Song Jiang

songjiang (at) cs (dot) ucla (dot) edu

About Me

• I'm a final-year Ph.D. Candidate at Computer Science Department, University of California, Los Angeles (UCLA). My advisor is Prof. Yizhou Sun. Prior to UCLA, I got my Master of Engineering degree from Tsinghua University, and Bachelor of Engineering degree from Shandong University.

• I have broad interests in machine learning, large language models, graphs, and causality.

Publication

Conferences

• ResPrompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models
  

  • Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, Asli Celikyilmaz
    

  • NAACL 2024, Mexico City, Mexico
    

  • [Arxiv]

• LLM-Rec: Personalized Recommendation via Prompting Large Language Models
  

  • Hanjia Lyu, Song Jiang, Hanqing Zeng, Qifan Wang, Si Zhang, Ren Chen, Chris Leung, Jiajie Tang, Yinglong Xia, Jiebo Luo
    

  • NAACL 2024 - Findings, Mexico City, Mexico
    

  • [Arxiv]

• CARE: Modeling Interacting Dynamics Under Temporal Distribution Shift
  

  • Xiao Luo, Haixin Wang, Zijie Huang, Huiyu Jiang, Abhijeet Sadashiv Gangan, Song Jiang, Yizhou Sun
    

  • NeurIPS 2023, New Orleans, LA
    

  • [Paper]

• CF-GODE: Continuous-Time Causal Inference for Multi-Agent Dynamical Systems
  

  • Song Jiang, Zijie Huang, Xiao Luo and Yizhou Sun
    

  • KDD 2023, Long Beach, CA
    

  • [Paper] [Code]

• A Single Vector Is Not Enough: Taxonomy Expansion via Box Embeddings
  

  • Song Jiang, Qiyue Yao, Qifan Wang and Yizhou Sun
    

  • WWW 2023, Austin, TX
    

  • Best Student Paper Award
    

  • [Paper] [Code]

• Deep Learning of Potential Outcomes
  

  • Bernard Koch, Tim Sainburg, Pablo Geraldo, Song Jiang, Yizhou Sun, and Jacob Gates Foster
    

  • Sociological Methods & Research (Journal) 2023
    

  • [Paper]

• Estimating Causal Effects on Networked Observational Data via Representation Learning
  

  • Song Jiang and Yizhou Sun
    

  • CIKM 2022, Atlanta, GA
    

  • [Paper] [Code]

• Bridging Self-Attention and Time Series Decomposition for Periodic Forecasting
  

  • Song Jiang, Tahin Syed, Xuan Zhu, Joshua Levy, Boris Aronchik and Yizhou Sun
    

  • CIKM 2022, Atlanta, GA
    

  • [Paper] [Code]

• HINTS: Citation Time Series Prediction for New Publications via Dynamic Heterogeneous Information Network Embedding
  

  • Song Jiang, Bernard Koch and Yizhou Sun
    

  • WWW 2021, virtual
    

  • [Paper] [Code]

• Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
  

  • Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun and Quanquan Gu
    

  • NeurIPS 2019, Vancouver, Canada
    

  • [Paper]

Workshops and Preprints

• Reducing Communication Overhead in Distributed GNN Training via Client-Server Knowledge Distillation
  

  • Song Jiang, Xiaotian Han, Yinglong Xia, Qifan Wang, Yizhou Sun
    

  • Preprint 2023
    

  • [Arxiv]

• On the Equivalence of Graph Convolution and Mixup
  

  • Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu
    

  • Preprint 2023
    

  • [Arxiv]

• Unit Selection: Learning Benefit Function from Finite Population Data
  

  • Ang Li, Song Jiang, Yizhou Sun and Judea Pearl
    

  • NeurIPS 2022 Workshop on Causality for Real-world Impact
    

  • [Arxiv]

• Learning probabilities of causation from finite population data
  

  • Ang Li, Song Jiang, Yizhou Sun and Judea Pearl
    

  • Preprint 2022
    

  • [Arxiv]

Industry Experience

• Meta AI, Research intern
  

  • Menlo Park, CA,  Jun 2023 - Sept 2023
  
  

• Meta AI, Research intern
  

  • Menlo Park, CA,  Jun 2022 - Sept 2022
  
  

• Amazon Web Services (AWS), Applied scientist intern
  

  • Boston, MA (Remote),  Jun 2021 - Sept 2021
  
  

• Snap Inc., Research intern
  

  • Santa Monica, CA (Remote),  Jun 2020 - Aug 2020

Education

• Ph.D. University of California, Los Angeles (UCLA),  2018 - now
  

• M.E.    Tsinghua University,     2015 - 2018
  

• B.E.      Shandong University,  2011 - 2015
  

Services

• PC member / reviewer:

  • Conference:
    • Machine Learning: ICLR 2024, NeurIPS 2023, ICML 2023-2024, AISTATS 2024;
    • Natural Language Processing: EMNLP 2023;
    • Data Mining: KDD 2023 2020, WWW 2023-2024, WSDM 2024, CIKM 2022-2023, ECML-PKDD 2020-2023, SDM 2024;
    • Misc: AAAI 2023-2024, ICWSM 2023-2024, ICASSP 2023, IJCAI 2021-2023, LoG 2022-2023.
  
  
  • Journal:
    • TPAMI, TMLR, TNNLS, TKDE, TKDD, Neurocomputing, TBD.
      
      

• Session Chair:

  • WWW 2023
  
  
  
  

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