most citedChain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

5 citations · 6 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CL2024

Lifelong Event Detection with Embedding Space Separation and Compaction

Chengwei Qin, Ruirui Chen, Ruochen Zhao +2

To mitigate forgetting, existing lifelong event detection methods typically maintain a memory module and replay the stored memory data during the learning of a new task. However, t…

cs.LG2024★ 5 cited

Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Wenhan Xia, Chengwei Qin, Elad Hazan

Fine-tuning is the primary methodology for tailoring pre-trained large language models to specific tasks. As the model's scale and the diversity of tasks expand, parameter-efficien…

cs.CL2023★ 1 cited

PromptSum: Parameter-Efficient Controllable Abstractive Summarization

Mathieu Ravaut, Hailin Chen, Ruochen Zhao +3

Prompt tuning (PT), a parameter-efficient technique that only tunes the additional prompt embeddings while keeping the backbone pre-trained language model (PLM) frozen, has shown p…