Natural Language Processing

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments

Han Zhou, Xingchen Wan, Yinhong Liu, Nigel Collier, Ivan Vulić, Anna Korhonen

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

Mitigating prompt biases and unifying existing calibration approaches without labeled data (ICLR 2024)

Han Zhou, Xingchen Wan, Lev Proleev, Diana Mincu, Jilin Chen, Katherine Heller, Subhrajit Roy

Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering

AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning

Automatic discovery of families of high-performing PEFT configurations (TACL 2024)

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen

Universal Self-Adaptive Prompting

Empirical Methods in Natural Language Processing (EMNLP), 2023

Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arık, Tomas Pfister

Universal Self-Adaptive Prompting

Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning

Orders-of-magnitude faster hard prompt search with SoTA performance (EMNLP Findings 2023)

Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen

Better Zero-Shot Reasoning with Self-Adaptive Prompting

Findings of the Association for Computational Linguistics: ACL 2023

Xingchen Wan, Ruoxi Sun, Hanjun Dai, Sercan Ö. Arık, Tomas Pfister

Better Zero-Shot Reasoning with Self-Adaptive Prompting

Sentiment Correlation in Financial News Networks and Associated Market Movements

Scientific Reports 11.

Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong