From the 1 of 9 linked papers with an AI index.
6 citations · 6 across the 4 of their papers we have counts for
9 papers
DriftWorld: Fast World Modeling through Drifting
Susie Lu, Haonan Chen, Weirui Ye +1
The paper introduces DriftWorld, an action‑conditioned world model that uses a drifting generative approach to produce future frames in a single forward pass, enabling fast (30+ fp…
Temporal Backtracking Search for Test-time Generative Video Reasoning
Sejoon Jun, Zheng Ding, Huangyuan Su +2
While test-time scaling has revolutionized reasoning in large language models, generative video reasoning remains bottlenecked by a single-shot paradigm. We demonstrate that search…
Self-Improving Language Models with Bidirectional Evolutionary Search
Guowei Xu, Zhenting Qi, Huangyuan Su +4
Search has been proposed as an effective method for self-improving language models and agentic systems, both for post-training sample generation and for inference. However, widely…
Seer: Language Instructed Video Prediction with Latent Diffusion Models
Xianfan Gu, Chuan Wen, Weirui Ye +2
Imagining the future trajectory is the key for robots to make sound planning and successfully reach their goals. Therefore, text-conditioned video prediction (TVP) is an essential…
Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own
Weirui Ye, Yunsheng Zhang, Haoyang Weng +6
Reinforcement learning (RL) is a promising approach for solving robotic manipulation tasks. However, it is challenging to apply the RL algorithms directly in the real world. For on…
Scaling Tasks, Not Samples: Mastering Humanoid Control through Multi-Task Model-Based Reinforcement Learning
Shaohuai Liu, Weirui Ye, Yilun Du +1
Developing generalist robots capable of mastering diverse skills remains a central challenge in embodied AI. While recent progress emphasizes scaling model parameters and offline d…