This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation (Xu et al., ICML 2024), that I read and studied. [Read More]

This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled Beyond One-Prefernce-Fits-All Alignment: Multi-Objective Direct Preference Optimization (Zhou et al., arXiv 2023), that I read and studied. [Read More]

This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled What Makse Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning (Liu et al., ICLR 2024), that I... [Read More]

This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled Chat Vector: A Simple Approach to Equip LLMs with Instruction Following and Model Alignment in New Languages (Huang et al., arXiv 2024) ,... [Read More]

This post is a brief summary about the paper that I read for my study and curiosity, so I shortly arrange the content of the paper, titled ORPO: Monolithic Preference Optimization without Reference Model (Hong et al., arXiv 2024), that I read and studied. [Read More]