Tu Teng

Focus on natural language processing, knowledge graph, data mining

Co-publish Paper: CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning

Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, Jie Tang

(IEEE TKDE-2020-07-0735.R1)

Co-publish Paper: GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation

Ji Qi, Jifan Yu, Teng Tu, Kunyu Gao, Yifan Xu, Xinyu Guan, Xiaozhi Wang, Yuxiao Dong, Bin Xu, Lei Hou, Juanzi Li, Jie Tang, Weidong Guo, Hui Liu, Yu Xu

(CIKM 2023 Resource Track)

Co-publish Paper: ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation

Xianzhe Fan, Zihan Wu, Chun Yu, Fenggui Rao, Weinan Shi, Teng Tu

(CHI'24)

As Research Assistant

Responsible for sentiment classification and topic classification of telephone psychological consultation records during the COVID-19 epidemic, and establish a collaborative AI-assisted labeling platform.

Focus on knowledge graph-assisted recommendation system.

Preprint: RCK: Recommendation System with Cross-Domain Knowledge (In Progress)

work with: Xinwen Huang, Giorgos Mamakoukas

Introduce a two-dimensional learnable Position Embedding to optimize the image input method of VQ Tokenizer based on BEiT2. The VQ Tokenizer will serve as backbone for various generation and alignment downstream tasks, one of which is known as CogVLM. (In Progress)

work with: Ming Ding, Zhuoyi Yang, Jie Tang

Implement a project that uses natural language to query knowledgeable videos, knowing as Kuaizhi Search, based on the multi-model knowledge graph, with a pipeline including sequence annotation, entity disambiguation, and text matching.

work with: Haojie Pan

Organize students from the Department of Computer Science, the Academy of Fine Arts, the School of Economics and Management, and the Department of Psychology to build more professional and easier-to-use generative AI tools and platforms, to explore more cutting-edge and more pragmatic generative AI research directions, and to promote broader and more active generative AI discussions environment

Responsible for the design of promotional materials (such as main posters, cultural shirts, etc.), responsible for organizing publicity and on-site photography, and participating in the planning of large-scale activities of the Department of Computer Science (such as Student Day, Orientation, Graduation, etc.)