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20192026
most citedFundamental Safety-Capability Trade-offs in Fine-tuning Large Language Models

1 citations · 1 across the 6 of their papers we have counts for

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cs.AI2024

Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs

Megh Thakkar, Quentin Fournier, Matthew Riemer +4

There is a growing interest in training domain-expert LLMs that excel in specific technical fields compared to their general-purpose instruction-tuned counterparts. However, these…

cs.LG2024

SEAL: Safety-enhanced Aligned LLM Fine-tuning via Bilevel Data Selection

Han Shen, Pin-Yu Chen, Payel Das +1

Fine-tuning on task-specific data to boost downstream performance is a crucial step for leveraging Large Language Models (LLMs). However, previous studies have demonstrated that fi…