Jianghao Lin (林江浩)

Jianghao Lin (林江浩)

Senior student at SJTU

About me

I am a PhD student at Shanghai Jiao Tong University, China. I am now pursuing PhD Degree at APEX lab, advised by Prof. Weinan Zhang and Prof. Yong Yu. I am also the member of Zhiyuan Honors Program (致远荣誉计划) during my stage of undergraduate. I am now a member of Wu Wen Jun Honorary Doctoral Program (吴文俊荣誉博士班), advised by Prof. Cewu Lu.

My research interests include machine learning and data mining, especially, deep learning, reinforcement learning and their applications in real-world data mining scenarios including recommender system and information retrieval.

I am also wrting weekly paper notes about latest LLM-enhanced RS at WeChat. Welcome to follow by scanning the QR-Code.

Email: chiangel [DOT] ljh [AT] gmail [DOT] com

Recent News

  • Aug., 2024. Our paper Mamba4Rec wins the best paper award at RelKD-KDD 2024.
  • Jul., 2024. Two papers were accepted by RecSys 2024
  • Jul., 2024. Five papers were accepted by CIKM 2024 (Accept Rate: 23.0%)
  • Jun., 2024. Our survey paper about LLM-enhanced RS was accepted by TOIS (CCF A).
  • Jun., 2024. Two papers were accepted by Frontiers of Computer Science (CCF-B)
  • May., 2024. One paper was accepted by KDD 2024 (Accept Rate: 20.0%)
  • Jan., 2024. Three papers were accepted by WWW 2024 (Accept Rate: 20.2%)
  • Sep., 2023. Our paper KAR wins the best paper award at DLP-RecSys 2023.
  • Jun., 2023. We release our survey paper and awesome GitHub repo for LLM-enhanced RS.
  • May, 2023. One paper was accepted by KDD 2023 (Accept Rate: 22.1%).

Education

YearEducation
09.2021-presentPhD student, Computer Science and Technology, Shanghai Jiao Tong University, China.
09.2017-06.2021B.S., Software Engineering, Shanghai Jiao Tong University, China.

Selected Publications

LLM-enhanced Recommendation

How Can Recommender Systems Benefit from Large Language Models: A Survey
Jianghao Lin, Xinyi Dai, Yunjia Xi, Weiwen Liu, Bo Chen, Hao Zhang, Yong Liu, Chuhan Wu, Xiangyang Li, Chenxu Zhu, Huifeng Guo, Yong Yu, Ruiming Tang, Weinan Zhang.
ACM Transactions on Information Systems (TOIS) 2024. Paper. Repo.
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
Yunjia Xi, Weiwen Liu, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu.
CIKM 2024. Paper.
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation
Jizheng Chen, Kounianhua Du, Jianghao Lin, Bo Chen, Ruiming Tang, Weinan Zhang.
CIKM 2024. Paper.
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang.
KDD 2024 (Full, Oral). Paper. Code.
Towards Efficient and Effective Unlearning of Large Language Models for Recommendation
Hangyu Wang*, Jianghao Lin*, Bo Chen, Yang Yang, Ruiming Tang, Weinan Zhang, Yong Yu.
Frontiers of Computer Science 2024 (CCF-B). Co-first Author. Paper. Code.
Large Language Models Make Sample-Efficient Recommender Systems
Jianghao Lin, Xinyi Dai, Rong Shan, Bo Chen, Ruiming Tang, Yong Yu, Weinan Zhang.
Frontiers of Computer Science 2024 (CCF-B). Paper.
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang.
WWW 2024 (Full, Oral). Paper Code v1 Code v2.
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang.
WWW 2024 (Full, Oral). Paper. Code.
FLIP: Towards Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
Hangyu Wang*, Jianghao Lin*, Xiangyang Li, Bo Chen, Chenxu Zhu, Ruiming Tang, Weinan Zhang, Yong Yu.
RecSys 2024. Co-first Author. Paper.
Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models
Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu.
RecSys 2024. DLP-RecSys 2023 (Best Paper Award). Paper. Code.

