Behavioral Foundation Models

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13 papers5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Action-Aligned Latent Planning for Versatile Humanoid Loco-Manipulation
Oct 17, 2026Yutang Lin, Guanya Shi, C. Karen LiuHumanoid Loco-Manipulation Latent-Space Planning
Amazon FAR. · Carnegie Mellon University. · Stanford University.
P-BFM: Perceptive Behavioral Foundation Models for Humanoid Control via Unsupervised Reinforcement Learning
Oct 11, 2026Xue Wang, Yitang Li, Yiming Zhang +7Unsupervised RL Behavioral Foundation Models
University of Shanghai for Science and Technology · RoboPartyLab · Tsinghua University +2
Benchmarking Behavioral Steerability in Behavior Foundation Models
Oct 7, 2026Minghe Gao, Zhanxi Yan, Jiahui Liu +9Behavioral Foundation Models Human Motion Generation
ZJU · Unitree · NUS +2
Task Inference Beyond Least Squares in Behavioral Foundation Models
Oct 4, 2026Kuan-Hsun Tu, Chien-Sheng Chiang, Hsin-Wei Chen +2Reinforcement Learning Multi-Task RL
National Taiwan University
Behavioral Foundation Models for Quality Diversity
Sep 28, 2026Nazim Bendib, Nicolas Perrin-Gilbert, Olivier SigaudReinforcement Learning Quality-Diversity Optimization
Sorbonne Université, ISIR Paris, France
Sparks of In Silico Cognitive Science: Theories from Simulated Data Can Generalize to Humans
Sep 7, 2026Akshay K. Jagadish, Younes Strittmatter, Nori Jacoby +4Computational Cognitive Modeling Human Behavior Simulation
Princeton University · Cornell University · Helmholtz Munich
Small Foundation Models of Human Cognition and Behaviour
Aug 5, 2026Nick Oh, Fernand GobetComputational Cognitive Modeling Human Behavior Modeling
socius labs · London School of Economics and Political Science
Exploration and Online Transfer with Behavioral Foundation Models
Jun 29, 2026Louis Bagot, Mathieu Lefort, Laëtitia MatignonReinforcement Learning RL Exploration
SyCoSMA · Université Lyon 1, CNRS, INSA Lyon LIRIS - UMR5205, 69622 Villeurbanne, France · LIRIS, SyCoSMA, IRISA, MALT, UR +1
BFMTrack: Latent Sequence Optimization for Physics-Based Motion Tracking with Behavioral Foundation Models
Jun 23, 2026Thomas Rupf, Agon Serifi, David Müller +4Humanoid Robot Control Behavioral Foundation Models
Disney Research, Zurich, Switzerland
BehaviorBench: Benchmarking Foundation Models for Behavioral Science Tasks
Jun 23, 2026Jin Huang, Yutong Xie, Wanli Song +5Benchmark Design Human Behavior Simulation
University of Michigan · MobLab · Stanford University +1
Scaling Laws for Behavioral Foundation Models over User Event Sequences
Jun 3, 2026Rickard Brüel GabrielssonNext-Event Prediction Behavioral Foundation Models
Unbox AI
Plan, Don't Pose: Long Composite Motion Generation with Text-Aligned BFM
May 28, 2026Nikolay Shvetsov, Maksim Bobrin, Nazar Buzun +2Text-to-Motion Generation Human Motion Generation
AvaCapo, Potsdam, Germany · Potsdam University, Potsdam, Germany · Applied AI Institute, Computational Imaging Lab, Moscow, Russia +2
Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
Mar 16, 2026Pranaya Jajoo, Harshit Sikchi, Siddhant Agarwal +3Behavioral Foundation Models Zero-Shot RL
Department of Computing Science, University of Alberta, Canada · Alberta Machine Intelligence Institute (Amii) · The University of Texas at Austin +2
Decoding the Human Factor: High Fidelity Behavioral Prediction for Strategic Foresight
Feb 19, 2026Ben Yellin, Ehud Ezra, Mark Foreman +1Behavioral Foundation Models Human Behavior Simulation
OMGene AI Lab
BFM-Zero: A Promptable Behavioral Foundation Model for Humanoid Control Using Unsupervised Reinforcement Learning
Nov 6, 2025Yitang Li, Zhengyi Luo, Tonghe Zhang +10Humanoid Robot Control Behavioral Foundation Models

Oct 17, 2026J/K move · Enter open · S save

Action-Aligned Latent Planning for Versatile Humanoid Loco-Manipulation

Yutang Lin, Guanya Shi, C. Karen Liu

Amazon FAR. · Carnegie Mellon University. · Stanford University.

Humanoid Loco-Manipulation Latent-Space Planning Robot Skill Learning Behavioral Foundation Models

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Learning a single perceptive policy for diverse humanoid loco-manipulation requires unifying high-level task decisions without losing the state-dependent physical responses that make each interaction succeed. This makes the representation between high-level planning and whole-body control critical: kinematic or contact targets provide compact abstractions but do not directly encode interaction-specific control responses, while directly predicting low-level actions requires the planner to model high-frequency closed-loop feedback. We propose FIBER, a framework that uses the executable latent space of a frozen behavioral foundation model (BFM) as a shared planning representation for heterogeneous interaction skills. Our latent policy projection (LPP) maps independently acquired task-specific policies into this representation by identifying latent commands whose induced actions match their local control responses, enabling lower-rate planning while retaining the BFM's high-frequency state feedback. After projection, we aggregate closed-loop latent rollouts from all skills and train a single perceptive flow planner entirely offline. We further introduce AH-BFM, an adaptive-horizon BFM trained with multi-gamma forward-backward (FB) learning to support both precise control and temporally extended whole-body behavior. We evaluate FIBER on box pickup, door opening, and object grasping in simulation and on a real Unitree G1 humanoid. Across 128 diverse variations per task in simulation, FIBER achieves 42.0% mean success, more than tripling projected latent replay (11.6%) and substantially outperforming kinematic planning (3.5%). Real-world experiments further demonstrate sim-to-real transfer, skill chaining, and conditional steering through the same unified planner.