News


13th Oct2023
Our RA Yongxin gave a talk to Google DeepMind introducing our recent work. ID vs. Modality and Large Micro-Video Recsys Datasets!


20 Apr2018
A full paper about word embedding was accepted by ACL2018, equal contribution with Xinxin.

16 Apr2018
A full paper Approximating Word Ranking and Negative Sampling for Word Embedding was accepted by IJCAI2018, equal contribution with Guibing Guo and Shichang Ouyang.

10 Dec 2016
A full paper Boosted Factorization Machines for top-N Feature-based Recommendations was accepted by ACM IUI2017.

7 Nov. 2016
We won the Best Studeng Paper Award (5/157) in ICTAI16 after the presentation of our work.

29 Oct. 2016
I am travelling to San Jose for ICTAI16 and will present our work GeoBPR.

24 Oct. 2016
I am travelling to Indianapolis for CIKM16 and will present our work LambdaFM.

27 Sep. 2016
I am invited to be the reviewer of European Conference on Information Retrieval (ECIR 2017).

24 Aug. 2016
Our work Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation is accepted by ICTAI as a full paper.

14 July 2016
Our work LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates is accepted by CIKM as a full paper.

31 Aug. 2015
I am travelling to thessaloniki,Greece for The European Summer School in Information Retrieval (ESSIR 2015) .

Copyright@Webpage template is from Weinan Zhang.

Fajie Yuan 

Assistant Professor

AI division, Westlake University

Hangzhou, China

Email: yuanfajie[AT]westlake.edu.cn

Before joining Westlake University, Fajie was a senior AI researcher at Tencent, working on recommender systems and AI foundation models. He obtained his Ph.D. degree at University of Glasgow, advised by Prof. Joemon Jose in 2018. Between 2017 and 2018, He was also a visiting scholar at National University of Singapore, supported by Jim Gatheral Travel Scholarship, and research intern at Telefonic Research in Barcelona, mentored by Dr. Alexandros Karatzoglou and Dr. Ioannis Arapakis. He has published over 30 research papers in premier AI conferences as the first/co-first/corresponding author. Several of his AI algorithms were applied in real-world large-scale production systems, such as LambdaFM (CIKM2016), NextItNet (WSDM2019), and PeterRec (SIGIR2020). At Westlake, he worked as an independent PI, focusing on two major research directions: AI+Life Science and deep learning (for recommender systems) He often works as reviewers for premier AI conferences and bioinfomatics journals, such as NeurIPS, SIGIR, KDD, WSDM, CIKM, WWW, Recsys etc. His lab is now recruiting self-motivated interns / full-time (posdoc/assistant/associate) researchers/ PHD students in machine learning and Life AI. 西湖大学原发杰团队长期招聘:推荐系统和生物信息(尤其蛋白质相关)方向 ,科研助理,博士生 (2024年4月份招生仍有1个PHD名额),博后,访问学者,助理研究员系列。 可以提前联系我,如果你想要申请我的PHD! He is also open to various collaborations. If you are interested in, please drop an email.

Talk

One Model for ALL Recsys (SIGIR2021)
Learning Universal User Representations in Recommender Systems
Paradigm for Pre-training and Transfer Learning in Recommender Systems
ID vs. Multimodal Recsys (SIGIR2023 by Yuan Zheng)
A Content-Driven Micro-Video Recommendation Dataset at Scale (Invited Talk to DeepMind (by Yongxin))

Large-scale Recommendation DataSets

Transfer Learning Recommendation Dataset (see our PeterRec(SIGIR2020) or Conure (SIGIR2021) for descriptions)
Sequential Recommendation Dataset (see our StackRec(SIGIR2021) Github)
Tenrec Dataset (see our NeurIPS2022 Github)
PixelRec Dataset
NineRec (see our TPAMI2024 Github) Dataset
MicroLens (Invited Talk by DeepMind) Dataset

