Summary of A Minimalist Prompt For Zero-shot Policy Learning, by Meng Song et al.
A Minimalist Prompt for Zero-Shot Policy Learningby Meng Song, Xuezhi Wang, Tanay Biradar, Yao Qin,…
Summary of Hmt: Hierarchical Memory Transformer For Efficient Long Context Language Processing, by Zifan He et al.
HMT: Hierarchical Memory Transformer for Efficient Long Context Language Processingby Zifan He, Yingqi Cao, Zongyue…
Summary of Distilling Diffusion Models Into Conditional Gans, by Minguk Kang et al.
Distilling Diffusion Models into Conditional GANsby Minguk Kang, Richard Zhang, Connelly Barnes, Sylvain Paris, Suha…
Summary of Memory-space Visual Prompting For Efficient Vision-language Fine-tuning, by Shibo Jie et al.
Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuningby Shibo Jie, Yehui Tang, Ning Ding, Zhi-Hong Deng,…
Summary of Aux-nas: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost, by Yuan Gao et al.
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Costby Yuan Gao, Weizhong Zhang, Wenhan Luo,…
Summary of The Effect Of Model Size on Llm Post-hoc Explainability Via Lime, by Henning Heyen et al.
The Effect of Model Size on LLM Post-hoc Explainability via LIMEby Henning Heyen, Amy Widdicombe,…
Summary of Aspire: Iterative Amortized Posterior Inference For Bayesian Inverse Problems, by Rafael Orozco et al.
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problemsby Rafael Orozco, Ali Siahkoohi, Mathias Louboutin,…
Summary of Variance Control For Black Box Variational Inference Using the James-stein Estimator, by Dominic B. Dayta
Variance Control for Black Box Variational Inference Using The James-Stein Estimatorby Dominic B. DaytaFirst submitted…
Summary of Vidur: a Large-scale Simulation Framework For Llm Inference, by Amey Agrawal et al.
Vidur: A Large-Scale Simulation Framework For LLM Inferenceby Amey Agrawal, Nitin Kedia, Jayashree Mohan, Ashish…
Summary of Conv-basis: a New Paradigm For Efficient Attention Inference and Gradient Computation in Transformers, by Yingyu Liang et al.
Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformersby Yingyu Liang,…