminus AI Lab, School of Engineering Science, University of Chinese Academy of Sciences · VIS Lab, University of Amsterdam · Central Research Institute, United Imaging Healthcare, Co., Ltd.
Spatial-Semantic Uncertainty in VLM-Based Target Search: Balancing Exploration and Identification
Sep 17, 2026Alkesh K. Srivastava, Jonathan Diller, Vijay Kumar +1Vision-Language Navigation Low-Latency Latent Planning
Temple University, Philadelphia, PA, 19122 USA · University of Pennsylvania, Philadelphia, PA, 19104 USA
RAF-VLA: Representation Alignment with the Future for End-to-End Autonomous Driving
Sep 15, 2026Dogun Kim, Yongjae Lee, Joonhee Lim +4Autonomous Driving Low-Latency Latent Planning
Graduate School of Mobility, Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Korea · Robotics Program, Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Korea
Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving
Sep 3, 2026Ruoyu Yao, Yusen Xie, Qingzhao Liu +5Autonomous Driving Low-Latency Latent Planning
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, China · Central Media Technology Institute, Huawei
Latent Energy Action Planning with World Models
Sep 3, 2026Phu Pham, Aniket BeraLatent World Models Low-Latency Latent Planning
Department of Computer Science, Purdue University, USA
Reinforcement Learning Enhanced LLM Agents for Complex Vehicle Routing Problems
Sep 1, 2026Yi Chen, Zikang Yu, Jiahai Wang +3Vehicle Routing Problem Solvers
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China · Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore
Hydra: A Navigation World Action Model with Discrete Latent Planning and Continuous Flow-Matching Execution
Aug 29, 2026Mohammad Nazeri, Alexandyr Card, Samira Huber +6Low-Latency Latent Planning Efficient World-Action Model
George Mason University · Kiel University · Ludwig Maximilian University Munich +1
Search-Aided Joint Agent-Environment Reinforcement Learning for Robust Lifelong Multi-Agent Path Finding with Rotations
Aug 6, 2026He Jiang, Jingtian Yan, Yulun Zhang +5Multi-Agent Path Finding Low-Latency Latent Planning
1Carnegie Mellon University · University of Southern California · 3National University of Singapore
PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning
Aug 2, 2026Volodymyr Havrylov, Faris Janjoš, Andreas Look +2Autonomous Driving Low-Latency Latent Planning
University of Tübingen · Bosch Center for Artificial Intelligence · Coburg University +1
Temporal-Distance JEPA: Plan-Aware Representation Learning for Latent World Model Predictive Control
Jul 28, 2026Jiaxin Bai, Jiaxuan XiongLow-Latency Latent Planning Video Joint Embedding Predictive Architecture
Hong Kong Baptist University Hong Kong, China
Memory for Attention: Language-Conditioned Re-Perception with a Vision--Language--Motion Map
Jul 26, 2026Dibyendu GhoshVision-Language Navigation Spatial Memory
Dibyendu Ghosh
Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models
Jul 26, 2026Liangyu Li, Qingwen Liu, Mingqing Liu +1Low-Latency Latent Planning Latent World Models
Tongji University
Koopman Dreamer: Spectrally Constrained Latent Dynamics for Stable World-Model Imagination
Jul 22, 2026Jiaqi Li, Xinglong Zhang, Haibin Xie +3Latent Dynamics Dream
College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China
Minimum Time Dubins Airplane Paths with Asymmetric Climb Rates
Jul 17, 2026Jaeyoung Lim, Giuseppe LoiannoPath Planning Low-Latency Latent Planning
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
LIDAR-AD: A Decoder-Free Latent-Interaction Dreamer with Action-Residual Chains for Autonomous Driving
Jul 12, 2026Yongzhi Liu, Yang Xiao, Zhong Cao +5Autonomous Driving Low-Latency Latent Planning
School of Mechanical Engineering, Southeast University, Nanjing, Jiangsu 211189, China · Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI 48109, USA · Xheart Technology Co., Ltd., Suzhou, Jiangsu 215100, China
Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control
Jul 6, 2026Ruslan Rakhimov, George Bredis, Yuriy Maksyuta +1Joint-Embedding Predictive Architectures Latent World Models
T-Tech
AnchorVLA: Bridging Discrete Decisions and Continuous Trajectories for Vision-Language-Action Planning
Jul 3, 2026Qi Liu, Yabei Li, Hongsong Wang +2Vision-Language-Action Framework Low-Latency Latent Planning
School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, Tsinghua University, Beijing 100084, China · School of Computer Science and Engineering, Southeast University, Nanjing 210096, China +2
Valdi: Value Diffusion World Models
Jul 1, 2026Christopher Lindenberg, Kashyap ChittaLatent World Models Model Predictive Control
University of Tübingen, Germany · 2KE:SAI – Kyutai ELLIS Scalable Autonomous Intelligence, Germany
LeCropFollow: Latent Space Planning for Navigation in Unstructured Crop Fields
Jun 30, 2026Felipe Tommaselli, Francisco Affonso, Arthur Pompeu +4Agricultural Robotics Low-Latency Latent Planning
Mobile Robotics Group, Center for Robotics (CRob), São Carlos School of Engineering (EESC), University of São Paulo, São Carlos, SP, Brazil · DASLab, Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA
Motion Planning in Compressed Representation Spaces
Jun 29, 2026Lukas Lao Beyer, Sertac KaramanLow-Latency Latent Planning Motion Planning
MIT LIDS.
J-LAW: Joint Localization and Action-Conditioned World Modeling via Coupled Latent Factor Graphs
