Skip to content

Author

Jiajun Wu

We have 18 of 218 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Preprint Aug 2026

FL-MAESTRO: Multi-Agent LLM Orchestration for Resource-Constrained Federated Learning

FL-MAESTRO is proposed, a multi-agent orchestrator that makes the joint runtime FL decision directly through three specialist LLM agents, one per decision dimension, and matches the accuracy of the strongest energy-aware baseline while cutting wasted round energy from over a third to near zero.

Jia-Jun Wu, Zi-Rui Wang, Jia-Yu Zhou et al. · 0 citations
#natural language process... Preprint Aug 2026

WebWorld: The Browser as a World Model for Self-Improving Web Code

WebWorld is presented, the interface that lets a VLM prior interact with this browser-as-world-model autonomously and decides which interactions become supervision and reaches the level of strong frontier systems such as Kimi-K2.6 and GPT-5.4 on interactive HTML generation.

Jia-Jun Wu, Jian Yang, Ya-Xin Du et al. · 0 citations
Jul 2026

Masked Visual Actions for Unified World Modeling

Masked Visual Actions is introduced, a pixel-space control interface that expresses action as a partially revealed trajectory of an arbitrary entity in a video that supports inverse modeling by synthesizing robot motion from desired object motion.

Hadi Alzayer, Wenlong Huang, Haonan Chen et al. · 3 citations · ⚡1
Preprint Jul 2026

APIVOT: Adaptive Planning with Interleaved Vision-Language Thoughts

This work proposes APIVOT, a VLM-based planner that adaptively interleaves language and visual thoughts for long-horizon planning that outperforms general-purpose VLMs and prior planning frameworks, achieving the largest gains in spatially constrained settings.

Emily Jin, Joy Hsu, Yiqing Xu et al. · 0 citations

L pCoder ∞ : Scaling Code Intelligence via Looped Language Models

This work presents LoopCoder pre-trained on 12T+ code and general tokens, along with LoopCoder-Thinking and LoopCoder-Instruct variants, the first large-scale looped transformer for code, achieving comparable performance to standard dense architectures with more parameters.

Jian Yang, Wei Zhang, Shawn Guo et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.