PerPLM: Personalized Fine-tuning of Pretrained Language Models via Writer-specific Intermediate Learning and Prompts

14 September 2023

Papers citing "PerPLM: Personalized Fine-tuning of Pretrained Language Models via Writer-specific Intermediate Learning and Prompts"

4 / 4 papers shown

Title
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 236 805 0 14 Oct 2021
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis Fatemehsadat Mireshghallah Vaishnavi Shrivastava Milad Shokouhi Taylor Berg-Kirkpatrick Robert Sim Dimitrios Dimitriadis FedML 37 33 0 01 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,843 0 18 Apr 2021
Dynamic Contextualized Word Embeddings Valentin Hofmann J. Pierrehumbert Hinrich Schütze 27 50 0 23 Oct 2020