Good Papers

Showing papers from Xiaomi Show all papers

57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026South China University of TechnoRIKENXiaomi CorporationXiaomiFlow matching

Inference-Time Self-Aligned Drifting for Few-Step Flow Matching

Shigui Li, JIAN XU, Wei Chen, Junmei Yang and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026ShanxiU Technology SydneyXiaomi CorporationU Trento Via Calepina n. 14 - 38Huazhong University of Science aEmbodied agents

Think Densely, Act Sparsely: Latent Expert Cognitive Chains for Vision-Language-Action Autonomous Driving

Jie Wang, Guang Li, Zhijian Huang, Jinlong Li and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026TsinghuaU MacauXiaomi CorporationLi Auto Inc.Alibaba GroupEmbodied agents

LaST-VLA: Thinking in Latent Spatio-Temporal Space for Vision-Language-Action in Autonomous Driving

LaST-VLA replaces explicit chain-of-thought reasoning with a physically grounded latent spatio-temporal framework, achieving record NAVSIM scores and improved reasoning.

Yuechen Luo, Fang Li, Shaoqing Xu, Yang Ji and 9 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 3/5
medium 5/10
strict 1/5