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Pay Attention to MLPs | Papers With Code

Images should be at least ×px ×px for best display. Include the markdown at the top of your GitHub README. md file to showcase the performance of the model. Badges are live and will be dynamically updated with the latest ranking of this paper. SoQuoc V. Le · Edit social preview. Pay for paper have become one of the most important architectural innovations in deep learning and have pay for paper many breakthroughs over the past few years.

Here we propose a simple network architecture, gMLP, based on MLPs with gating, and show that it can perform as well as Transformers in key language and vision applications. Our comparisons show that self-attention is not critical for Vision Transformers, as gMLP can achieve the same accuracy.

For BERT, our model achieves parity with Transformers on pretraining perplexity and is better on some downstream NLP tasks. On finetuning tasks where gMLP performs worse, making the gMLP model substantially larger can close the gap with Transformers. In general, our experiments show that gMLP can scale as well as Transformers over increased data and compute. read more. Ranked 19 on Natural Language Inference on MultiNLI. Browse State-of-the-Art Datasets Methods More Libraries Newsletter.

Subscribe to the PwC Newsletter ×. Stay informed on pay for paper latest trending ML papers with code, pay for paper, research developments, libraries, methods, and datasets. Read previous issues. Join the community ×. Pay for paper need to log in to edit, pay for paper. You can create a new account if you don't have one. Or, discuss a change on Slack. Edit Social Preview ×. Description Default.

Image Default. File is too large. Close Save. Add a new code entry for this paper ×. Official code from paper authors. Remove a code repository from this paper ×. Mark the official implementation from paper authors ×.

There is no official implementation. Multiple official implementations. Add a new evaluation result row ×. Not in the list? Add a task. Higher is better for the metric. Uses extra training data. Data evaluated on. TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK REMOVE Image Classification ImageNet gMLP-B Top 1 Accuracy Add a task ×, pay for paper.

Attached tasks:. Add: Create a new task. New task name:. Top-level area: Adversarial Audio Computer Code Computer Vision Graphs Knowledge Base Medical Methodology Miscellaneous Music Natural Language Processing Playing Games Reasoning Robots Speech Time Series.

Parent task if any : Remove a task ×. Image Classification - Natural Language Inference - Question Answering - Sentiment Analysis. Add a method ×, pay for paper.

Attached methods:. Create a new method. New method name e. ReLU :. New method full name e, pay for paper. Rectified Linear Unit :. Paper where method was first introduced : Method category e, pay for paper. Activation Functions : If no match, add something for now then you can add a new category afterwards.

Remove a method ×. Badge Markdown [! Edit Datasets ×. Add or remove datasets introduced in this paper:. Add or remove other datasets used in this paper: C4 GLUE ImageNet MultiNLI SQuAD SST. Paper introduces a new dataset? Add a new dataset here. Pay Attention to MLPs 17 May · Hanxiao LiuZihang DaiDavid R. read more PDF Abstract. Code Edit Add Remove Mark official. See all 13 implementations.

Collapse 13 implementations. Tasks Edit Add Remove. Image Classification Natural Language Inference Question Answering Sentiment Analysis. Datasets Edit. ImageNet SQuAD GLUE SST MultiNLI C4. Results from the Paper Edit. Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark Image Classification ImageNet gMLP-B Top 1 Accuracy Methods Edit Add Remove. Contact us on: hello paperswithcode.

Papers With Code is a free resource with all data licensed under CC-BY-SA. Pay for paper Privacy Cookies policy. Top 1 Accuracy. Number of params. Natural Language Inference. SST-2 Binary classification.

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