Selected Publications [Google Scholar] [Github]


pdf
SaprotHub: Making Protein Modeling Accessible to All Biologists
J. Su, Z. Li, C. Han, Y. Zhou, J. Shan, X. Zhou, T. OPMC, S. Ovchinnikov, F. Yuan#
Preprint.   Codes    blog

pdf
Toward De Novo Protein Design from Natural Language
F. Dai, Y. Fan, J. Su, C. Wang, ..., F. Yuan#
Preprint.   Code (soon)   

pdf
ProTrek: Navigating the Protein Universe through Tri-Modal Contrastive Learning
J. Su, X. Zhou, X. Zhang, F. Yuan#
Preprint.   Codes    blog

pdf
SaProt: Protein Language Modeling with Structure-aware Vocabulary
J. Su, C. Han, Y. Zhou, J. Shan, X. Zhou, F. Yuan# 650M的蛋白质结构预训练大模型
ICLR2024 spotlight (top5%)   Codes    ranked first on Proteingym leaderboard

pdf
Protein language models-assisted engineering of Uracil-N glycosylase enables programmable T-to-G and T-to-C base editing
Y. He, X. Zhou, C. Chang, G. Chen, W. Liu, G. Li, X. Fan, Y. Ma, F. Yuan# , X. Chang#
Molecular Cell (Impact factor:19.3)   Code   STAR Protocols   

pdf
Generative Diffusion Models for Antibody Design, Docking, and Optimization
Z. Peng, C. Han, X. Wang, J. Shan, D. Li#, F. Yuan# Diffusion 模型抗体设计和优化
Preprint.   Codes   

pdf
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
Y. Cheng, Y. Pan, J. Zhang, Y. Ni, F. Yuan# 最大的信息流媒体封面图像推荐系统数据集
SDM (2024)   Codes   

pdf
NineRec: A Benchmark Dataset Suite for Evaluating Transferable Recommendation
J. Zhang, Y. Cheng, Y. Ni, Y. Pan, F. Yuan# 最多样的多模态推荐系统数据集用于迁移学习研究
TPAMI2024 (Impact factor:24.3)   Codes   

pdf
A Content-Driven Micro-Video Recommendation Dataset at Scale
Y. Ni, Y. Cheng, X. Liu, J. Fu, Y. Li, X. He, Y. Zhang F. Yuan# 首套大规模微视频推荐系统数据集,含有原始视频
Invited Talk (Google DeepMind)   Codes   

pdf
Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insights
R. Li, W. Deng, Yu. Cheng, Z. Yuan, J. Zhang, F. Yuan# . ID vs. GPT-3, 175B的GPT-3能否打败最简单的ID?
Preprint.   Codes (Soon)   

pdf
TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback
J. Wang, F. Yuan# , M. Cheng, etc. 首次提出采用混合模态用户反馈实现推荐系统预训练与可迁移性。
Preprint.   Codes (Soon)   

pdf
Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors
B. Geng, Z. Huang, X. Zhang, Y. He, L. Zhang, F. Yuan , J. Zhou, L. Ma.
SIGIR(short)2024   Codes (Soon)   

pdf
Multi-Modality is All You Need for Transferable Recommender Systems
Y. Li*, H, Du, Y Ni, P. Zhao, Q. Guo#, F. Yuan# , X. Zhou, etc. 多模态推荐系统迁移学习研究
ICDE2024   Codes   

pdf
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights
J. Fu, F. Yuan# , Y. Song, Z. Yuan, M. Cheng, etc. 系统研究Adapter对于推荐系统迁移学习的影响
WSDM2024   Codes   

pdf
Where to Go Next for Recommender Systems? ID- vs.Modality-based recommender models revisited
Z. Yuan*, F. Yuan* (co-first authors) , Y. Song, etc. 推荐系统何去何从,ID是否有望继续主导推荐系统社区?
SIGIR2023 (CORE rank A*)   Codes   

pdf
Tenrec: A Large-scale Multipurpose Benchmark Dataset for Recommender Systems
G. Yuan*, F. Yuan* (co-first authors) , B. Kong, etc. 一个大规模的推荐系统数据集,覆盖10个任务。
NeurlPS2022 (CORE rank A*)   Codes   

pdf
Ultra-Accurate Classification and Discovery of Functional Protein-Coding Genes from Microbiomes Using FunGeneTyper: An Expandable Deep Learning-Based Framework
G. Zhang*, H. Wang* ,..., F. Yuan# , F. Ju#
preprint   Codes (soon)   

pdf
Exploring evolution-based & -free protein language models as protein function predictors
M. Hu*, F. Yuan* (co-first authors) , K. Yang, etc. 首次探究AlphaFold's Evoformer蛋白质功能预测能力。
NeurlPS2022 (CORE rank A*)   Codes   

