Large Language Models

Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
Fairer Preferences Elicit Improved Human-Aligned Large Language Model Judgments
Han Zhou, Xingchen Wan, Yinhong Liu, Nigel Collier, Ivan Vulić, Anna Korhonen
Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators
Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators.
Yinhong Liu, Han Zhou, Zhijiang Guo, Ehsan Shareghi, Ivan Vulić, Anna Korhonen, Nigel Collier
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Mitigating prompt biases and unifying existing calibration approaches without labeled data.
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.
Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen
AutoPEFT: Automatic Configuration Search for Parameter-Efficient Fine-Tuning
Can Large Language Models Achieve Calibration with In-Context Learning?
Can Large Language Models Achieve Calibration with In-Context Learning?
Chengzu Li, Han Zhou, Goran Glavaš, Anna Korhonen, Ivan Vulić
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
Efficient prompt optimization via influential search space pruning.
Han Zhou, Xingchen Wan, Ivan Vulić, Anna Korhonen
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and Pruning
A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems
A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems
Songbo Hu, Han Zhou, Zhangdie Yuan, Milan Gritta, Guchun Zhang, Ignacio Iacobacci, Anna Korhonen, Ivan Vulić