General Personalized Recommendation

A Comprehensive Survey on Retrieval Methods in Recommender Systems
Junjie Huang, Jizheng Chen, Jianghao Lin, Jiarui Qin, Ziming Feng, Weinan Zhang, Yong Yu.
Arxiv Preprint. Paper.
Retrieval-Oriented Knowledge for Click-Through Rate Prediction
Huanshuo Liu, Bo Chen, Menghui Zhu, Jianghao Lin, Jiarui Qin, Yang Yang, Hao Zhang, Ruiming Tang.
CIKM 2024. Paper.
Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation
Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, James Caverlee.
CIKM 2024. Paper. Code
Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models
Chengkai Liu, Jianghao Lin, Hanzhou Liu, Jianling Wang, James Caverlee.
RelKD@KDD 2024 (Best Paper Award). Paper. Code.
Invariant Graph Contrastive Learning for Mitigating Neighborhood Bias in Graph Neural Network based Recommender Systems
Zhenyu Mu, Jianghao Lin, Xiaoyu Zhu, Weinan Zhang, Yong Yu.
ICANN 2024 (Full, Oral). [Paper].
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
Jiachen Zhu, Yichao Wang, Jianghao Lin, Jiarui Qin, Ruiming Tang, Weinan Zhang, Yong Yu.
WWW 2024 (Full, Poster). Paper.
MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction
Jianghao Lin, Yanru Qu, Wei Guo, Xinyi Dai, Ruiming Tang, Yong Yu, Weinan Zhang.
KDD 2023 (Full, Oral). Paper. Code.
A Bird’s-eye View of Reranking: from List Level to Page Level
Yunjia Xi*, Jianghao Lin*, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu.
WSDM 2023 (Full, Poster). Co-first Author. Paper. Code.

User Click Models

Adversarially Trained Environment Models Are Effective Policy Evaluators and Improvers - An Application to Information Retrieval
Yao Li, Yifan Liu, Xinyi Dai, Jianghao Lin, Hang Lai, Yunfei Liu, Yong Yu.
DAI 2023 (Full, Oral). Paper.
An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages
Lingyue Fu*, Jianghao Lin*, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu.
WSDM 2023 (Full, Poster). Co-first Author. Paper. Code.
A Graph-Enhanced Click Model for Web Search
Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Shuai Li, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu.
SIGIR 2021 (Full, Oral). Paper. Code.
An Adversarial Imitation Click Model for Information Retrieval
Xinyi Dai, Jianghao Lin, Weinan Zhang, Shuai Li, Weiwen Liu, Ruiming Tang, Xiuqiang He, Jianye Hao, Jun Wang, Yong Yu.
WWW 2021 (Full, Oral). Paper. Code.

Academic Services

  • Conference Review: KDD, WWW, WSDM, CIKM
  • Journal Review: TKDE, TOIS, TORS, TCYB, Frontier of Computer Science (FCS), Nature Science Report, Journal of Intelligent & Fuzzy Systems

Internships

  • Huawei Noah’s Ark Lab
    • Research Intern, Search & Recommendation Group, supervised by Ruiming Tang.
    • Shenzhen, China.  Jul. 2020 - Jan. 2021
    • Focus on user modeling and click models. Two paper accepted by WWW 2021 and SIGIR 2021.

Competition

  • [2020.] Outstanding Winner (Top 0.14%), MCM/ICM 2020 (certificate).
  • [2019.] National Second Prize, CUMCM 2019 (certificate).

Honor and Awards

  • [2024.] National Scholarship for Graduate Student
  • [2024.] Best Paper Award at RelKD-KDD 2024
  • [2023.] Best Paper Award at DLP-RecSys 2023
  • [2021.] National Scholarship for Graduate Student
  • [2021.] Shanghai Outstanding Undergraduate
  • [2020.] Tang Lixin Scholarship (certificate).
  • [2020.] National Scholarship for Undergraduate Student
  • [2018.] National Scholarship for Undergraduate Student (certificate).

More

My hobbies mainly focus on animation and online games.