research
∙
08/21/2023
Bayesian Optimal Experimental Design for Constitutive Model Calibration
Computational simulation is increasingly relied upon for high-consequenc...
share
research
∙
06/07/2023
Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models
Currently, most machine learning models are trained by centralized teams...
research
∙
08/10/2022
Reducing Retraining by Recycling Parameter-Efficient Prompts
Parameter-efficient methods are able to use a single frozen pre-trained ...
research
∙
05/25/2022
Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation
In this paper, we explore the challenging problem of performing a genera...
research
∙
03/31/2022
Scaling Up Models and Data with and
Recent neural network-based language models have benefited greatly from ...
research
∙
10/15/2021
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer
As pre-trained language models have gotten larger, there has been growin...
research
∙
09/03/2021
Finetuned Language Models Are Zero-Shot Learners
This paper explores a simple method for improving the zero-shot learning...
research
∙
04/18/2021
Intent Features for Rich Natural Language Understanding
Complex natural language understanding modules in dialog systems have a ...
research
∙
04/18/2021
The Power of Scale for Parameter-Efficient Prompt Tuning
In this work, we explore "prompt tuning", a simple yet effective mechani...
research
∙
10/09/2020
iobes: A Library for Span-Level Processing
Many tasks in natural language processing, such as named entity recognit...
research
∙
10/09/2020
Constrained Decoding for Computationally Efficient Named Entity Recognition Taggers
Current state-of-the-art models for named entity recognition (NER) are n...
research
∙
09/30/2020
Multiple Word Embeddings for Increased Diversity of Representation
Most state-of-the-art models in natural language processing (NLP) are ne...
research
∙
09/29/2020
Leader: Prefixing a Length for Faster Word Vector Serialization
Two competing file formats have become the de facto standards for distri...
research
∙
01/05/2020
Computationally Efficient NER Taggers with Combined Embeddings and Constrained Decoding
Current State-of-the-Art models in Named Entity Recognition (NER) are ne...
research
∙
03/18/2019
