Qwen: Towards a Generalist Model

Speaker: Junyang Lin
         Staff Engineer
         and
         Leader of Qwen team in Alibaba

Title:  "Qwen: Towards a Generalist Model"

Date:   Tuesday, 5 December 2023

Time:   4:00pm - 5:00pm

Venue:  Lecture Theater H
        (Chen Kuan Cheng Forum)
        near lift 27/28, HKUST


Abstract:

This talk introduces the large language and multimodal model series Qwen,
which stands for Tongyi Qianwen (通义千问), published and opensourced by
Alibaba Group. It will provide a brief review of the development of LLMs
and LMMs, and delve into details about building such models, including
pretraining, alignment, multimodal extension, as well as the opensource.
Additionally, it points out the limitations of recent work, and discusses
future work for both the research community and industry.


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Biography:

Junyang Lin is a staff engineer of Alibaba Group, and he is now a leader
of Qwen Team. He has been doing research in natural language processing
and multimodal representation learning, with a focus on large-scale
pretraining, and he has around 3000 citations. Recently his team released
and opensourced the Qwen series, including large language model Qwen,
large vision-language model Qwen-VL, and large audio-language model
Qwen-Audio. Previously, he focused on building large-scale pretraining
with a focus on multimodal pretraining, and developed opensourced models
OFA, Chinese-CLIP, etc. Now, he aims at building a multimodal AI system
towards a generalist agent.