Your submission is now in Draft mode.

Once it's ready, please submit your draft for review by our team of Community Moderators. Thank you!

Your essay is now in Draft mode

Once you submit your essay, it will be available to judges for review and you can no longer edit it. Please make sure to review eligibility criteria before submitting. Thank you!

Submit Essay

Once you submit your essay, you can no longer edit it.


This content now needs to be approved by community moderators.


This essay was submitted and is waiting for review by judges.

Best Penn Treebank perplexity of 2019?


An active area of research in artificial intelligence is language modelling: the task of learning a probability distribution over the next word in a sentence given all the previous words. To measure the performance of these models, researchers often use the Penn Treebank dataset, a large collection of sentences published in the Wall Street Journal. They then measure the word-level perplexity of their model, which intuitively is the weighted average number of words the model thinks might occur next at any point in time. More specifically, if our test set is where is a word, is the context for that word, and ranges from 1 to , the number of words, then the perplexity of model on that test set is Basically, lower perplexities are better.

The best perplexity achieved so far by a published model that the author can find is 52.8, achieved in the paper Regularizing and Optimizing LSTM Language Models published by Merity, Keskar, and Socher in ICLR 2018. Better results have been achieved using dynamic evaluation, which trains the model on data while it is being tested, however we will discard those, only focussing on perplexities of pre-trained models.

In this question, we ask: what will the lowest achieved perplexity on the Penn Treebank dataset be of all pre-trained models in papers accepted to prominent AI conferences in 2019?

For the purpose of this conference, the list of prominent AI conferences is ICLR, ICML, NeurIPS, AAAI, AISTATS, NAACL, EMNLP-IJCNLP, UAI, ACL, IJCAI, and COLT. The author reserves the right to add conferences to this list if he thinks they should be on it, and promises not to use this power to rig the question.

Make a Prediction


Note: this question resolved before its original close time. All of your predictions came after the resolution, so you did not gain (or lose) any points for it.

Note: this question resolved before its original close time. You earned points up until the question resolution, but not afterwards.

This question is not yet open for predictions.

Current points depend on your prediction, the community's prediction, and the result. Your total earned points are averaged over the lifetime of the question, so predict early to get as many points as possible! See the FAQ.

Metaculus help: Predicting

Predictions are the heart of Metaculus. Predicting is how you contribute to the wisdom of the crowd, and how you earn points and build up your personal Metaculus track record.

The basics of predicting are very simple: move the slider to best match the likelihood of the outcome, and click predict. You can predict as often as you want, and you're encouraged to change your mind when new information becomes available.

The displayed score is split into current points and total points. Current points show how much your prediction is worth now, whereas total points show the combined worth of all of your predictions over the lifetime of the question. The scoring details are available on the FAQ.

Thanks for predicting!

Your prediction has been recorded anonymously.

Want to track your predictions, earn points, and hone your forecasting skills? Create an account today!

Track your predictions
Continue exploring the site