4 papers
DriveZero: End-to-End Driving Beyond Human Demonstrations
Hao He, Chengcheng Hu, Zirun Su +17
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavioral coverage of the recorded…
On the Identifiability of Controlled World Models
Xiangteng Zhang, Yang Guan, Bo Zhang +3
World model serves as a promising tool to infer environment dynamics under high-dimensional observations and candidate actions. Recently, LeCun's JEPA provides a compelling framewo…
Orca: The World is in Your Mind
Yihao Wang, Yuheng Ji, Mingyu Cao +54
We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals and exposes it through multi…
Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs
James Flemings, Haosheng Gan, Hongyi Li +2
In-context learning (ICL) has shown promising improvement in downstream task adaptation of LLMs by augmenting prompts with relevant input-output examples (demonstrations). However,…