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Junkang Wu
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2020 – today
- 2024
- [c9]Wentao Shi, Mengqi Yuan, Junkang Wu, Qifan Wang, Fuli Feng:
Direct Multi-Turn Preference Optimization for Language Agents. EMNLP 2024: 2312-2324 - [c8]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang:
BSL: Understanding and Improving Softmax Loss for Recommendation. ICDE 2024: 816-830 - [c7]Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang:
Masked Graph Modeling with Multi- View Contrast. ICDE 2024: 2584-2597 - [c6]Wentao Shi
, Chenxu Wang
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. WWW 2024: 3253-3264 - [i10]Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He:
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. CoRR abs/2403.00844 (2024) - [i9]Wentao Shi, Mengqi Yuan, Junkang Wu, Qifan Wang, Fuli Feng:
Direct Multi-Turn Preference Optimization for Language Agents. CoRR abs/2406.14868 (2024) - [i8]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. CoRR abs/2407.07880 (2024) - [i7]Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He:
β-DPO: Direct Preference Optimization with Dynamic β. CoRR abs/2407.08639 (2024) - 2023
- [c5]Hang Pan
Discriminative-Invariant Representation Learning for Unbiased Recommendation. IJCAI 2023: 2270-2278 - [c4]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He:
Understanding Contrastive Learning via Distributionally Robust Optimization. NeurIPS 2023 - [c3]Wentao Shi
On the Theories Behind Hard Negative Sampling for Recommendation. WWW 2023: 812-822 - [c2]Jiawei Chen
Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. WWW 2023: 1085-1096 - [i6]Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He:
On the Theories Behind Hard Negative Sampling for Recommendation. CoRR abs/2302.03472 (2023) - [i5]Wentao Shi, Junkang Wu, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Wei Wu, Xiangnan He:
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion. CoRR abs/2302.04088 (2023) - [i4]Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He:
Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation. CoRR abs/2302.04775 (2023) - [i3]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He:
Understanding Contrastive Learning via Distributionally Robust Optimization. CoRR abs/2310.11048 (2023) - [i2]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang:
BSL: Understanding and Improving Softmax Loss for Recommendation. CoRR abs/2312.12882 (2023) - 2021
- [c1]Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He:
DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network. CIKM 2021: 2140-2149 - [i1]Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He:
DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network. CoRR abs/2108.09628 (2021)
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