Post-Hoc Reversal: Are We Selecting Models Prematurely?

Post-Hoc Reversal: Are We Selecting Models Prematurely?

11 April 2024

Carlos Guestrin

Zachary Chase Lipton

Papers citing "Post-Hoc Reversal: Are We Selecting Models Prematurely?"

10 / 10 papers shown

Title
WARM: On the Benefits of Weight Averaged Reward Models Alexandre Ramé Nino Vieillard Léonard Hussenot Robert Dadashi Geoffrey Cideron Olivier Bachem Johan Ferret 97 92 0 22 Jan 2024
To Repeat or Not To Repeat: Insights from Scaling LLM under Token-Crisis Fuzhao Xue Yao Fu Wangchunshu Zhou Zangwei Zheng Yang You 79 74 0 22 May 2023
Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle Rylan Schaeffer Mikail Khona Zachary Robertson Akhilan Boopathy Kateryna Pistunova J. Rocks Ila Rani Fiete Oluwasanmi Koyejo 62 29 0 24 Mar 2023
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 186 128 0 19 May 2022
ResNet strikes back: An improved training procedure in timm Ross Wightman Hugo Touvron Hervé Jégou AI4TS 198 477 0 01 Oct 2021
SWAD: Domain Generalization by Seeking Flat Minima Junbum Cha Sanghyuk Chun Kyungjae Lee Han-Cheol Cho Seunghyun Park Yunsung Lee Sungrae Park MoMe 216 422 0 17 Feb 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 223 4,424 0 23 Jan 2020
Bag of Tricks for Image Classification with Convolutional Neural Networks Tong He Zhi-Li Zhang Hang Zhang Zhongyue Zhang Junyuan Xie Mu Li 210 1,391 0 04 Dec 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,635 0 05 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016