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Zhuoyang Song

2 accepted papers

2024

DimA: A Parameter-efficient Fine-tuning Method with Knowledge Transfer Based on Transformer

COLING 2024main

Fine-tuning is a widely used technique for leveraging pre-trained language models (PLMs) in downstream tasks, but it can be computationally expensive and storage-intensive. To address this challenge, researchers have developed parameter-efficient methods that balance performance and resource cost. H…

2024

Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Training

ACL 2024long

While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The “lost in the middle” problem challenges most LLMs, referring to the dramatic decline in accuracy when correct information is located…