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Brian K Chen

2 accepted papers

2026

PrefixMemory-Tuning: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

ICLR 2026poster

Parameter-Efficient Fine-Tuning (PEFT) methods have become crucial for rapidly adapting large language models (LLMs) to downstream tasks. Prefix-Tuning, an early and effective PEFT technique, demonstrated the ability to achieve performance comparable to full fine-tuning with significantly reduced co…

Cited by 0SourcecodeScholar
2024

Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers

ICML 2024poster

In-Context Learning (ICL) has been a powerful emergent property of large language models that has attracted increasing attention in recent years. In contrast to regular gradient-based learning, ICL is highly interpretable and does not require parameter updates. In this paper, we show that, for linea…

Cited by 0SourcePDFScholar