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Notes on world models
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AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control
AD-WM is a joint-embedding world model designed for counterfactual model predictive control. It combines residual latent dynamics with action-recovery regularization so the model preserves action-dependent differences…
Alaya-EVOKE: From Linear-Scaling Supervision to Endless World
The paper presents an interactive video world model that keeps track of a scene's state outside the model itself (an externally stored, camera-indexed memory) so it does not need to hold everything in context, aiming…
DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation
The paper describes a model that, given a starting camera frame, a language instruction, and a planned sequence of robot actions, predicts what the robot's camera would see next, intended to help with robotic…
Better Slots, Better Worlds: Representation Quality & Robustness in Object-Centric World Models
The study investigates the performance of object-centric world models for visual model-predictive control, which enable agents to accomplish tasks through planning. The researchers find that these models perform better…
Better Slots, Better Worlds: Representation Quality & Robustness in Object-Centric World Models
The research focuses on object-centric world models (OCWMs) for artificial intelligence agents. The study compares OCWMs with traditional scene-centric models in terms of representation quality, planning success, and…
Concept-Guided Spatial Regularization for World Models in Atari Pong
Researchers evaluate five world model agents in Atari Pong and find inconsistencies and failures in the generated video trajectories. They hypothesize that insufficient modeling of task-critical concepts may contribute…
Concept-Guided Spatial Regularization for World Models in Atari Pong
Researchers evaluate five world model agents in Atari Pong and find failures in the generated video trajectories, such as ball disappearance and incorrect motion. They propose a new method called Concept-Guided Spatial…
Concept-Guided Spatial Regularization for World Models in Atari Pong
Researchers evaluate five different visual world-model agents in Atari Pong and find that their rollouts contain errors such as ball disappearance and incorrect motion. They propose Concept-Guided Spatial…
A Definition and Roadmap for World Models
The provided text discusses the concept of 'world models', which are internal simulators used in AI to understand the structure and dynamics of an environment. The authors propose a definition for world models, outline…
Self-Evolving World Models for LLM Agent Planning
In this paper, the authors introduce WorldEvolver, a framework for self-evolving world models designed to improve the planning abilities of long-horizon language model agents by offering predictions of action…
Self-Evolving World Models for LLM Agent Planning
The paper introduces a new framework called WorldEvolver for long-horizon agents. This framework improves the accuracy of predictions about action consequences before execution, which is crucial for agents to make…
World Models in Pieces: Structural Certification for General Agents
The paper proposes a method to evaluate the understanding of an AI agent in a complex world model, focusing on situations where the agent's abilities are specialized. The authors argue that standard guarantees fail to…
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