2025
January
|
CODEXGRAPH: Bridging Large Language Models and Code Repositories via Code Graph Databases
Xiangyan Liu*, Bo Lan*, Zhiyuan Hu, Yang Liu, Zhicheng Zhang, Fei Wang, Michael Qizhe Shieh, and Wenmeng Zhou
NAACL 2025
|
2025
January
|
MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures
Jinjie Ni, Yiran Song, Yuxi Xie, Deepanway Ghosal, Bo Li, David Junhao Zhang, Xiang Yue, Fuzhao Xue, Zian Zheng, Kaichen Zhang, Mahir Shah, Kabir Jain, Yang You, and Michael Qizhe Shieh
ICLR 2025 (Spotlight)
|
2025
January
|
Identifying and Tuning Safety Neurons in Large Language Models
Yiran Zhao, Wenxuan Zhang, Yuxi Xie, Anirudh Goyal, Kenji Kawaguchi, and Michael Qizhe Shieh
ICLR 2025
|
2025
January
|
LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization
Guanzheng Chen, Xin Li, Michael Qizhe Shieh, and Lidong Bing
ICLR 2025
|
2024
December
|
Single Character Perturbations Break LLM Alignment
Leon Lin*, Hannah Brown*, Kenji Kawaguchi, and Michael Shieh
AAAI 2025
|
2024
September
|
Accelerating greedy coordinate gradient via probe sampling
Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, and Michael Qizhe Shieh
NeurIPS 2024
|
2024
September
|
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning
Yuxi Xie, Anirudh Goyal, Wenyue Zheng, Min-Yen Kan, Timothy P Lillicrap, Kenji Kawaguchi, and Michael Shieh
NeurIPS 2024 Workshop
|
2024
September
|
Advancing Adversarial Suffix Transfer Learning on Aligned Large Language Models
Hongfu Liu*, Yuxi Xie*, Ye Wang, and Michael Shieh
EMNLP 2024
|
2024
September
|
Reasoning Robustness of LLMs to Adversarial Typographical Errors
Esther Gan*, Yiran Zhao*, Liying Cheng, Yancan Mao, Anirudh Goyal, Kenji Kawaguchi, Min-Yen Kan, and Michael Shieh
EMNLP 2024
|
2024
May
|
Instructcoder: Instruction tuning large language models for code editing
Kaixin Li*, Qisheng Hu*, James Zhao, Hui Chen, Yuxi Xie, Tiedong Liu, Michael Shieh†, and Junxian He†
ACL 2024 Workshop
|
2024
May
|
Prompt optimization via adversarial in-context learning
Xuan Long Do*, Yiran Zhao*, Hannah Brown*, Yuxi Xie, James Xu Zhao, Nancy F. Chen, Kenji Kawaguchi, Michael Shieh†, and Junxian He†
ACL 2024 (Oral)
|
2023
October
|
Self-evaluation guided beam search for reasoning
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, James Xu Zhao, Min-Yen Kan†, Junxian He†, and Michael Xie†
NeurIPS 2023
|
2023
October
|
Automatic model selection with large language models for reasoning
James Xu Zhao, Yuxi Xie, Kenji Kawaguchi, Junxian He, and Michael Qizhe Xie
EMNLP 2023 Findings
|
2023
May
|
Multi-Source Test-Time Adaptation as Dueling Bandits for Extractive Question Answering
Hai Ye, Qizhe Xie, and Hwee Tou Ng
ACL 2023
|
2021
February
|
Meta pseudo labels
Hieu Pham, Zihang Dai, Qizhe Xie, and Quoc V. Le
CVPR 2021
|
2020
October
|
Unsupervised data augmentation for consistency training
Qizhe Xie, Zihang Dai, Eduard Hovy, Thang Luong, and Quoc V. Le
NeurIPS 2020
|
2020
February
|
Self-training with noisy student improves imagenet classification
Qizhe Xie, Minh-Thang Luong, Eduard Hovy, and Quoc V. Le
CVPR 2020
|
2017
November
|
RACE: Large-scale ReAding Comprehension Dataset From Examinations
Guokun Lai*, Qizhe Xie*, Hanxiao Liu, Yiming Yang, and Eduard Hovy
EMNLP 2017
|