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Fei Huang

Qwen Team, Alibaba Group

32 papers hereh-index 1618.3k citations36 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author22

Across the 27 of 32 papers where every author was matched, so the position is known.

fields
  • cs.CL31
  • cs.LG1
affiliations
  • Qwen Team, Alibaba Group
same name
  • Fei Huang — 83 papers, h 49
  • Fei Huang — 58 papers, h 24
  • Fei Huang — 44 papers, h 19
  • Fei Huang — 38 papers, h 29
  • Fei Huang — 26 papers, h 15
  • Fei Huang — 16 papers, h 11

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedQwen3 Technical Report

111 citations · 513 across the 30 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.CL2024

P-MMEval: A Parallel Multilingual Multitask Benchmark for Consistent Evaluation of LLMs

Yidan Zhang, Yu Wan, Boyi Deng +6

Recent advancements in large language models (LLMs) showcase varied multilingual capabilities across tasks like translation, code generation, and reasoning. Previous assessments of…

cs.CL2024★ 45 cited

Qwen2.5-Coder Technical Report

Binyuan Hui, Jian Yang, Zeyu Cui +21

In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes six models: Qwen2.5-Coder-(0.5B/1.5B/3B/7B/14B/…

cs.CL2024★ 60 cited

Qwen2 Technical Report

An Yang, Baosong Yang, Binyuan Hui +59

This report introduces the Qwen2 series, the latest addition to our large language models and large multimodal models. We release a comprehensive suite of foundational and instruct…

cs.CL2024★ 2 cited

Training-Free Long-Context Scaling of Large Language Models

Chenxin An, Fei Huang, Jun Zhang +4

The ability of Large Language Models (LLMs) to process and generate coherent text is markedly weakened when the number of input tokens exceeds their pretraining length. Given the e…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.