Summary of Rosa: Accurate Parameter-efficient Fine-tuning Via Robust Adaptation, by Mahdi Nikdan et al.
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptationby Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević, Dan AlistarhFirst…
Summary of Chain Of Lora: Efficient Fine-tuning Of Language Models Via Residual Learning, by Wenhan Xia et al.
Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learningby Wenhan Xia, Chengwei Qin,…
Summary of Private Fine-tuning Of Large Language Models with Zeroth-order Optimization, by Xinyu Tang et al.
Private Fine-tuning of Large Language Models with Zeroth-order Optimizationby Xinyu Tang, Ashwinee Panda, Milad Nasr,…
Summary of Empirical Analysis Of Efficient Fine-tuning Methods For Large Pre-trained Language Models, by Nigel Doering et al.
Empirical Analysis of Efficient Fine-Tuning Methods for Large Pre-Trained Language Modelsby Nigel Doering, Cyril Gorlla,…
Summary of Preserving Silent Features For Domain Generalization, by Chujie Zhao et al.
Preserving Silent Features for Domain Generalizationby Chujie Zhao, Tianren Zhang, Feng ChenFirst submitted to arxiv…
Summary of Moto: Offline Pre-training to Online Fine-tuning For Model-based Robot Learning, by Rafael Rafailov et al.
MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learningby Rafael Rafailov, Kyle Hatch, Victor…
Summary of Deepseek Llm: Scaling Open-source Language Models with Longtermism, by Deepseek-ai: Xiao Bi et al.
DeepSeek LLM: Scaling Open-Source Language Models with Longtermismby DeepSeek-AI, Xiao Bi, Deli Chen, Guanting Chen,…
Summary of Simple Hierarchical Planning with Diffusion, by Chang Chen et al.
Simple Hierarchical Planning with Diffusionby Chang Chen, Fei Deng, Kenji Kawaguchi, Caglar Gulcehre, Sungjin AhnFirst…
Summary of Mapping Of Land Use and Land Cover (lulc) Using Eurosat and Transfer Learning, by Suman Kunwar et al.
Mapping of Land Use and Land Cover (LULC) using EuroSAT and Transfer Learningby Suman Kunwar,…
Summary of Switchtab: Switched Autoencoders Are Effective Tabular Learners, by Jing Wu et al.
SwitchTab: Switched Autoencoders Are Effective Tabular Learnersby Jing Wu, Suiyao Chen, Qi Zhao, Renat Sergazinov,…