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Jizhi Zhang
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2020 – today
- 2024
- [c19]Wenjie Wang
, Honghui Bao
Learnable Item Tokenization for Generative Recommendation. CIKM 2024: 2400-2409 - [c18]Shihao Cai, Keqin Bao, Hangyu Guo, Jizhi Zhang, Jun Song, Bo Zheng:
GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation. EMNLP 2024: 750-766 - [c17]Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, Fuli Feng:
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models. EMNLP 2024: 10540-10552 - [c16]Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang:
BSL: Understanding and Improving Softmax Loss for Recommendation. ICDE 2024: 816-830 - [c15]Tianhao Shi
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. SIGIR 2024: 448-457 - [c14]Yiyan Xu
Diffusion Models for Generative Outfit Recommendation. SIGIR 2024: 1350-1359 - [c13]Wentao Shi
Large Language Models are Learnable Planners for Long-Term Recommendation. SIGIR 2024: 1893-1903 - [c12]Keqin Bao
Large Language Models for Recommendation: Past, Present, and Future. SIGIR 2024: 2993-2996 - [c11]Jizhi Zhang
Large Language Models for Recommendation: Progresses and Future Directions. WWW (Companion Volume) 2024: 1268-1271 - [c10]Meng Jiang
Item-side Fairness of Large Language Model-based Recommendation System. WWW 2024: 4717-4726 - [i22]Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He:
Item-side Fairness of Large Language Model-based Recommendation System. CoRR abs/2402.15215 (2024) - [i21]Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He:
DiFashion: Towards Personalized Outfit Generation and Recommendation. CoRR abs/2402.17279 (2024) - [i20]Jizhi Zhang, Keqin Bao, Wenjie Wang, Yang Zhang, Wentao Shi, Wanhong Xu, Fuli Feng, Tat-Seng Chua:
Prospect Personalized Recommendation on Large Language Model-based Agent Platform. CoRR abs/2402.18240 (2024) - [i19]Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng:
Enhancing Long-Term Recommendation with Bi-level Learnable Large Language Model Planning. CoRR abs/2403.00843 (2024) - [i18]Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He:
Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. CoRR abs/2405.01063 (2024) - [i17]Wenjie Wang, Honghui Bao, Xilin Chen, Jizhi Zhang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua:
Learnable Tokenizer for LLM-based Generative Recommendation. CoRR abs/2405.07314 (2024) - [i16]Shihao Cai, Keqin Bao, Hangyu Guo, Jizhi Zhang, Jun Song, Bo Zheng:
GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation. CoRR abs/2406.11503 (2024) - [i15]Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, Fuli Feng:
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation. CoRR abs/2406.14900 (2024) - [i14]Chengbing Wang, Wentao Shi, Jizhi Zhang, Wenjie Wang, Hang Pan, Fuli Feng:
Debias Can be Unreliable: Mitigating Bias Issue in Evaluating Debiasing Recommendation. CoRR abs/2409.04810 (2024) - [i13]Shihao Cai, Jizhi Zhang, Keqin Bao, Chongming Gao, Fuli Feng:
FLOW: A Feedback LOop FrameWork for Simultaneously Enhancing Recommendation and User Agents. CoRR abs/2410.20027 (2024) - [i12]Yang Zhang, Juntao You, Yimeng Bai, Jizhi Zhang, Keqin Bao, Wenjie Wang, Tat-Seng Chua:
Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation. CoRR abs/2410.22809 (2024) - [i11]Keqin Bao, Ming Yang, Yang Zhang, Jizhi Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning. CoRR abs/2410.23136 (2024) - 2023
- [j2]Zeyu Yang, Jizhi Zhang, Fuli Feng, Chongming Gao, Qifan Wang, Xiangnan He:
Interactive active learning for fairness with partial group label. AI Open 4: 175-182 (2023) - [c9]Jujia Zhao
Popularity-aware Distributionally Robust Optimization for Recommendation System. CIKM 2023: 4967-4973 - [c8]Moxin Li, Wenjie Wang, Fuli Feng, Yixin Cao, Jizhi Zhang, Tat-Seng Chua:
Robust Prompt Optimization for Large Language Models Against Distribution Shifts. EMNLP 2023: 1539-1554 - [c7]Jizhi Zhang
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. RecSys 2023: 993-999 - [c6]Keqin Bao
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. RecSys 2023: 1007-1014 - [c5]Zhengyi Yang
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. SIGIR 2023: 331-340 - [c4]Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Large Language Models for Recommendation: Progresses and Future Directions. SIGIR-AP 2023: 306-309 - [c3]Wentao Shi
On the Theories Behind Hard Negative Sampling for Recommendation. WWW 2023: 812-822 - [i10]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) - [i9]Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. CoRR abs/2305.00447 (2023) - [i8]Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He:
Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. CoRR abs/2305.07609 (2023) - [i7]Moxin Li, Wenjie Wang, Fuli Feng, Jizhi Zhang, Tat-Seng Chua:
Robust Instruction Optimization for Large Language Models with Distribution Shifts. CoRR abs/2305.13954 (2023) - [i6]Keqin Bao, Jizhi Zhang, Wenjie Wang, Yang Zhang, Zhengyi Yang, Yancheng Luo, Fuli Feng, Xiangnan He, Qi Tian:
A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems. CoRR abs/2308.08434 (2023) - [i5]Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang:
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation. CoRR abs/2310.16566 (2023) - [i4]Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang, Xiangnan He:
CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation. CoRR abs/2310.19488 (2023) - [i3]Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He:
Large Language Model Can Interpret Latent Space of Sequential Recommender. CoRR abs/2310.20487 (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
- [c2]Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua:
Empowering Language Understanding with Counterfactual Reasoning. ACL/IJCNLP (Findings) 2021: 2226-2236 - [i1]Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua:
Empowering Language Understanding with Counterfactual Reasoning. CoRR abs/2106.03046 (2021)
2010 – 2019
- 2017
- [c1]Jizhi Zhang, Guoying Zhang, Qiangyu Wang, Shuang Bai:
A Weakly Supervised Deep Learning Semantic Segmentation Framework. SmartCloud 2017: 182-185 - 2010
- [j1]Vitaliy Avrutin, Gene Cantwell, Jizhi Zhang, J. J. Song, Donald J. Silversmith, Hadis Morkoç:
Bulk ZnO: Current Status, Challenges, and Prospects. Proc. IEEE 98(7): 1339-1350 (2010)
Coauthor Index
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