Ph.D. in NLP

Xu Guo

I am a Wallenberg-NTU Presidential Postdoctoral Fellow, starting from 2023. I am currently based at KTH, Sweden, working with Mikael Skoglund. I spent the first half of my fellowship at NTU, Singapore, where I worked with Miao Chun Yan. I received my Ph.D. from NTU in 2023, advised by Han Yu.

Research Interests

My research lies at the intersection of Machine Learning and Natural Language Processing, with a focus on efficiency and generative techniques.

Efficient/Low-Resource Methods for NLP

  • Data-efficient learning for downstream tasks
  • Lightweight model adaptation and training strategies
  • Fast and cost-effective inference techniques

Generation

  • Synthetic data generation for downstream tasks
  • Data augmentation via controlled generation
  • Generating auxiliary signals to support reasoning and learning

Preprints

[NEW] Yige Xu, Xu Guo, Zhiwei Zeng, Chunyan Miao. SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs. [Paper][Code]

Publications đź“–

[EMNLP’24] Yige Xu, Xu Guo, Zhiwei Zeng, Chunyan Miao. “RevMUX: Data Multiplexing with Reversible Adapters for Efficient LLM Batch Inference” (Long Paper) [Oral Talk][Paper][Code]

[EMNLP Findings’24] Yongjie Wang, Xiaoqi Qiu, Yue Yu, Xu Guo, Zhiwei Zeng, Yuhong Feng, Zhiqi Shen. “A Survey on Natural Language Counterfactual Generation” (Long Paper)[Paper]

[COLM’24] Xu Guo, Zilin Du, Boyang Li, Chunyan Miao. “Generating Synthetic Datasets for Few-shot Prompt Tuning” (Long Paper)[Poster][Paper]

[ACL’24] Xiaoqi Qiu*, Yongjie Wang*, Xu Guo, Zhiwei Zeng, Yue Yu, Yuhong Feng, and Chunyan Miao. “PairCFR: Enhancing Model Training on Paired Counterfactually Augmented Data through Contrastive Learning” (Long Paper)[Video][Paper][Code]

[EMNLP Findings’23] Meizhen Liu, Xu Guo, Jiakai He, Jianye Chen, Fengyu Zhou, and Siu Hui. “InteMATs: Integrating Granularity-Specific Multilingual Adapters for Cross-Lingual Transfer”. (Long Paper) [Paper]

[CIKM’23] Meizhen Liu, Jiakai He, Xu Guo, Jianye Chen, Siu Cheung Hui, and Fengyu Zhou. “GranCATs: Cross-Lingual Enhancement through Granularity-Specific Contrastive Adapters”. (Long Paper; Oral) [Paper][Code]

[ACM MM’23] Zilin Du, Yunxin Li, Xu Guo, Yidan Sun, and Boyang Li. “Training Multimedia Event Extraction With Generated Images and Captions”. (Long Paper) [Paper][Code]

[IJCNN’22] Fei Luo, Hangwei Qian, Di Wang, Xu Guo, Yan Sun, Eng Sing Lee, Hui Hwang Teong, Ray Tian Rui Lai, Chunyan Miao. “Missing value imputation for diabetes prediction”. (Long Paper) [Paper]

[EMNLP Findings’22] Xu Guo, Boyang Li, Han Yu. “Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation”. (Long Paper) [Video][Paper][Code]

[ACM TIST’22] Xu Guo, Han Yu, Boyang Li, Hao Wang, Pengwei Xing, Siwei Feng, Zaiqing Nie, and Chunyan Miao. “Federated learning for personalized humor recognition” (Long Paper) [Paper][FL-IJCAI Best Application Paper Award]

[NAACL’21] Xu Guo, Boyang Li, Han Yu, Chunyan Miao. “Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection” (Long Paper) [PREMIA Best Presentation Award] [Video][Paper][Code]

[IJCAI’19] Xu Guo, Han Yu, Chunyan Miao, and Yiqiang Chen. “Agent-based Decision Support for Pain Management in Primary Care Settings” (Demo Paper) [Video][Paper]

Honors and Awards 🏆

  • 2025 Wallenberg-NTU Presidential Postdoctoral Fellowship. WASP, Sweden. 300,000 SEK
  • 2023 Wallenberg-NTU Presidential Postdoctoral Fellowship. NTU, Singapore. 100,000 SGD
  • 2023 WiEST Development Grant. Awarded by Women in Engineering, Science, and Technology, NTU. 3,000 SGD
  • 2021 Best Presentation Award. Pattern Recognition and Machine Intelligence Association (PREMIA)
  • 2020 Best Application Paper Award. International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with IJCAI 2020 (FL-IJCAI’20)
  • 2019 Student Travel Grant. Awarded by IJCAI.
  • 2019 Full Research Scholarship. NTU, Singapore.