🧑‍🔬 Wenxiang Hu

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery (2026 · 10 citations)
   Most current LLM-based "AI scientist" systems follow fixed, hand-built pipelines. They do not learn from what happened in earlier runs, so they may retry experiments that already failed, miss promising directions, or chase ideas that cannot be implemented. EvoScientist addresses this with a multi-agent framework that…
2. GRIN: GRadient-INformed MoE (2024 · 7 citations)
   Mixture-of-Experts (MoE) models activate only a few expert subnetworks per token. However, the discrete routing step has no true gradient, so standard training substitutes the gating gradient. Large-scale MoE training also usually relies on expert parallelism, which forces capacity limits and discards overflow…

🤝 Co-authors here

12 of 15 co-authors with a page, the most papers together first.

• Chen Liang
• Hao Cheng
• Jan Piotrowski
• Liyuan Liu
• Masahiro Tanaka
• Shuohang Wang
• Vishrav Chaudhary
• Xi Zhang
• Xiaodong Liu
• Xiaohui Yan
• Xiaoxia Wu
• Yelong Shen

🔗 Cited by

Papers of our library cite their works 16 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated 1 November 2026

This page in Markdown → https://md.research.elamur.ai/free/en/authors/wenxiang-hu/