arXiv AI By Sam Siavoshian, Omar Ramadan, Amir K. Saeed, Benjamin A. Johnson, Amin Mohamed El-Amin Diab, Benjamin M. Rodriguez

ChronoState: Hidden Elapsed-Time Conditioning for Temporal-State Action Selection in Frozen-Backbone Language Models

Read the original on arXiv AI →

arXiv:2608. 09124v1 Announce Type: new Abstract: Temporal decisions in language-model systems often depend on both symbolic task state and elapsed wall-clock time, such as cache expiration, job completion, quota resets, deadlines, or stale sessions.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI
Jul 20

Think at 5 Hz, Act at 20 Hz: Asynchronous Fast-Slow Vision-Language-Action Inference for Closed-Loop Driving

arXiv:2607. 15621v1 Announce Type: cross Abstract: Large language models bring instruction following and scene reasoning to end-to-end driving, but their inference latency collides with the control rate a vehicle requires.

By Yun Li, Jiachen Gong, Simon Thompson, Ehsan Javanmardi, Qunli Zhang, Zifan Zeng, Shiming Liu, Peng Wang, Zixuan Guo, Manabu Tsukada
arXiv Machine Learning
Sep 10

ActionSplice: In-Flight Action Editing for Interactive World Models

ActionSplice is an inference framework for chunk‑autoregressive video world models that allows in‑flight action editing without re‑sampling completed evaluations. It formulates the problem as Counterfactual State Transport (CST), using a lightweight corrector to move the backbone representation toward the state induced by a revised action at the same solver step. Two variants, CST*R and CST*T, update either the entire active chunk or only its suffix, achieving significant reductions in rollback‑relative LPIPS and providing speedups over waiting.

By Pardis Taghavi, Tingyu Guo, Jonas Lossner, Gaurav Pandey, Reza Langari