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2020 – today
- 2024
[j31]Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, Jingren Zhou:
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation. Proc. VLDB Endow. 17(5): 1132-1145 (2024)- [j30]Zitao Li, Bolin Ding, Liuyi Yao, Yaliang Li, Xiaokui Xiao, Jingren Zhou:
Performance-Based Pricing of Federated Learning via Auction. Proc. VLDB Endow. 17(6): 1269-1282 (2024) - [j29]Changxin Tian
, Yuexiang Xie, Xu Chen, Yaliang Li, Xin Zhao:
Privacy-preserving Cross-domain Recommendation with Federated Graph Learning. ACM Trans. Inf. Syst. 42(5): 135:1-135:29 (2024) - [c124]Yingqian Min, Kun Zhou, Dawei Gao, Xin Zhao, He Hu, Yaliang Li:
DATA-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning. ACL (Findings) 2024: 13748-13761 - [c123]Mengsha Liu, Daoyuan Chen, Yaliang Li, Guian Fang, Ying Shen:
ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization. LREC/COLING 2024: 3057-3074 - [c122]Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. LREC/COLING 2024: 5174-5190 - [c121]Chenxi Sun, Hongyan Li, Yaliang Li, Shenda Hong:
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series. ICLR 2024 - [c120]Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding:
Improving LoRA in Privacy-preserving Federated Learning. ICLR 2024 - [c119]Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism. ICML 2024 - [c118]Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng:
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes. ICML 2024 - [c117]Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen:
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models. KDD 2024: 1827-1838 - [c116]Feijie Wu, Zitao Li, Yaliang Li, Bolin Ding, Jing Gao:
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. KDD 2024: 3345-3355 - [c115]Fangyuan Zhao, Zitao Li, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li:
VertiMRF: Differentially Private Vertical Federated Data Synthesis. KDD 2024: 4431-4442 - [c114]Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning. KDD 2024: 5260-5271 - [c113]Daoyuan Chen, Yaliang Li, Bolin Ding:
Multi-modal Data Processing for Foundation Models: Practical Guidances and Use Cases. KDD 2024: 6414-6415 - [c112]Zhe Xu, Daoyuan Chen, Jiayi Kuang, Zihao Yi, Yaliang Li, Ying Shen:
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation. SIGIR 2024: 774-784 - [c111]Daoyuan Chen, Yilun Huang, Zhijian Ma, Hesen Chen, Xuchen Pan, Ce Ge, Dawei Gao, Yuexiang Xie, Zhaoyang Liu, Jinyang Gao, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer: A One-Stop Data Processing System for Large Language Models. SIGMOD Conference Companion 2024: 120-134 - [c110]Zhen Wang, Yaliang Li, Bolin Ding, Yule Li, Zhewei Wei:
Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs. WWW 2024: 780-791 - [i88]Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen:
ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph. CoRR abs/2401.00158 (2024) - [i87]Yingqian Min, Kun Zhou, Dawei Gao, Wayne Xin Zhao, He Hu, Yaliang Li:
Data-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning. CoRR abs/2401.03563 (2024) - [i86]Qirui Jiao, Daoyuan Chen, Yilun Huang, Yaliang Li, Ying Shen:
Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study. CoRR abs/2401.17981 (2024) - [i85]Xuchen Pan, Yanxi Chen, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models. CoRR abs/2402.00518 (2024) - [i84]Yue Cui, Liuyi Yao, Yaliang Li, Ziqian Chen, Bolin Ding, Xiaofang Zhou:
An Auction-based Marketplace for Model Trading in Federated Learning. CoRR abs/2402.01802 (2024) - [i83]Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen:
