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cs.LG2024
Aligning Large Language Models by On-Policy Self-Judgment
Sangkyu Lee, Sungdong Kim, Ashkan Yousefpour +3
Existing approaches for aligning large language models with human preferences face a trade-off that requires a separate reward model (RM) for on-policy learning. In this paper, we…
cs.LG2024
Rethinking the Role of Proxy Rewards in Language Model Alignment
Sungdong Kim, Minjoon Seo
Learning from human feedback via proxy reward modeling has been studied to align Large Language Models (LLMs) with human values. However, achieving reliable training through that p…
cs.LG2023★ 28 cited
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
Jeonghoon Kim, Jung Hyun Lee, Sungdong Kim +4
Large language models (LLMs) face the challenges in fine-tuning and deployment due to their high memory demands and computational costs. While parameter-efficient fine-tuning (PEFT…