Dawei Yin
About
In The Last Decade
Dawei Yin
60 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Artificial Intelligence 2.0k
- Information Systems 1.6k
- Computer Vision and Pattern Recognition 493
- Computer Networks and Communications 309
- Statistical and Nonlinear Physics 281
Countries citing papers authored by Dawei Yin
This map shows the geographic impact of Dawei Yin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dawei Yin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dawei Yin more than expected).
Fields of papers citing papers by Dawei Yin
This network shows the impact of papers produced by Dawei Yin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dawei Yin. The network helps show where Dawei Yin may publish in the future.
Co-authorship network of co-authors of Dawei Yin
This figure shows the co-authorship network connecting the top 25 collaborators of Dawei Yin. A scholar is included among the top collaborators of Dawei Yin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dawei Yin. Dawei Yin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Retrieval Models Aren’t Tool-Savvy: Benchmarking Tool Retrieval for Large Language Models | Yuhan Wang, Pengjie Ren et al. | 0 | |
| 2 | Mitigating Hallucinations in Large Vision-Language Models via Entity-Centric Multimodal Preference Optimization | Kesheng Wu, Zhiao Shi et al. | 1 | |
| 3 | Graph Machine Learning in the Era of Large Language Models (LLMs) | ACM Transactions on Intelligent Systems and Technology | Shijie Wang, Wenqi Fan et al. | 6 |
| 4 | TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy | Qi Liu, Jiaxin Mao et al. | 2 | |
| 5 | Contrastive Modality-Disentangled Learning for Multimodal Recommendation | ACM Transactions on Information Systems | Xixun Lin, Yanan Cao et al. | 11 |
| 6 | Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation | Jiawei Sheng, Xinghua Zhang et al. | 1 | |
| 7 | Agent4Ranking: Semantic Robust Ranking via Personalized Query Rewriting Using Multi-Agent LLMs | ACM Transactions on Information Systems | Lixin Su, Suqi Cheng et al. | 0 |
| 8 | GS2P: a generative pre-trained learning to rank model with over-parameterization for web-scale search | Machine Learning | Yuchen Li, Haoyi Xiong et al. | 5 |
| 9 | A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models breakdown → | Wenqi Fan, Yujuan Ding et al. | 137 | |
| 10 | When Search Engine Services Meet Large Language Models: Visions and Challenges | IEEE Transactions on Services Computing | Haoyi Xiong, 将尚 渡辺 et al. | 19 |
| 11 | LLMRec: Large Language Models with Graph Augmentation for Recommendation breakdown → | Wei Wei, Xubin Ren et al. | 87 | |
| 12 | GraphGPT: Graph Instruction Tuning for Large Language Models breakdown → | Jiabin Tang, Yuhao Yang et al. | 57 | |
| 13 | AgentIR: 1st Workshop on Agent-based Information Retrieval | Rare & Special e-Zone (The Hong Kong University of Science and Technology) | Qingpeng Cai, Xiangyu Zhao et al. | 1 |
| 14 | Representation Learning with Large Language Models for Recommendation breakdown → | The HKU Scholars Hub (University of Hong Kong) | Xubin Ren, Wei Wei et al. | 69 |
| 15 | Unsupervised Large Language Model Alignment for Information Retrieval via Contrastive Feedback | Yiding Liu, Qingyao Ai et al. | 2 | |
| 16 | Toward Bias-Agnostic Recommender Systems: A Universal Generative Framework | ACM Transactions on Information Systems | Lixin Zou, Chenliang Li et al. | 4 |
| 17 | I3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval | Yiding Liu, Qingyao Ai et al. | 3 | |
| 18 | Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation | IEEE Transactions on Knowledge and Data Engineering | Xixun Lin, Chuan Zhou et al. | 8 |
| 19 | Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks | Chao Huang, Jiashu Zhao et al. | 3 | |
| 20 | A Graph Neural Network Framework for Social Recommendations | IEEE Transactions on Knowledge and Data Engineering | Wenqi Fan, Yao Ma et al. | 142 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.