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models. CoRR abs/2402.05926 (2024) - [i82]Jiamu Bai, Daoyuan Chen, Bingchen Qian, Liuyi Yao, Yaliang Li:
Federated Fine-tuning of Large Language Models under Heterogeneous Language Tasks and Client Resources. CoRR abs/2402.11505 (2024) - [i81]Dawei Gao, Zitao Li, Weirui Kuang, Xuchen Pan, Daoyuan Chen, Zhijian Ma, Bingchen Qian, Liuyi Yao, Lin Zhu, Chen Cheng, Hongzhu Shi, Yaliang Li, Bolin Ding, Jingren Zhou:
AgentScope: A Flexible yet Robust Multi-Agent Platform. CoRR abs/2402.14034 (2024) - [i80]Shen Li, Liuyi Yao, Jinyang Gao, Lan Zhang, Yaliang Li:
Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning. CoRR abs/2402.14883 (2024) - [i79]Yue Cui, Liuyi Yao, Zitao Li, Yaliang Li, Bolin Ding, Xiaofang Zhou:
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning. CoRR abs/2402.15247 (2024) - [i78]Xinyu Tang, Xiaolei Wang, Wayne Xin Zhao, Siyuan Lu, Yaliang Li, Ji-Rong Wen:
Unleashing the Potential of Large Language Models as Prompt Optimizers: An Analogical Analysis with Gradient-based Model Optimizers. CoRR abs/2402.17564 (2024) - [i77]Zikang Liu, Kun Zhou, Wayne Xin Zhao, Dawei Gao, Yaliang Li, Ji-Rong Wen:
Less is More: Data Value Estimation for Visual Instruction Tuning. CoRR abs/2403.09559 (2024) - [i76]Mengsha Liu, Daoyuan Chen, Yaliang Li, Guian Fang, Ying Shen:
ChartThinker: A Contextual Chain-of-Thought Approach to Optimized Chart Summarization. CoRR abs/2403.11236 (2024) - [i75]Youbang Sun, Zitao Li, Yaliang Li, Bolin Ding:
Improving LoRA in Privacy-preserving Federated Learning. CoRR abs/2403.12313 (2024) - [i74]Zhe Xu, Daoyuan Chen, Jiayi Kuang, Zihao Yi, Yaliang Li, Ying Shen:
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation. CoRR abs/2404.02505 (2024) - [i73]Chenxi Sun, Hongyan Li, Yaliang Li, Shenda Hong:
Review of Data-centric Time Series Analysis from Sample, Feature, and Period. CoRR abs/2404.16886 (2024) - [i72]Ce Ge, Zhijian Ma, Daoyuan Chen, Yaliang Li, Bolin Ding:
Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining. CoRR abs/2405.14908 (2024) - [i71]Zhongjie Duan, Wenmeng Zhou, Cen Chen, Yaliang Li, Weining Qian:
ExVideo: Extending Video Diffusion Models via Parameter-Efficient Post-Tuning. CoRR abs/2406.14130 (2024) - [i70]Feijie Wu, Zitao Li, Yaliang Li, Bolin Ding, Jing Gao:
FedBiOT: LLM Local Fine-tuning in Federated Learning without Full Model. CoRR abs/2406.17706 (2024) - [i69]Fangyuan Zhao, Zitao Li, Xuebin Ren, Bolin Ding, Shusen Yang, Yaliang Li:
VertiMRF: Differentially Private Vertical Federated Data Synthesis. CoRR abs/2406.19008 (2024) - [i68]Zhen Qin, Daoyuan Chen, Wenhao Zhang, Liuyi Yao, Yilun Huang, Bolin Ding, Yaliang Li, Shuiguang Deng:
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective. CoRR abs/2407.08583 (2024) - [i67]Daoyuan Chen, Haibin Wang, Yilun Huang, Ce Ge, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development. CoRR abs/2407.11784 (2024) - [i66]Yanxi Chen, Yaliang Li, Bolin Ding, Jingren Zhou:
On the Design and Analysis of LLM-Based Algorithms. CoRR abs/2407.14788 (2024) - [i65]Xuchen Pan, Dawei Gao, Yuexiang Xie, Zhewei Wei, Yaliang Li, Bolin Ding, Ji-Rong Wen, Jingren Zhou:
Very Large-Scale Multi-Agent Simulation in AgentScope. CoRR abs/2407.17789 (2024) - [i64]Die Chen, Zhiwen Li, Mingyuan Fan, Cen Chen, Wenmeng Zhou, Yaliang Li:
EIUP: A Training-Free Approach to Erase Non-Compliant Concepts Conditioned on Implicit Unsafe Prompts. CoRR abs/2408.01014 (2024) - 2023
- [j28]Chenzhan Shang, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Jing Zhang:
