Junkang Wu

According to our database, Junkang Wu authored at least 15 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Large Language Models Empower Personalized Valuation in Auction.

Jie Sun, Tianyu Zhang, Houcheng Jiang, Kexin Huang, Chi Luo, Junkang Wu, Jiancan Wu, An Zhang, Xiang Wang

CoRR, 2024

α-DPO: Adaptive Reward Margin is What Direct Preference Optimization Needs.

Junkang Wu, Xue Wang, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

CoRR, 2024

β-DPO: Direct Preference Optimization with Dynamic β.

Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

CoRR, 2024

Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization.

Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He

CoRR, 2024

Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation.

Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He

Proceedings of the ACM on Web Conference 2024, 2024

BSL: Understanding and Improving Softmax Loss for Recommendation.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Masked Graph Modeling with Multi- View Contrast.

Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Direct Multi-Turn Preference Optimization for Language Agents.

Wentao Shi, Mengqi Yuan, Junkang Wu, Qifan Wang, Fuli Feng

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He

CoRR, 2023

FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion.

Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He

CoRR, 2023

On the Theories Behind Hard Negative Sampling for Recommendation.

Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Understanding Contrastive Learning via Distributionally Robust Optimization.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Discriminative-Invariant Representation Learning for Unbiased Recommendation.

Hang Pan, Jiawei Chen, Fuli Feng, Wentao Shi, Junkang Wu, Xiangnan He

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2021

DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network.

Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021