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cs.CL2026
Annotations Mitigate Post-Training Mode Collapse
Jacob Mitchell Springer, Madhu Advani, Lukas Aichberger +7
Post-training (via supervised fine-tuning) improves instruction-following, but often induces semantic mode collapse by biasing models toward low-entropy fine-tuning data at the exp…
cs.CL2024
LoRA Soups: Merging LoRAs for Practical Skill Composition Tasks
Akshara Prabhakar, Yuanzhi Li, Karthik Narasimhan +3
Low-Rank Adaptation (LoRA) is a popular technique for parameter-efficient fine-tuning of Large Language Models (LLMs). We study how different LoRA modules can be merged to achieve…