pdf
Protein Language Model Predicts Mutation Pathogenicity and Clinical Prognosis
X Liu, X Yang, L Ouyang, G Guo, J Su, R Xi*, K Yuan*, F. Yuan# 首次发现蛋白质语言模型具有预测基因突变致癌性和临床生存期。
NeurlPS2022 LMRL workshop   Codes (soon)   

pdf
Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search
L. Chen, F. Yuan , J. Yang, M. Yang, C. Li
Preprint.   Codes (Soon)   

pdf
Enhancing Top-N Item Recommendations by Peer Collaboration
Y. Sun*, F. Yuan* (co-first authors), M. Yang, A. Karatzoglou, L.Shen, x. Zhao
SIGIR2022 (short).   Codes   

pdf
User-specific Adaptive Fine-tuning for Cross-domain Recommendations
L. Chen*, F. Yuan* (co-first authors), J. Yang, X. He, C. Li, M. Yang
TKDE 2021 (CORE rank A*).   Codes (Soon)   

pdf
CmnRec: Sequential Recommendations with Chunk-accelerated Memory Network
S. Qu*, F. Yuan* (co-first authors), G. Guo, L. Zhang, W. Wei
TKDE 2021 (CORE rank A*).   Codes   

pdf
One Person, One Model, One World: Learning Continual User Representation without Forgetting
F. Yuan, G. Zhang, A. Karatzoglou, J. Jose, etc. 首次提出通用用户表征终生学习问题。
SIGIR 2021 (Accept rate: 21%) (CORE rank A*).   Codes   Slide

pdf
StackRec: Efficient Training of Very Deep Sequential Recommender Models by Layer Stacking
J. Wang*, F. Yuan* (co-first authors), J. Chen, Q. Wu, C. Li, M. Yang, Y. Sun, G. Zhang
SIGIR 2021 (Accept rate: 21%) (CORE rank A*).   Codes   

pdf
Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement
M. Cheng*, F. Yuan* (co-first authors), Q. Liu, S. Ge, Z. Li, R. Yu, D. Lian, S. Yuan, En, Chen
SIGIR 2021 (Accept rate: 21%) (CORE rank A*).   Codes (Soon)   

pdf
Iterative Pruning with Adaptive Regularization for Lifelong Sentiment Classification
B. Geng, M, Yang, F. Yuan , S. Wang, X. Ao, R. Xu
SIGIR 2021 (Accept rate: 21%) (CORE rank A*).   Codes   

pdf
Learning Transferable User Representations with Sequential Behaviors via Contrastive Pre-training
M. Cheng*, F. Yuan* (co-first authors), Q. Liu, S. Ge, X. Xin, En, Chen
ICDM 2021 (Accept rate: 9.9%) (CORE rank A*).   Codes (Soon)   

pdf
SkipRec: A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models
L. Chen*, F. Yuan* (co-first authors), M. Yang, etc. 首次发现推荐系统可以加深到100层。
AAAI 2021 (Accept rate: 21%) (CORE rank A*).   Codes   Slide

pdf
Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking
B. Geng, F. Yuan , Q. Xu, Y. Shen, R. Xu, M, Yang,
ACL 2021 (Short Paper) (CORE rank A*).   Codes   

pdf
Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation
F. Yuan, X. He, A. Karatzoglou, etc. 首次发现自监督学习可以学到通用用户表征.
SIGIR 2020 (Accept rate: 26%) (CORE rank A*).   Codes   Slide    post

pdf
A Generic Network Compression Framework for Sequential Recommender Systems
Y. Sun*, F. Yuan* (co-first authors), M. Yang, G. Wei, Z. Zhao, D, Liu
SIGIR 2020 (Accept rate: 26%) (CORE rank A*).   Codes    post

pdf
Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation
F. Yuan, X. He, H.Jiang, G. Guo, J. Xiong, Z. Xu, Y. Xiong
WWW 2020 (Accept rate: 19%) (CORE rank A*).   Codes   Slide    post

pdf
VSE-fs: Fast Full-Sample Visual Semantic Embedding
S. Zhai, G. Guo, F. Yuan,Y. Liu, X. Wang
IEEE Intelligent Systems (CORE rank A).   

