Summary of Extended Mind Transformers, by Phoebe Klett and Thomas Ahle
Extended Mind Transformersby Phoebe Klett, Thomas AhleFirst submitted to arxiv on: 4 Jun 2024CategoriesMain: Machine…
Summary of Differentially Private Tabular Data Synthesis Using Large Language Models, by Toan V. Tran and Li Xiong
Differentially Private Tabular Data Synthesis using Large Language Modelsby Toan V. Tran, Li XiongFirst submitted…
Summary of The Importance Of Online Data: Understanding Preference Fine-tuning Via Coverage, by Yuda Song et al.
The Importance of Online Data: Understanding Preference Fine-tuning via Coverageby Yuda Song, Gokul Swamy, Aarti…
Summary of Expected Grad-cam: Towards Gradient Faithfulness, by Vincenzo Buono et al.
Expected Grad-CAM: Towards gradient faithfulnessby Vincenzo Buono, Peyman Sheikholharam Mashhadi, Mahmoud Rahat, Prayag Tiwari, Stefan…
Summary of Diffusion Tuning: Transferring Diffusion Models Via Chain Of Forgetting, by Jincheng Zhong et al.
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgettingby Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong,…
Summary of Is In-context Learning in Large Language Models Bayesian? a Martingale Perspective, by Fabian Falck et al.
Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspectiveby Fabian Falck, Ziyu Wang,…
Summary of Covariance-adaptive Sequential Black-box Optimization For Diffusion Targeted Generation, by Yueming Lyu et al.
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generationby Yueming Lyu, Kim Yong Tan, Yew Soon…
Summary of Transforming Computer Security and Public Trust Through the Exploration Of Fine-tuning Large Language Models, by Garrett Crumrine et al.
Transforming Computer Security and Public Trust Through the Exploration of Fine-Tuning Large Language Modelsby Garrett…
Summary of Furl: Visual-language Models As Fuzzy Rewards For Reinforcement Learning, by Yuwei Fu et al.
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learningby Yuwei Fu, Haichao Zhang, Di Wu,…
Summary of Empirical Influence Functions to Understand the Logic Of Fine-tuning, by Jordan K. Matelsky et al.
Empirical influence functions to understand the logic of fine-tuningby Jordan K. Matelsky, Lyle Ungar, Konrad…