2 papers
cs.LG2025
Data Selection for LLM Alignment Using Fine-Grained Preferences
Jia Zhang, Yao Liu, Chen-Xi Zhang +4
Large language models (LLMs) alignment aims to ensure that the behavior of LLMs meets human preferences. While collecting data from multiple fine-grained, aspect-specific preferenc…
cs.LG2025
D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning
Jia Zhang, Chen-Xi Zhang, Yao Liu +5
Recent advancements in instruction tuning for large language models (LLMs) suggest that a small, high-quality dataset can significantly equip LLMs with instruction-following capabi…