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20232026
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cs.LG2026

Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference

Chuning Zhu, Eva Xu, Jose Barreiros +3

Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a similar capacity for adaptive "…

cs.LG2026

Operator-Theoretic Foundations and Policy Gradient Methods for General MDPs with Unbounded Costs

Abhishek Gupta, Aditya Mahajan

Markov decision processes (MDPs) is viewed as an optimization of an objective function over certain linear operators over general function spaces. A new existence result is establi…

cs.LG2025

Semantic World Models

Jacob Berg, Chuning Zhu, Yanda Bao +2

Planning with world models offers a powerful paradigm for robotic control. Conventional approaches train a model to predict future frames conditioned on current frames and actions,…

cs.LG2024

Distributional Successor Features Enable Zero-Shot Policy Optimization

Chuning Zhu, Xinqi Wang, Tyler Han +2

Intelligent agents must be generalists, capable of quickly adapting to various tasks. In reinforcement learning (RL), model-based RL learns a dynamics model of the world, in princi…

cs.LG2023

Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning

Zhaoyi Zhou, Chuning Zhu, Runlong Zhou +3

Off-policy dynamic programming (DP) techniques such as -learning have proven to be important in sequential decision-making problems. In the presence of function approximation, h…