Summary of Parameter-efficient Fine-tuning with Discrete Fourier Transform, by Ziqi Gao et al.
Parameter-Efficient Fine-Tuning with Discrete Fourier Transformby Ziqi Gao, Qichao Wang, Aochuan Chen, Zijing Liu, Bingzhe…
Summary of Xft: Unlocking the Power Of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-experts, By Yifeng Ding et al.
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Expertsby Yifeng Ding,…
Summary of Personalized Wireless Federated Learning For Large Language Models, by Feibo Jiang et al.
Personalized Wireless Federated Learning for Large Language Modelsby Feibo Jiang, Li Dong, Siwei Tu, Yubo…
Summary of Textsquare: Scaling Up Text-centric Visual Instruction Tuning, by Jingqun Tang et al.
TextSquare: Scaling up Text-Centric Visual Instruction Tuningby Jingqun Tang, Chunhui Lin, Zhen Zhao, Shu Wei,…
Summary of Unveiling Imitation Learning: Exploring the Impact Of Data Falsity to Large Language Model, by Hyunsoo Cho
Unveiling Imitation Learning: Exploring the Impact of Data Falsity to Large Language Modelby Hyunsoo ChoFirst…
Summary of Cem: a Data-efficient Method For Large Language Models to Continue Evolving From Mistakes, by Haokun Zhao and Haixia Han and Jie Shi and Chengyu Du and Jiaqing Liang and Yanghua Xiao
CEM: A Data-Efficient Method for Large Language Models to Continue Evolving From Mistakesby Haokun Zhao,…
Summary of Post-hoc Reversal: Are We Selecting Models Prematurely?, by Rishabh Ranjan et al.
Post-Hoc Reversal: Are We Selecting Models Prematurely?by Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin,…
Summary of On Training Data Influence Of Gpt Models, by Yekun Chai et al.
On Training Data Influence of GPT Modelsby Yekun Chai, Qingyi Liu, Shuohuan Wang, Yu Sun,…
Summary of Groundedness in Retrieval-augmented Long-form Generation: An Empirical Study, by Alessandro Stolfo
Groundedness in Retrieval-augmented Long-form Generation: An Empirical Studyby Alessandro StolfoFirst submitted to arxiv on: 10…
Summary of Reft: Representation Finetuning For Language Models, by Zhengxuan Wu and Aryaman Arora and Zheng Wang and Atticus Geiger and Dan Jurafsky and Christopher D. Manning and Christopher Potts
ReFT: Representation Finetuning for Language Modelsby Zhengxuan Wu, Aryaman Arora, Zheng Wang, Atticus Geiger, Dan…