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 efficient and generative techniques for LLMs.
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] SoftCoT++: Test-Time Scaling with Soft Chain-of-Thought Reasoning
Yige Xu*, Xu Guo*, Zhiwei Zeng, Chunyan Miao . [Paper][Code]
Publications 📖
- SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs.
Yige Xu*, Xu Guo*, Zhiwei Zeng, Chunyan Miao
ACL, 2025 [Paper][Code][Data] - Diffusion-Guided Diversity for Single Domain Generalization in Time Series Classification
Junru Zhang, Lang Feng, Xu Guo, Han Yu, Yabo Dong, Duanqing Xu
KDD, 2025 - RevMUX: Data Multiplexing with Reversible Adapters for Efficient LLM Batch Inference
Yige Xu, Xu Guo, Zhiwei Zeng, Chunyan Miao
EMNLP, 2024 [Lecture][Paper][Code] - A Survey on Natural Language Counterfactual Generation
Yongjie Wang*, Xiaoqi Qiu*, Yue Yu, Xu Guo, Zhiwei Zeng, Yuhong Feng, Zhiqi Shen.
EMNLP Findings, 2024 [Paper] - Generating Synthetic Datasets for Few-shot Prompt Tuning
Xu Guo, Zilin Du, Boyang Li, Chunyan Miao
COLM, 2024 [Poster][Paper] - PairCFR: Enhancing Model Training on Paired Counterfactually Augmented Data through Contrastive Learning
Xiaoqi Qiu*, Yongjie Wang*, Xu Guo, Zhiwei Zeng, Yue Yu, Yuhong Feng, and Chunyan Miao
ACL, 2024 [Lecture][Paper][Code] - InteMATs: Integrating Granularity-Specific Multilingual Adapters for Cross-Lingual Transfer
Meizhen Liu, Xu Guo, Jiakai He, Jianye Chen, Fengyu Zhou, and Siu Hui
EMNLP Findings, 2023 [Paper] - GranCATs: Cross-Lingual Enhancement through Granularity-Specific Contrastive Adapters
Meizhen Liu, Jiakai He, Xu Guo, Jianye Chen, Siu Cheung Hui, and Fengyu Zhou
CIKM, 2023 [Paper][Code] - Training Multimedia Event Extraction With Generated Images and Captions
Zilin Du, Yunxin Li, Xu Guo, Yidan Sun, and Boyang Li
ACM MM, 2023 [Paper][Code] - Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation
Xu Guo, Boyang Li, Han Yu
EMNLP Findings, 2022 [Lecture][Paper][Code] - Federated learning for personalized humor recognition
Xu Guo, Han Yu, Boyang Li, Hao Wang, Pengwei Xing, Siwei Feng, Zaiqing Nie, and Chunyan Miao
ACM TIST, 2022 [Paper] - Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection
Xu Guo, Boyang Li, Han Yu, Chunyan Miao
NAACL, 2021 [Lecture][Paper][Code]
Honors and Awards 🏆
- Wallenberg-NTU Presidential Postdoctoral Fellowship. 2023
- WiEST Development Grant. Women in Engineering, Science, and Technology, NTU. 2023
- Best Presentation Award. Pattern Recognition and Machine Intelligence Association. 2021
- Best Application Paper Award. International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with IJCAI 2020
- Student Travel Grant. Awarded by IJCAI. 2019
- NTU Research Scholarship. NTU, Singapore. 2019