Xuancheng Ren
Xuancheng Ren is a researcher at Alibaba Group whose work spans natural language processing, sequence modeling and multimodal representation learning. After earning a computer science degree at Peking University in 2017 and pursuing graduate study under Xu Sun, he coauthored a 2021 method for faster language-model inference. From 2023 through 2025, he coauthored reports for Qwen, Qwen2, Qwen2.5, Qwen3 and Qwen3-VL. In 2026, he coauthored Qwen-Scope, an open-source sparse-autoencoder suite for seven Qwen3 and Qwen3.5 variants, and Qwen-RobotNav, a configurable navigation model for agentic systems.
Timeline
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2017
A Peking University degree
He earns a Bachelor of Science in computer science at Peking University in 2017 and studies in its School of Electronics Engineering and Computer Science under Professor Xu Sun.
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2021
Faster language-model inference
In 2021, he coauthors a global past-future method for early exit in pretrained language models. It combines information from past and future layers to make predictions while accelerating inference.
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September 2023–December 2024
Three Qwen technical reports
In September 2023, he coauthors Qwen Technical Report, which introduces Qwen as the first installment in its model series. He coauthors Qwen2 Technical Report in July 2024; it presents large language and multimodal models. Qwen2.5 Technical Report follows in December 2024 with a comprehensive series of large language models.
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May 2025
The Qwen3 technical report
In May 2025, he coauthors Qwen3 Technical Report, which presents Qwen3 as the latest version of the Qwen model family.
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November 2025
Qwen3-VL for multimodal input
In November 2025, he coauthors Qwen3-VL Technical Report. The model integrates text, images and video in interleaved contexts of up to 256K tokens.
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May 2026
Qwen-Scope for sparse features
In May 2026, he coauthors Qwen-Scope, an open-source suite of sparse autoencoders with 14 groups across seven Qwen3 and Qwen3.5 model variants.
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June 2026
Qwen-RobotNav navigation model
In June 2026, he coauthors Qwen-RobotNav Technical Report, which describes a configurable navigation model for agentic systems trained on 15.6 million samples.
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Since 2022
Researcher at Alibaba Group
In 2022, he joins Alibaba Group as a researcher. His research spans natural language processing, sequence modeling and multimodal representation learning.
Career
- NowAlibabaResearcher
Education
- 2017Peking UniversityBachelor of Science in computer science
Sources and credits
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- Xuancheng Ren
- A Global Past-Future Early Exit Method for Accelerating Inference of Pre-trained Language Models
- Qwen Technical Report
- Qwen2 Technical Report
- Qwen2.5 Technical Report
- Qwen3 Technical Report
- Qwen3-VL Technical Report
- Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models
- Qwen-RobotNav Technical Report: A Scalable Navigation Model Designed for an Agentic Navigation System
- Xuancheng Ren (Alibaba Group): natural language processing