Latent Action Learning

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

Jul 13Week of Sep 28

Latest papers 74

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Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control
May 14, 2026Haozhe Jia, Honglei Jin, Yuan Zhang +9Robotic Control Latent Action Learning
The Hong Kong University of Science and Technology (Guangzhou). · LimX Dynamics Technology Co., Ltd. · Shandong University. +3
Dynamic Latent Routing
May 14, 2026Fangyuan Yu, Xin Su, Amir AbdullahLatent Action Learning RL Post-Training
Thoughtworks AI Labs (TAILS)
SCAR: Self-Supervised Continuous Action Representation Learning
May 13, 2026Hongjia Liu, Fan Feng, Minghao Fu +3Latent Action Learning Representation Learning
University of California, San Diego · KTH Royal Institute of Technology
RotVLA: Rotational Latent Action for Vision-Language-Action Model
May 13, 2026Qiwei Li, Xicheng Gong, Xinghang Li +5Latent Action Learning Vision-Language-Action Models
Wangxuan Institute of Computer Technology, Peking University · Xiaomi Robotics · CASIA
Why Latent Actions Fail, and How to Prevent It
May 13, 2026Jung Min Lee, Taehyun Cho, Li Zhao +1Latent Action Learning Disentangled Representation Learning
Seoul National University · Microsoft Research
From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation
May 12, 2026Yajie Li, Bozhou Zhang, Chun Gu +5Latent Action Learning Long-Horizon Robotic Manipulation
School of Data Science, Fudan University · Shanghai Innovation Institute · Imperial College London +1
ALAM: Algebraically Consistent Latent Action Model for Vision-Language-Action Models
May 11, 2026Zuojin Tang, Haoyun Liu, Xinyuan Chang +11Latent Action Learning Vision-Language-Action Models
Zhejiang University · Amap, Alibaba Group · Nanjing University +5
Learning Visual Feature-Based World Models via Residual Latent Action
May 8, 2026Xinyu Zhang, Zhengtong Xu, Yutian Tao +3Latent Action Learning World Model Learning
Rutgers University · Purdue University · University of Wisconsin-Madison
From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models
May 6, 2026Yihan Lin, Haoyang Li, Yang Li +4Latent Action Learning Vision-Language-Action Models
School of Information, Renmin University of China, Beijing, China · Key Laboratory of Data Engineering and Knowledge Engineering, Beijing, China · Engineering Research Center of Database and Business Intelligence, Beijing, China
Action Motifs: Self-Supervised Hierarchical Representation of Human Body Movements
Apr 30, 2026Genki Kinoshita, Shu Nakamura, Ryo Kawahara +3Latent Action Learning Representation Learning
1Kyoto University · 2Kyoto Institute of Technology · 3RIKEN
UniT: Toward a Unified Physical Language for Human-to-Humanoid Policy Learning and World Modeling
Apr 21, 2026Boyu Chen, Yi Chen, Lu Qiu +3Latent Action Learning Humanoid Robot Control
1XPENG Robotics · 2Tsinghua University · 3The University of Hong Kong
Latent Policy Steering through One-Step Flow Policies
Mar 5, 2026Hokyun Im, Andrey Kolobov, Jianlong Fu +1RL for Robotics Latent Action Learning
Department of Artificial Intelligence, Yonsei University · Microsoft Research
On the Sample Efficiency of Inverse Dynamics Models for Semi-Supervised Imitation Learning
Feb 2, 2026Sacha Morin, Moonsub Byeon, Alexia Jolicoeur-Martineau +1Latent Action Learning Imitation Learning
Département d’informatique et de recherche opérationnelle, Université de Montréal · Mila – Quebec AI Institute · Samsung AI Lab, Montreal +1
CoLA-Flow Policy: Temporally Coherent Imitation Learning via Continuous Latent Action Flow Matching for Robotic Manipulation
Jan 30, 2026Wu Songwei, Jiang Zhiduo, Sun Wandong +4Flow Matching Latent Action Learning
Harbin Institute of Technology, Harbin 150001, China · Honor Device Co., Ltd., Shenzhen, China
Wavelet Policy: Imitation Learning in the Scale Domain with World Prior Memory
Apr 7, 2025Changchuan Yang, Haoxuan Xu, Yuhang Dong +3Latent Action Learning Visuomotor Policy Learning
Zhejiang University · The Hong Kong University of Science and Technology · Tsinghua University, DISCOVER Robotics

May 14, 2026, cs.ROJ/K move · Enter open · S save

Before the Body Moves: Learning Anticipatory Joint Intent for Language-Conditioned Humanoid Control

Haozhe Jia, Honglei Jin, Yuan Zhang, Youcheng Fan+8

The Hong Kong University of Science and Technology (Guangzhou). · LimX Dynamics Technology Co., Ltd. · Shandong University.+3

Robotic Control Latent Action Learning Diffusion Policy AI Control Robot Motion Generation Language-Conditioned Robot Control

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Natural language is an intuitive interface for humanoid robots, yet streaming whole-body control requires control representations that are executable now and anticipatory of future physical transitions. Existing language-conditioned humanoid systems typically generate kinematic references that a low-level tracker must repair reactively, or use latent/action policies whose outputs do not explicitly encode upcoming contact changes, support transfers, and balance preparation. We propose \textbf{DAJI} (\emph{Dynamics-Aligned Joint Intent}), a hierarchical framework that learns an anticipatory joint-intent interface between language generation and closed-loop control. DAJI-Act distills a future-aware teacher into a deployable diffusion action policy through student-driven rollouts, while DAJI-Flow autoregressively generates future intent chunks from language and intent history. Experiments show that DAJI achieves strong results in anticipatory latent learning, single-instruction generation, and streaming instruction following, reaching 94.42% rollout success on HumanML3D-style generation and 0.152 subsequence FID on BABEL.

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