ICML 2024 "supervised fine-tuning" Papers
7 papers found
Can AI Assistants Know What They Don't Know?
Qinyuan Cheng, Tianxiang Sun, Xiangyang Liu et al.
ICML 2024poster
Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation
Haoran Xu, Amr Sharaf, Yunmo Chen et al.
ICML 2024poster
Exploring the LLM Journey from Cognition to Expression with Linear Representations
Yuzi Yan, Jialian Li, YipinZhang et al.
ICML 2024poster
Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch
Le Yu, Bowen Yu, Haiyang Yu et al.
ICML 2024poster
Privacy-Preserving Instructions for Aligning Large Language Models
Da Yu, Peter Kairouz, Sewoong Oh et al.
ICML 2024poster
Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment
Rui Yang, Xiaoman Pan, Feng Luo et al.
ICML 2024poster
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen, Yihe Deng, Huizhuo Yuan et al.
ICML 2024poster