Tencent Hunyuan Team

Tencent Hunyuan Team has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Ao Liu, Botong Zhou, Can Xu.

2 papers in our library · 2025–2026

The profile is the library's match of the name; two people with one name are not always told apart.

Fields, topics and concepts

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

The most cited first (OpenAlex and our library).

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought (2025 · 10 citations)
Hunyuan-TurboS tackles the tension between strong LLM quality and inference cost, especially for long inputs and reasoning-heavy requests.
Hunyuan-A13B Technical Report (2026 · 1 citation)
Serving frontier LLMs is costly because dense models use every weight for every token. Tencent's Hunyuan team addresses this with Hunyuan-A13B, an openly released sparse Mixture-of-Experts model. It has 80B parameters in total, but only about 13B are active per token: one always-on shared expert plus 8 of 64…

11 co-authors with a page, the most papers together first.

Papers of our library cite their works 11 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated 31 October 2026