Summary of Scaling Laws For Precision, by Tanishq Kumar et al.
Scaling Laws for Precisionby Tanishq Kumar, Zachary Ankner, Benjamin F. Spector, Blake Bordelon, Niklas Muennighoff,…
Summary of Inference Optimal Vlms Need Only One Visual Token but Larger Models, by Kevin Y. Li et al.
Inference Optimal VLMs Need Only One Visual Token but Larger Modelsby Kevin Y. Li, Sachin…
Summary of Training Compute-optimal Protein Language Models, by Xingyi Cheng et al.
Training Compute-Optimal Protein Language Modelsby Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang,…
Summary of Manibox: Enhancing Spatial Grasping Generalization Via Scalable Simulation Data Generation, by Hengkai Tan et al.
ManiBox: Enhancing Spatial Grasping Generalization via Scalable Simulation Data Generationby Hengkai Tan, Xuezhou Xu, Chengyang…
Summary of Physics in Next-token Prediction, by Hongjun An and Yiliang Song and Xuelong Li
Physics in Next-token Predictionby Hongjun An, Yiliang Song, Xuelong LiFirst submitted to arxiv on: 1…
Summary of Bayesian Scaling Laws For In-context Learning, by Aryaman Arora et al.
Bayesian scaling laws for in-context learningby Aryaman Arora, Dan Jurafsky, Christopher Potts, Noah D. GoodmanFirst…
Summary of A Simple Model Of Inference Scaling Laws, by Noam Levi
A Simple Model of Inference Scaling Lawsby Noam LeviFirst submitted to arxiv on: 21 Oct…
Summary of Scaling Laws For Post Training Quantized Large Language Models, by Zifei Xu et al.
Scaling Laws for Post Training Quantized Large Language Modelsby Zifei Xu, Alexander Lan, Wanzin Yazar,…
Summary of A Hitchhiker’s Guide to Scaling Law Estimation, by Leshem Choshen et al.
A Hitchhiker’s Guide to Scaling Law Estimationby Leshem Choshen, Yang Zhang, Jacob AndreasFirst submitted to…
Summary of Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws, by Yiding Jiang et al.
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Lawsby Yiding Jiang, Allan Zhou, Zhili Feng,…