Same Pre-training Loss, Better Downstream: Implicit Bias Matters for
Language Models

Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models

25 October 2022

Sang Michael Xie

Papers citing "Same Pre-training Loss, Better Downstream: Implicit Bias Matters for Language Models"

18 / 18 papers shown

Title
Revisiting Transformers through the Lens of Low Entropy and Dynamic Sparsity Ruifeng Ren Yong Liu 39 0 0 26 Apr 2025
Reasoning Bias of Next Token Prediction Training Pengxiao Lin Zhongwang Zhang Zhi-Qin John Xu LRM 80 1 0 21 Feb 2025
Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations Yize Zhao Tina Behnia V. Vakilian Christos Thrampoulidis 55 7 0 20 Feb 2025
SLoPe: Double-Pruned Sparse Plus Lazy Low-Rank Adapter Pretraining of LLMs Mohammad Mozaffari Amir Yazdanbakhsh Zhao Zhang M. Dehnavi 65 5 0 28 Jan 2025
Understanding Emergent Abilities of Language Models from the Loss Perspective Zhengxiao Du Aohan Zeng Yuxiao Dong Jie Tang UQCV LRM 55 46 0 23 Mar 2024
Improving Language Plasticity via Pretraining with Active Forgetting Yihong Chen Kelly Marchisio Roberta Raileanu David Ifeoluwa Adelani Pontus Stenetorp Sebastian Riedel Mikel Artetx KELM AI4CE CLL 17 23 0 03 Jul 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 22 6 0 25 May 2023
Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency Lingfeng Shen Weiting Tan Boyuan Zheng Daniel Khashabi VLM 22 6 0 18 May 2023
Understanding Gradient Descent on Edge of Stability in Deep Learning Sanjeev Arora Zhiyuan Li A. Panigrahi MLT 72 88 0 19 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,261 0 28 Jan 2022
Sharpness-Aware Minimization Improves Language Model Generalization Dara Bahri H. Mobahi Yi Tay 119 82 0 16 Oct 2021
What Happens after SGD Reaches Zero Loss? --A Mathematical Framework Zhiyuan Li Tianhao Wang Sanjeev Arora MLT 83 98 0 13 Oct 2021
Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers Yi Tay Mostafa Dehghani J. Rao W. Fedus Samira Abnar Hyung Won Chung Sharan Narang Dani Yogatama Ashish Vaswani Donald Metzler 183 89 0 22 Sep 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 239 2,554 0 04 May 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 220 4,424 0 23 Jan 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,927 0 20 Apr 2018
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 2016
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights Weijie Su Stephen P. Boyd Emmanuel J. Candes 97 1,150 0 04 Mar 2015