research
∙
08/07/2023
Simple synthetic data reduces sycophancy in large language models
Sycophancy is an undesirable behavior where models tailor their response...
share
research
∙
05/29/2023
Brainformers: Trading Simplicity for Efficiency
Transformers are central to recent successes in natural language process...
research
∙
05/15/2023
Symbol tuning improves in-context learning in language models
We present symbol tuning - finetuning language models on in-context inpu...
research
∙
03/07/2023
Larger language models do in-context learning differently
We study how in-context learning (ICL) in language models is affected by...
research
∙
02/13/2023
Symbolic Discovery of Optimization Algorithms
We present a method to formulate algorithm discovery as program search, ...
research
∙
09/12/2022
On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models
For industrial-scale advertising systems, prediction of ad click-through...
research
∙
04/15/2022
Resource-Constrained Neural Architecture Search on Tabular Datasets
The best neural architecture for a given machine learning problem depend...
research
∙
06/23/2021
PatentNet: A Large-Scale Incomplete Multiview, Multimodal, Multilabel Industrial Goods Image Database
In deep learning area, large-scale image datasets bring a breakthrough i...
research
∙
02/17/2021
Rethinking Co-design of Neural Architectures and Hardware Accelerators
Neural architectures and hardware accelerators have been two driving for...
research
∙
11/06/2018
