arXiv (All)
open access
ATM: Why Latent World Models Can Fail to Plan
Latent world models can achieve accurate latent prediction yet still differ substantially in downstream planning performance. We argue that a key source of this discrepancy lies in the structure of action-induced latent transitions. We formalize action-identifiability through Bayes inverse risk, cha
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- ATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning#1131175
- From World Models to World Action Models: Rethinking Next-State Prediction#1128685
- V-JEPA Policy: Building Effective World-Action Models on Predictive Visual Latents#1141294
- ARC-Bench: Closed-Loop Replanning Masks Broken Action Ranking in Frozen JEPA World Models#972525
- The Right Future for Action: Learning Action-Relevant Predictive States in World Action Models#1049111
Record · ID 1143799
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive