Summary of Scaling Offline Model-based Rl Via Jointly-optimized World-action Model Pretraining, by Jie Cheng et al.
Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretrainingby Jie Cheng, Ruixi Qiao, Yingwei Ma,…
Summary of Investigating the Impact Of Model Complexity in Large Language Models, by Jing Luo et al.
Investigating the Impact of Model Complexity in Large Language Modelsby Jing Luo, Huiyuan Wang, Weiran…
Summary of Cxpmrg-bench: Pre-training and Benchmarking For X-ray Medical Report Generation on Chexpert Plus Dataset, by Xiao Wang et al.
CXPMRG-Bench: Pre-training and Benchmarking for X-ray Medical Report Generation on CheXpert Plus Datasetby Xiao Wang,…
Summary of Fine-tuning Vision Classifiers on a Budget, by Sunil Kumar et al.
Fine-tuning Vision Classifiers On A Budgetby Sunil Kumar, Ted Sandler, Paulina VarshavskayaFirst submitted to arxiv…
Summary of Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models, by Ji Liu et al.
Fisher Information-based Efficient Curriculum Federated Learning with Large Language Modelsby Ji Liu, Jiaxiang Ren, Ruoming…
Summary of Treb: a Bert Attempt For Imputing Tabular Data Imputation, by Shuyue Wang et al.
TREB: a BERT attempt for imputing tabular data imputationby Shuyue Wang, Wenjun Zhou, Han drk-m-s…
Summary of The Perfect Blend: Redefining Rlhf with Mixture Of Judges, by Tengyu Xu et al.
The Perfect Blend: Redefining RLHF with Mixture of Judgesby Tengyu Xu, Eryk Helenowski, Karthik Abinav…
Summary of Using Pretrained Graph Neural Networks with Token Mixers As Geometric Featurizers For Conformational Dynamics, by Zihan Pengmei et al.
Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamicsby Zihan…
Summary of Sata: Spatial Autocorrelation Token Analysis For Enhancing the Robustness Of Vision Transformers, by Nick Nikzad et al.
SATA: Spatial Autocorrelation Token Analysis for Enhancing the Robustness of Vision Transformersby Nick Nikzad, Yi…
Summary of Vision-language Models Are Strong Noisy Label Detectors, by Tong Wei and Hao-tian Li and Chun-shu Li and Jiang-xin Shi and Yu-feng Li and Min-ling Zhang
Vision-Language Models are Strong Noisy Label Detectorsby Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi,…