Summary of Prompt Tuning Strikes Back: Customizing Foundation Models with Low-rank Prompt Adaptation, by Abhinav Jain et al.
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptationby Abhinav Jain, Swarat Chaudhuri,…
Prompt Tuning Strikes Back: Customizing Foundation Models with Low-Rank Prompt Adaptationby Abhinav Jain, Swarat Chaudhuri,…
Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantificationby Shang Liu, Zhongze Cai,…
Online Prompt Pricing based on Combinatorial Multi-Armed Bandit and Hierarchical Stackelberg Gameby Meiling Li, Hongrun…
Extracting Prompts by Inverting LLM Outputsby Collin Zhang, John X. Morris, Vitaly ShmatikovFirst submitted to…
Large language models can be zero-shot anomaly detectors for time series?by Sarah Alnegheimish, Linh Nguyen,…
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecastingby Qingxiang Liu, Xu Liu, Chenghao…
Enhancing Image Layout Control with Loss-Guided Diffusion Modelsby Zakaria Patel, Kirill SerkhFirst submitted to arxiv…
Mixture of Experts Meets Prompt-Based Continual Learningby Minh Le, An Nguyen, Huy Nguyen, Trang Nguyen,…
Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalizationby Zexi Li, Lingzhi Gao, Chao WuFirst submitted…
Rehearsal-free Federated Domain-incremental Learningby Rui Sun, Haoran Duan, Jiahua Dong, Varun Ojha, Tejal Shah, Rajiv…