Signals 4 · free daily AI digest

Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model

Paper recorded by Signals 4 on 2026-09-23 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-23 on arXiv · recorded by Signals 4 on 2026-09-24

Category: cs.AI · 人工智能 · first seen 2026-09-24

Abstract

Latent world models that integrate a flow in a frozen self supervised latent space train stably and cheaply, yet silently lose the property manipulation depends on most: motion. The pretrained flow never moves the manipulated object; retraining it with latent-only losses only trades stillness for teleport-like motion. We trace the failure to the training signal, not the representation: anchor-spar

Read on arXiv →

#6 most recent of 380 cs.AI papers we have recorded · ↑ newer: Agent-Editing World Model: Rethinking World Modeling for LLM Agents · ↓ older: Learning Holographic Reduced Representations with Clifford Variational
Cite this page: Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model: the #6 most recent of 380 cs.AI papers we have recorded (as of 2026-09-23). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/frozen-flows-forget-diagnosing-and-restoring-lost-motion-in-a-latent-flow-world-.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions