PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization

PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization

25 July 2024

Christopher Clarke

Papers citing "PEFT-U: Parameter-Efficient Fine-Tuning for User Personalization"

10 / 10 papers shown

Title
Teach LLMs to Personalize -- An Approach inspired by Writing Education Cheng Li Mingyang Zhang Qiaozhu Mei Yaqing Wang Spurthi Amba Hombaiah Yi Liang Michael Bendersky AI4Ed 87 40 0 15 Aug 2023
LaMP: When Large Language Models Meet Personalization Alireza Salemi Sheshera Mysore Michael Bendersky Hamed Zamani RALM 84 234 0 22 Apr 2023
LoRA: Low-Rank Adaptation of Large Language Models J. E. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen OffRL AI4TS AI4CE ALM AIMat 460 10,367 0 17 Jun 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 570 4,047 0 18 Apr 2021
Did they answer? Subjective acts and intents in conversational discourse Elisa Ferracane Greg Durrett Junjie Li K. Erk 51 20 0 09 Apr 2021
Prefix-Tuning: Optimizing Continuous Prompts for Generation Xiang Lisa Li Percy Liang 242 4,261 0 01 Jan 2021
Six Attributes of Unhealthy Conversation Ilan Price Jordan Gifford-Moore Jory Flemming Saul Musker Maayan Roichman Guillaume Sylvain Nithum Thain Lucas Dixon Jeffrey Scott Sorensen 36 33 0 14 Oct 2020
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 320 326 0 21 Aug 2019
Personalizing Dialogue Agents: I have a dog, do you have pets too? Saizheng Zhang Emily Dinan Jack Urbanek Arthur Szlam Douwe Kiela Jason Weston 105 1,459 0 22 Jan 2018
Ex Machina: Personal Attacks Seen at Scale Ellery Wulczyn Nithum Thain Lucas Dixon 89 758 0 27 Oct 2016