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Yueqian Wang 王越千
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Future Blog Post
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Blog Post number 4
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Blog Post number 1
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internships
Algorithm R&D Intern @ ByteDance Douyin Search Group - 字节跳动抖音搜索
Develop searching strategies for Douyin.
portfolio
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publications
SMASH: Improving SMAll Language Models’ Few-SHot Ability with Prompt-Based Distillation
Yueqian Wang, Chang Liu, Kai Chen, Xi Wang, Dongyan Zhao
Published in Findings of the Association for Computational Linguistics: EMNLP, 2022
Prompt-based learning and distillation for small transformer encoder-based language models.
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VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions
Yuxuan Wang, Zilong Zheng, Xueliang Zhao, Jinpeng Li, Yueqian Wang, Dongyan Zhao
Published in Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
A large-scale video dialogue corpus collected from TV series with scene and segment transistion annotation.
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Overview of the NLPCC 2023 Shared Task 10: Learn to Watch TV: Multimodal Dialogue Understanding and Response Generation
Yueqian Wang, Yuxuan Wang, Dongyan Zhao
Published in Natural Language Processing and Chinese Computing, 2023
Hosted a shared task about video dialogue understanding and prediction at NLPCC 2023.
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STAIR: Spatial-Temporal Reasoning with Auditable Intermediate Results for Video Question Answering
Yueqian Wang, Yuxuan Wang, Kai Chen, Dongyan Zhao
Published in AAAI Conference on Artificial Intelligence, 2024
A neural module network (NMN) based method for videoqa with long videos and complicated questions.
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HawkEye: Training Video-Text LLMs for Grounding Text in Videos
Yueqian Wang, Xiaojun Meng, Jianxin Liang, Yuxuan Wang, Qun Liu, Dongyan Zhao
Published in arXiv:2403.10228, 2024
One of the first video-text LLMs that can perform temporal video grounding in a fully text-to-text manner, and InternVid-G, a large-scale video-text dataset for video grounding training.
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LSTP: Language-guided Spatial-Temporal Prompt Learning for Long-form Video-Text Understanding
Yuxuan Wang, Yueqian Wang, Pengfei Wu, Jianxin Liang, Dongyan Zhao, Zilong Zheng
Published in arXiv:2402.16050, 2024
Intergrating optical flow for relevant content selection to improve video-text LLMs’ abilities on videoqa.
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talks
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teaching
TA @ Data Analysis in Python - Python 数据分析
Undergraduate course, Department of Information Management, Peking University
Data Analysis in Python is a programming course for undergraduates. The syllabus of this course includes commonly used statistical methods, machine learning algorithms, and data visualization methods, as well as their implementations in Python.
TA @ Introduction to Computation (B) - 计算概论（B）
Undergraduate course, School of Electronics Engineering and Computer Science, Peking University
Introduction to Computation （计算概论） is a programming course for junior undergraduates. The syllabus of this course includes basic programming skills in Python.