Jun 27, 2026Guanqun Cao, Liang ChenLatent World Models Low-Latency Latent Planning
Geely Technology Europe, Pumpgatan 1, 417 55 Gothenburg Sweden · State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, China
Slow Brain, Fast Planner: Latency-Resilient VLM-Augmented Urban Navigation
Jun 18, 2026Zhenghao "Mark'' Peng, Honglin He, Quanyi Li +2Low-Latency Latent Planning Classical Planning
Amazon FAR · UCLA · Independent +1
Pixels to Proofs: Probabilistically-Safe Latent World Model Control via Parallel Conformal Robust MPC
Jun 14, 2026Devesh Nath, Anutam Srinivasan, Haoran Yin +3Low-Latency Latent Planning Model Predictive Control
Georgia Institute of Technology
FF-JEPA: Long-Horizon Planning in World Models with Latent Planners
Jun 8, 2026Sergi Masip, Jonathan Swinnen, Yutong Hu +2Long-Horizon Planning Low-Latency Latent Planning
PSI, ESAT, KU Leuven · RAM, MECH, KU Leuven
PLAN-S: Bridging Planning with Latent Style Dynamics for Autonomous Driving World Models
Jun 4, 2026Xiaoyun Qiu, Jingtao He, Yijie Chen +4Low-Latency Latent Planning Autonomous Driving
Intelligent Transportation Thrust, Systems Hub, and Center of Seamless Connectivity & Connected Intelligence, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, China.
When Does LeJEPA Learn a World Model?
May 25, 2026David Klindt, Yann LeCun, Randall BalestrieroLatent World Models Low-Latency Latent Planning
Cold Spring Harbor Laboratory · New York University · Brown University
Semantic-Aware Guided Drone Exploration for Language-Conditioned 3D Indoor Mapping
May 22, 2026Nitin Vegesna, Avideh Zakhor3D Mapping Low-Latency Latent Planning
Department of Electrical Engineering and Computer Sciences University of California, Berkeley Berkeley, CA, USA
Verified Task-Space Motion Planning Under Joint-Space Constraints
May 21, 2026Hanjiang Hu, Changliu Liu, Yebin WangMotion Planning Low-Latency Latent Planning
Robotics Institute, Carnegie Mellon University · Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA 02139, USA
Bernini: Latent Semantic Planning for Video Diffusion
May 21, 2026Bernini Team, Chenchen Liu, Junyi Chen +9Video Multimodal Large Language Models Video Generation
Bernini Team, Bytedance · Bytedance
World Model Control by Trajectory Reachability Metrics
May 21, 2026Liangyu Li, Shengzhi Wang, Libin Qiu +2Latent World Models Low-Latency Latent Planning
Tongji University
Learning Multi-Timescale Abstractions for Hierarchical Combinatorial Planning
May 16, 2026Vivienne Huiling Wang, Tinghuai Wang, Joni PajarinenHierarchical Reinforcement Learning Low-Latency Latent Planning
Department of Electrical Engineering and Automation, Aalto University, Finland · Qutwo, Finland
Dream-MPC: Gradient-Based Model Predictive Control with Latent Imagination
May 6, 2026Jonathan Spieler, Sven BehnkeModel Predictive Control Model-Based Reinforcement Learning
Autonomous Intelligent Systems, Computer Science Institute VI - Intelligent Systems and Robotics, Center for Robotics and the Lamarr Institute for Machine Learning and Artificial Intelligence, University of Bonn, Germany.
SAGA: A Robust Self-Attention and Goal-Aware Anchor-based Planner for Safe UAV Autonomous Navigation
May 4, 2026Junhao Wei, Yanxiao Li, Dexing Yao +9Unmanned Aerial Vehicles Autonomous Navigation
Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China · Pazhou Lab (Huangpu), Guangzhou 510555, China · College of Animal Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China +3
Multi-Robot Motions in Milliseconds: Vector-Accelerated Primitives for Sampling-Based Planning
Apr 27, 2026James D. Motes, Marco Morales, Nancy M. AmatoMulti-Robot Motion Planning Motion Planning
Parasol Lab, School of Computing and Data Science, University of Illinois at Urbana Champaign, Champaign, IL, 61820 USA · Department of Computer Science at Instituto Tecnológico Autónomo de México (ITAM), Mexico City, México

Sep 30, 2026, cs.ROJ/K move · Enter open · S save

CF-JEPA: Improving Robustness of JEPA World Models via Controllability Factorization

Morgan Byrd, Robert Wright, Sehoon Ha

Georgia Institute of Technology, Atlanta, GA, 30308, USA · Georgia Tech Research Institute, Atlanta, GA, 30308, USA

Latent World Models Controllability World Models Low-Latency Latent Planning Distractor

Open paper AskPDF arXiv

Controlling an agent with vision requires being able to separate useful information from irrelevant background information. JEPA-style latent world models seem like a natural approach for this, as they do not perform pixel-level reconstruction; however, they are still sensitive to these distractor signals and experience latent collapse. In this work, we introduce Controllability Factorized JEPA (CF-JEPA), a JEPA-style world model which splits the latent space into controllable and uncontrollable subspaces. This factorization allows us to capture all the distractor information into the uncontrollable region, while we use the control-relevant latent information for our task. With this, we show comparable performance across 2D and 3D control tasks under nominal conditions and improved performance under distracted conditions, where CF-JEPA is the only model that does not experience latent collapse. We also validate our model under distracted conditions for a simulated robot task, highlighting the practical application of such a scheme.

Momentum

Related topics

Latest papers 39