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Calibration-risk routing for controlled world-model adaptation

MC-WM partitions target data to select lower-calibration-risk world models and weights imagined policy updates via learned confidence, evaluated across 541 MuJoCo shift executions.

Yifan F. Zhang, Liang Zheng

Published Oct 1, 2026 · 0 citations

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7/20 AI panelreviewers recommend it

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lenient 3/5

medium 3/10

strict 1/5

45%Niche pick

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NeurIPS 2026Aalto Model-based RL

Revisiting Value Iteration: Unified Analysis of Discounted and Average-Reward Cases

Arsenii Mustafin, Xinyi Sheng, Dominik Baumann

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026Zhejiang Southeast Binjiang Insititute U Hong Kong Model-based RL

AdaWM: Few-Shot Adaptation of World Models to Unseen Dynamical Regimes

Zian Guan, Guozheng Li, Zilun Zhang, Zecong Tang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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1/20 AI panelreviewers recommend it

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lenient 1/5

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NeurIPS 2026Proxima Technology / Kyoto Kyoto Model-based RL

Objective-Aligned Amortized Inference for Offline Bayes-Adaptive MDP Model Learning

Toru Hishinuma, Kei Senda

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Tsinghua national university of singaore,U Science and Technology Beijing Model-based RL

Amortizing Generative Guidance for Model-Based Reinforcement Learning

Xiangteng Zhang, Guojian Zhan, Likun Wang, Jingliang Duan and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Technische Universität Hamburg Hamburg University of Technology Model-based RL

When Actions Matter: Causal Affordances for Long-Horizon Credit Assignment in World Models

Pradeep Kumar Banerjee, Frank Röder, Nihat Ay

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Northeastern U California, San Diego U Maryland, College Park UC San Diego Model-based RL

Generalizing Action-Conditioned Latent World Models with Video Model Rewards

Haichao Zhang, Yijiang Li, Shwai He, Van T Le and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Universitat Pompeu Fabra Model-based RL

Control Under the Wrong Model Is Better Than Under the Correct One

Francesco Damiani, Ruben Moreno Bote

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026INRIA Inria Inria Grenoble - Rhône-Alpes CNRS Model-based RL

BlockFormer: Transformer-based inference from interaction maps

Eloïse Touron, Pedro Rodrigues, Julyan Arbel, Nelle Varoquaux and 1 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026nudt.edu.cn National University of Defense T Tsinghua Independent Researcher Department of Automation, Tsingh Model-based RL

Bridging Risk Approximation Gaps in Model Predictive Task Sampling via In-Context Modeling

Jiarong Wen, Qi Tao, Zhang Kaiyu, Yun Qu and 4 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026Princeton Department of Computer Science, Model-based RL

EpicWorldModel: Exploration-driven Planning with Latent World Models

Bowen Feng, Julian Ost, Zhiting Mei, Anirudha Majumdar and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026City University of Hong Kong Tencent AI Lab Jiangxi University of Finance an Georgia State Shanghai University of Finance a Model-based RL

Towards Optimism-Pessimism Trade-off in Model-based Offline-to-Online Reinforcement Learning

Guochen Zhou, Yijun Yang, Qiqi Duan, Qing Su and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026Arizona State United States Military Academy Model-based RL

Near-Optimal Sample Complexity of Robust Reinforcement Learning with KL Uncertainty Set

Yudan Wang, Zilong Deng, Nathaniel D Bastian, Shaofeng Zou

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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lenient 1/5

medium 0/10

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45%Niche pick

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NeurIPS 2026New York Meta AI Research McGill University / Facebook AI Meta Model-based RL

Hierarchical World Models with Implicit Dynamics

Gaoyue Zhou, Yvonne Wu, Zichen Cui, Nicolas Ballas and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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57%Worth a look

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NeurIPS 2026The Ohio State University, Colum West Virginia Cornell Ohio State University, Columbus Model-based RL

K-PWM: Control-Oriented Structured World Models under Partial Observation

Santosh M Rajkumar, Sriram Narayanan, Samuel E Otto, Debdipta Goswami

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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lenient 1/5

medium 0/10

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45%Niche pick

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NeurIPS 2026Harvard Google Deepmind / Harvard Model-based RL

Model-Based Online Decision Making via Generative Trajectory Planning

Haldun Balim, Yilun Du, Na Li

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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71%Highly rated

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NeurIPS 2026Cornell Google Deepmind Google DeepMind Model-based RL

Joint Learning of Hierarchical Neural Options and Abstract World Model

AgentOWL jointly learns hierarchical neural options and an abstract world model for sample-efficient skill acquisition, outperforming baselines on object-centric Atari games with fewer samples and stronger generalization.

Top Piriyakulkij, Wolfgang Lehrach, Kevin Ellis, Kevin Murphy

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it

lenient 4/5

medium 3/10

strict 0/5

70%Highly rated

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NeurIPS 2026Technion Model-based RL

Reinforcement Learning with Multi-Step Lookahead Information Via Adaptive Batching

Adaptive batching policies process multi-step lookahead via state-dependent batches, yielding near-optimal regret bounds for tabular reinforcement learning.

Nadav Merlis

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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4/20 AI panelreviewers recommend it

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AI panel: 4 of 20 reviewers recommend it

lenient 2/5

medium 2/10

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76%Highly rated

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NeurIPS 2026Institute for Data Science in Me Rheinisch Westfälische Technisch RWTH Aachen Model-based RL

Dyna-Style Safety Augmented Reinforcement Learning: Staying Safe in the Face of Uncertainty

Dyna-SAuR learns scalable safety filters and policies via uncertainty-aware dynamics to reduce training failures by two orders of magnitude versus baselines.

Artur Eisele, Bernd Frauenknecht, Friedrich Solowjow, Sebastian Trimpe

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it

lenient 4/5

medium 6/10

strict 0/5

78%Highly rated

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