Multi-grained hypergraph interest modeling for conversational recommendation. AI Open 4: 154-164 (2023) - [j27]Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. Proc. VLDB Endow. 16(5): 1059-1072 (2023) - [j26]Xu Chen, Zhen Wang, Shuncheng Liu, Yaliang Li, Kai Zeng, Bolin Ding, Jingren Zhou, Han Su, Kai Zheng:
BASE: Bridging the Gap between Cost and Latency for Query Optimization. Proc. VLDB Endow. 16(8): 1958-1966 (2023) - [j25]Dawei Gao, Daoyuan Chen, Zitao Li, Yuexiang Xie, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
FS-Real: A Real-World Cross-Device Federated Learning Platform. Proc. VLDB Endow. 16(12): 4046-4049 (2023) - [j24]Hengtong Zhang, Yaliang Li, Bolin Ding, Jing Gao:
LOKI: A Practical Data Poisoning Attack Framework Against Next Item Recommendations. IEEE Trans. Knowl. Data Eng. 35(5): 5047-5059 (2023) - [j23]Liuyi Yao, Yaliang Li, Sheng Li, Jinduo Liu, Mengdi Huai, Aidong Zhang, Jing Gao:
Concept-Level Model Interpretation From the Causal Aspect. IEEE Trans. Knowl. Data Eng. 35(9): 8799-8810 (2023) - [j22]Yang Deng, Yaliang Li, Bolin Ding, Wai Lam:
Leveraging Long Short-Term User Preference in Conversational Recommendation via Multi-agent Reinforcement Learning. IEEE Trans. Knowl. Data Eng. 35(11): 11541-11555 (2023) - [j21]Ying Shen, Min Yang, Yaliang Li, Dong Wang, Hai-Tao Zheng, Daoyuan Chen:
Knowledge-Based Reasoning Network for Relation Detection. IEEE Trans. Neural Networks Learn. Syst. 34(8): 5051-5063 (2023) - [c109]Jinhao Jiang, Kun Zhou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen:
ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph. EMNLP 2023: 3721-3735 - [c108]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Tunable Soft Prompts are Messengers in Federated Learning. EMNLP (Findings) 2023: 14665-14675 - [c107]Zishuo Zhao, Yuexiang Xie, Jingyou Xie, Zhenzhou Lin, Yaliang Li, Ying Shen:
Source-Free Unsupervised Domain Adaptation for Question Answering. ICASSP 2023: 1-5 - [c106]Daoyuan Chen, Wuchao Li, Yaliang Li, Bolin Ding, Kai Zeng, Defu Lian, Jingren Zhou:
Learned Index with Dynamic $\epsilon$. ICLR 2023 - [c105]Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. ICML 2023: 5234-5256 - [c104]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-Bench: A Benchmark Suite for Federated Hyperparameter Optimization. ICML 2023: 35908-35948 - [c103]Ergute Bao, Dawei Gao, Xiaokui Xiao, Yaliang Li:
Communication Efficient and Differentially Private Logistic Regression under the Distributed Setting. KDD 2023: 69-79 - [c102]Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan, Zitao Li, Yaliang Li, Bolin Ding, Jingren Zhou:
FS-REAL: Towards Real-World Cross-Device Federated Learning. KDD 2023: 3829-3841 - [c101]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. KDD 2023: 4743-4755 - [c100]Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou, Jinduo Liu, Mengdi Huai, Jing Gao:
Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning. WWW 2023: 3680-3688 - [i63]Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng:
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. CoRR abs/2302.01677 (2023) - [i62]Daoyuan Chen, Dawei Gao, Yuexiang Xie, Xuchen Pan, Zitao Li, Yaliang Li, Bolin Ding, Jingren Zhou:
FS-Real: Towards Real-World Cross-Device Federated Learning. CoRR abs/2303.13363 (2023) - [i61]Qian Tao, Zhen Wang, Wenyuan Yu, Yaliang Li, Zhewei Wei:
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis. CoRR abs/2303.13750 (2023) - [i60]Anda Cheng, Zhen Wang, Yaliang Li, Jian Cheng:
HPN: Personalized Federated Hyperparameter Optimization. CoRR abs/2304.05195 (2023) - [i59]Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li:
Efficient Personalized Federated Learning via Sparse Model-Adaptation. CoRR abs/2305.02776 (2023) - [i58]Chenzhan Shang, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Jing Zhang:
Multi-grained Hypergraph Interest Modeling for Conversational Recommendation. CoRR abs/2305.04798 (2023) - [i57]Chenhe Dong, Yuexiang Xie, Yaliang Li, Ying Shen:
Counterfactual Debiasing for Generating Factually Consistent Text Summaries. CoRR abs/2305.10736 (2023) - [i56]Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study. CoRR abs/2307.08072 (2023) - [i55]Chenxi Sun, Yaliang Li, Hongyan Li, Shenda Hong:
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series. CoRR abs/2308.08241 (2023) - [i54]Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, Jingren Zhou:
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation. CoRR abs/2308.15363 (2023) - [i53]Weirui Kuang, Bingchen Qian, Zitao Li, Daoyuan Chen, Dawei Gao, Xuchen Pan, Yuexiang Xie, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning. CoRR abs/2309.00363 (2023) - [i52]Daoyuan Chen, Yilun Huang, Zhijian Ma, Hesen Chen, Xuchen Pan, Ce Ge, Dawei Gao, Yuexiang Xie, Zhaoyang Liu, Jinyang Gao, Yaliang Li, Bolin Ding, Jingren Zhou:
Data-Juicer: A One-Stop Data Processing System for Large Language Models. CoRR abs/2309.02033 (2023) - [i51]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Tunable Soft Prompts are Messengers in Federated Learning. CoRR abs/2311.06805 (2023) - [i50]Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, Jingren Zhou:
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism. CoRR abs/2312.04916 (2023) - [i49]Zhen Qin, Daoyuan Chen, Bingchen Qian, Bolin Ding, Yaliang Li, Shuiguang Deng:
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes. CoRR abs/2312.06353 (2023) - 2022
- [j20]Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, Jingren Zhou:
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing. Proc. VLDB Endow. 15(11): 3098-3111 (2022) - [j19]Yang Deng, Yuexiang Xie, Yaliang Li, Min Yang, Wai Lam, Ying Shen:
Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge. ACM Trans. Inf. Syst. 40(1): 2:1-2:33 (2022) - [j18]Shanlei Mu, Yaliang Li, Wayne Xin Zhao, Siqing Li, Ji-Rong Wen:
Knowledge-Guided Disentangled Representation Learning for Recommender Systems. ACM Trans. Inf. Syst. 40(1): 6:1-6:26 (2022) - [j17]Siqing Li, Yaliang Li, Wayne Xin Zhao, Bolin Ding, Ji-Rong Wen:
Interpretable Aspect-Aware Capsule Network for Peer Review Based Citation Count Prediction. ACM Trans. Inf. Syst. 40(1): 11:1-11:29 (2022) - [j16]Yang Deng, Yaliang Li, Wenxuan Zhang, Bolin Ding, Wai Lam:
Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference Modeling. ACM Trans. Inf. Syst. 40(4): 87:1-87:28 (2022) - [c99]Shanlei Mu, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Bolin Ding:
ID-Agnostic User Behavior Pre-training for Sequential Recommendation. CCIR 2022: 16-27 - [c98]Ziniu Wu, Pei Yu, Peilun Yang, Rong Zhu, Yuxing Han, Yaliang Li, Defu Lian, Kai Zeng, Jingren Zhou:
A Unified Transferable Model for ML-Enhanced DBMS. CIDR 2022 - [c97]Jinjia Feng, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei, Hongteng Xu:
MGMAE: Molecular Representation Learning by Reconstructing Heterogeneous Graphs with A High Mask Ratio. CIKM 2022: 509-519 - [c96]Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen:
Privacy-Preserved Neural Graph Similarity Learning. ICDM 2022: 191-200 - [c95]Yuexiang Xie, Zhen Wang, Yaliang Li, Ce Zhang, Jingren Zhou, Bolin Ding:
iFlood: A Stable and Effective Regularizer. ICLR 2022 - [c94]Dawei Gao, Yuexiang Xie, Zimu Zhou, Zhen Wang, Yaliang Li, Bolin Ding:
