3 papers
cs.AI2025
Bayesian Principles Improve Prompt Learning In Vision-Language Models
Mingyu Kim, Jongwoo Ko, Mijung Park
Prompt learning is a popular fine-tuning method for vision-language models due to its efficiency. It requires a small number of additional learnable parameters while significantly…
cs.HC2025
Beyond correlation: The Impact of Human Uncertainty in Measuring the Effectiveness of Automatic Evaluation and LLM-as-a-Judge
Aparna Elangovan, Lei Xu, Jongwoo Ko +4
The effectiveness of automatic evaluation of generative models is typically measured by comparing the labels generated via automation with labels by humans using correlation metric…
cs.LG2024
SeRA: Self-Reviewing and Alignment of Large Language Models using Implicit Reward Margins
Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh +3
Direct alignment algorithms (DAAs), such as direct preference optimization (DPO), have become popular alternatives for Reinforcement Learning from Human Feedback (RLHF) due to thei…