Reading room.
Engineering blogs & AI research
A reading room from engineering teams and AI labs: titles, short feed excerpts, and links to the originals. For my own essays, explore the writing archive.
- 1359 articles tracked
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Sources
LinkBERT: Improving Language Model Training with Document Link
Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2 , achieve remarkable performance on many natural language processing (NLP) tasks. They are now the foundation of today’s NLP systems. 3 T…
Stanford AI Lab Papers and Talks at ACL 2022
The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is taking place May 22nd - May 27th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to pape…
Stanford AI Lab Papers and Talks at ICLR 2022
The International Conference on Learning Representations (ICLR) 2022 is being hosted virtually from April 25th - April 29th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to…
Discovering the systematic errors made by machine learning models
Discovering systematic errors with cross-modal embeddings In this blog post, we introduce Domino, a new approach for discovering systematic errors made by machine learning models. We also discuss a framework for quantita…
Grading Complex Interactive Coding Programs with Reinforcement Learning
[Summary] tl;dr: A tremendous amount of effort has been poured into training AI algorithms to competitively play games that computers have traditionally had trouble with, such as the retro games published by Atari, Go, D…
Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training
Deep models require a lot of training examples, but labeled data is difficult to obtain. This motivates an important line of research on leveraging unlabeled data, which is often more readily available. For example, larg…
Stanford AI Lab Papers and Talks at AAAI 2022
The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) is being hosted virtually from February 22th - March 1st. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to pap…
How to Improve User Experience (and Behavior): Three Papers from Stanford's Alexa Prize Team
Introduction In 2019, Stanford entered the Alexa Prize Socialbot Grand Challenge 3 for the first time, with its bot Chirpy Cardinal , which went on to win 2nd place in the competition. In our previous post , we discussed…
Reward Isn't Free: Supervising Robot Learning with Language and Video from the Web
This work was conducted as part of SAIL and CRFM . Deep learning has enabled improvements in the capabilities of robots on a range of problems such as grasping 1 and locomotion 2 in recent years. However, building the qu…
BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits
TL;DR Want something better than \(k\)-means? Our state-of-the-art \(k\)-medoids algorithm from NeurIPS, BanditPAM, is now publicly available! \(\texttt{pip install banditpam}\) and you're good to go! Like the \(k\)-mean…
Stanford AI Lab Papers and Talks at NeurIPS 2021
The thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 is being hosted virtually from Dec 6th - 14th. We’re excited to share all the work from SAIL that’s being presented at the main conferen…
Stanford AI Lab Papers at CoRL 2021
The Conference on Robot Learning (CoRL 2021) will take place next week. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach ou…
Stanford AI Lab Papers at EMNLP/CoNLL 2021
The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) will take place next week, colocated with CoNLL 2021. We’re excited to share all the work from SAIL that will be presented, and you’ll…
Selective Classification Can Magnify Disparities Across Groups
Selective classification, where models are allowed to “abstain” when they are uncertain about a prediction, is a useful approach for deploying models in settings where errors are costly. For example, in medicine, model e…
Stanford AI Lab Papers at ICCV 2021
The International Conference on Computer Vision (ICCV 2021) will be hosted virtually next week. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs belo…