Finding Meta Winning Ticket to Train Your MAML. KDD 2022: 411-420 - [c93]Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Towards Universal Sequence Representation Learning for Recommender Systems. KDD 2022: 585-593 - [c92]Zhen Wang, Zhewei Wei, Yaliang Li, Weirui Kuang, Bolin Ding:
Graph Neural Networks with Node-wise Architecture. KDD 2022: 1949-1958 - [c91]Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. KDD 2022: 4110-4120 - [c90]Yaliang Li, Bolin Ding, Jingren Zhou:
A Practical Introduction to Federated Learning. KDD 2022: 4802-4803 - [c89]Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding:
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. NeurIPS 2022 - [c88]Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei:
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. NeurIPS 2022 - [c87]Changxin Tian, Yuexiang Xie, Yaliang Li, Nan Yang, Wayne Xin Zhao:
Learning to Denoise Unreliable Interactions for Graph Collaborative Filtering. SIGIR 2022: 122-132 - [c86]Shanlei Mu, Yaliang Li, Wayne Xin Zhao, Jingyuan Wang, Bolin Ding, Ji-Rong Wen:
Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator. SIGIR 2022: 1401-1411 - [c85]Yiqing Xie, Zhen Wang, Carl Yang, Yaliang Li, Bolin Ding, Hongbo Deng, Jiawei Han:
KoMen: Domain Knowledge Guided Interaction Recommendation for Emerging Scenarios. WWW 2022: 1301-1310 - [c84]Shaoyun Shi, Yuexiang Xie, Zhen Wang, Bolin Ding, Yaliang Li, Min Zhang:
Explainable Neural Rule Learning. WWW 2022: 3031-3041 - [i48]Yuexiang Xie, Zhen Wang, Daoyuan Chen, Dawei Gao, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing. CoRR abs/2204.05011 (2022) - [i47]Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou:
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. CoRR abs/2204.05562 (2022) - [i46]Runlin Lei, Zhen Wang, Yaliang Li, Bolin Ding, Zhewei Wei:
EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks. CoRR abs/2205.13892 (2022) - [i45]Shanlei Mu, Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Bolin Ding:
ID-Agnostic User Behavior Pre-training for Sequential Recommendation. CoRR abs/2206.02323 (2022) - [i44]Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li:
A Benchmark for Federated Hetero-Task Learning. CoRR abs/2206.03436 (2022) - [i43]Daoyuan Chen, Dawei Gao, Weirui Kuang, Yaliang Li, Bolin Ding:
pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning. CoRR abs/2206.03655 (2022) - [i42]Zhen Wang, Weirui Kuang, Ce Zhang, Bolin Ding, Yaliang Li:
FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization. CoRR abs/2206.03966 (2022) - [i41]Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen:
Towards Universal Sequence Representation Learning for Recommender Systems. CoRR abs/2206.05941 (2022) - [i40]Chenghao Lyu, Qi Fan, Fei Song, Arnab Sinha, Yanlei Diao, Wei Chen, Li Ma, Yihui Feng, Yaliang Li, Kai Zeng, Jingren Zhou:
Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing. CoRR abs/2207.02026 (2022) - [i39]Yupeng Hou, Wayne Xin Zhao, Yaliang Li, Ji-Rong Wen:
Privacy-Preserved Neural Graph Similarity Learning. CoRR abs/2210.11730 (2022) - [i38]Chenhe Dong, Yuexiang Xie, Bolin Ding, Ying Shen, Yaliang Li:
Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning. CoRR abs/2212.05789 (2022) - 2021
- [j15]Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Yaliang Li, Bolin Ding, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui:
VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition. Proc. VLDB Endow. 14(11): 2167-2176 (2021) - [j14]Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang:
A Survey on Causal Inference. ACM Trans. Knowl. Discov. Data 15(5): 74:1-74:46 (2021) - [j13]