pdf
A Simple Convolutional Generative Network for Next Item Recommendation
F. Yuan, A. Karatzoglou, I. Arapakis, J. Jose, X. He. 首次应用空洞卷积于推荐系统。
WSDM 2019 (Accept rate: 16%) (CORE rank A*).   Codes    Slide    post

pdf
Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation
G. Guo, S. Ouyang, X. He, F. Yuan, X. Liu
IJCAI 2019.(Accept rate: 17.9%)(CORE rank A*).   Codes   post

pdf
Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering
X. Du, X. He, F. Yuan, J. Tang, Z. Qin, T. Chua
TOIS 2019 (CORE rank A)    Codes   

pdf
Adversarial Training Towards Robust Multimedia Recommender System
J. Tang, X. He, X. Du, F. Yuan, Q. Tian, T. Chua
TKDE 2019 (CORE rank A*).    Codes   

pdf
fBGD: Learning Embeddings From Positive Unlabeled Data with BGD
F. Yuan,X. Xin, X. He, G. Guo, W.Zhang, T. Chua, J. Jose
UAI 2018. (Accept rate: 30%)(CORE rank A*).   Codes    post

pdf
Batch IS NOT Heavy: Learning Word Representations From All Samples
X. Xin*, F. Yuan* (co-first authors), X. He, J. Jose
ACL 2018.(Accept rate: 24.8%)(CORE rank A*).   Codes   

pdf
Approximating Word Ranking and Negative Sampling for Word Embedding
G. Guo*, SC.Ouyang*,F. Yuan* (co-first authors)
IJCAI 2018.(Accept rate: 20.4%)(CORE rank A*).   Codes   

pdf
Improving Negative Sampling for Word Representation using Self-embedded Features
L. Chen*, F. Yuan*(co-first authors), J. Jose, W.Zhang
WSDM 2018.(Accept rate: 16%)(CORE rank A*).   

pdf
BoostFM: Boosted Factorization Machines for top-N Feature-based Recommendation
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang
ACM IUI 2017(Accept rate: 23%)(CORE rank A).   

pdf
A Semantic Graph-Based Approach for Mining Common Topics From Multiple Asynchronous Text Streams
L. Chen, J. Jose, H. Yu, F.Yuan
WWW 2017.   (Accept rate: 17%)(CORE rank A*).   

pdf
LTRo: Learning to Route Queries in Clustered P2P IR
R. Alkhawaldeh, J. Jose, Deepak P, F.Yuan
ECIR 2017 (short paper)(CORE rank B).   

pdf
A Concise Integer Linear Programming Formulation for Implicit Search Result Diversification
H. Yu, A. Jatowt, R. Blanco, H. Joho, J. Jose, L. Chen, F.Yuan
WSDM 2017. (Accept rate: 15.8%)(CORE rank A*).   

pdf
LambdaFM: Learning Optimal Ranking with Factorization Machines Using Lambda Surrogates
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang
CIKM 2016. (Accept rate: 17.6%) (CORE rank A)   Code   post   Applied in Tencent (腾讯) Recommender Systems.

pdf
Joint Geo-Spatial Preference and Pairwise Ranking for Point-of-Interest Recommendation
F. Yuan, J. Jose, G. Guo, L. Chen, H. Yu, R. Alkhawaldeh
ICTAI 2016.   (CORE rank B) (Best Student Paper Award)

pdf
Optimizing Factorization Machines for Top-N Context-aware Recommendations
F. Yuan, G. Guo, J. Jose, L. Chen, H. Yu, W.Zhang
WISE 2016 (CORE rank B).   

pdf
A Semantic Graph based Topic Model for Question Retrieval in Community Question Answering
L. Chen, J. Jose, H. Yu, F.Yuan, D.Zhang
WSDM 2016.   (Accept rate: 18.2%) (CORE rank A*)  

pdf
Probabilistic Topic Modelling with Semantic Graph
L. Chen, J. Jose, H. Yu, F.Yuan
ECIR 2016.   (Accept rate: 21%) (CORE rank B)  

pdf
A New Strategy of Storage and Retrieval for Massive Remote Sensing Data Based on Embedded Database Files
F. Yuan, W. Gao, X.Huang, F.Huang, T.Yu, Y.Zhu
International Journal of Advancements in Computing Technology 2012.