5 papers
Layer-wise Representation Dynamics: An Empirical Investigation Across Embedders and Base LLMs
Jingzhou Jiang, Yi Yang, Kar Yan Tam
Hidden states change substantially across the layers of modern language models, but most layer-wise analyses focus on one aspect of that change. We propose Layer-wise Representatio…
FLARE: Task-agnostic embedding model evaluation through a normalization process
Jingzhou Jiang, Yixuan Tang, Yi Yang +1
When task-specific labels are not available, it becomes difficult to select an embedding model for a specific target corpus. Existing labelless measures based on kernel estimators…
Robust Predictive Modeling Under Unseen Data Distribution Shifts: A Methodological Commentary
Hanyu Duan, Yi Yang, Ahmed Abbasi +1
Most research designing novel predictive models, or employing existing ones, assumes that training and testing data are independent and identically distributed. In practice, the da…
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness
Hanyu Duan, Yi Yang, Ahmed Abbasi +1
Machine unlearning is the process of removing the imprint left by specific data samples during the training of a machine learning model. AI developers, including those building per…
Evaluating and Aligning Human Economic Risk Preferences in LLMs
Jiaxin Liu, Yixuan Tang, Yi Yang +1
Large Language Models (LLMs) are increasingly used in decision-making scenarios that involve risk assessment, yet their alignment with human economic rationality remains unclear. I…