Kangning Zhang

I'm an incoming Ph.D. student at the APEX Lab, Shanghai Jiaotong University, advised by Prof. YongYu and Prof. Weinan Zhang .

Currently, I am an undergraduate student at Shanghai Jiao Tong University, majoring in Computer Science and Technology. My Research interest mainly lie in Data Mining, Recommendation System and Robotics Learning.

Email / Google Scholar / Github

Intership

Xiao Hong Shu
Duration: May 2023 - Present
Description: During the internship, I mainly focus on Multimodal Recommendation System, collaborating with Application Model Group of AI Technology Department of Xiaohongshu.

Shanghai Qi Zhi Institute
Duration: October 2023 - April 2024
Description: During the internship, I am delighted to cooperate with Gu Zhang and Yanjie Ze, advised by Prof. Huazhe Xu, focusing in Robotics Learning .

Publication

I'm interested in Data Mining, Recommendation and Robotics.

	DRepMRec: A Dual Representation Learning Framework for Multimodal Recommendation Kangning Zhang, Yingjie Qin, Ruilong Su, Yifan Liu Jiarui Jin, Weinan Zhang Yong Yu arxiv In this paper, we propose a novel Dual Representation learning framework called DRepMRec, which introduce separate dual lines for coupling problem and Behavior-Modal Alignment (BMA) for misalignment problem in multimodal recommendation.
	3D Diffusion Policy Yanjie Ze, Gu Zhang, Kangning Zhang, Chenyuan Hu, Muhan Wang, Huazhe Xu Acceptted by Robotics: Science and System (RSS), 2024 project / arxiv / code We present 3D Diffusion Policy (DP3), a novel visual imitation learning approach that incorporates the power of 3D visual representations into diffusion policies.
	An Aligning and Training Framework for Multimodal Recommendations Yifan Liu, Kangning Zhang, Xiangyuan Ren, Yanhua Huang, Jiarui Jin Yinjie Qin, Ruilong Su, Ruiwen Xu, Weinan Zhang Acceptted by International Conference on Information and Knowledge Managemen(CIKM), 2024 arxiv In this paper, we first systematically investigate the misalignment issue in multimodal recommendations, and propose a solution named AlignRec. We also find that the multimodal features generated by AlignRec are better than currently used ones.
	ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang Acceptted by The Web Conference (WWW), 2024 arxiv / code In this paper, we introduce ClickPrompt, aiming to model both the semantic knowledge and collaborative knowledge for accurate CTR estimation, and meanwhile address the inference inefficiency issue.
	CodeApex: A Bilingual Programming Evaluation Benchmark for Large Language Models Lingyue Fu, Huacan Chai, Shuang Luo, Kounianhua Du, Weiming Zhang Longteng Fan, Jiayi Lei, Renting Rui, Jianghao Lin, Yuchen Fang, Yifan Liu, Jingkuan Wang, Siyuan Qi, Kangning Zhang, Weinan Zhang, Yong Yu arxiv / code In this paper, we propose CodeApex, a bilingual benchmark dataset focusing on the programming comprehension and code generation abilities of LLMs.

Intership

Publication

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