Search Results for author:
Found 13 papers, 2 papers with code
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models.
Visualizing and Measuring the Geometry of BERT
Transformer architectures show significant promise for natural language processing.
TensorFlow.js: Machine Learning for the Web and Beyond
TensorFlow. js is a library for building and executing machine learning algorithms in JavaScript.
An Interpretability Illusion for BERT
We describe an "interpretability illusion" that arises when analyzing the BERT model.
Wordcraft: a Human-AI Collaborative Editor for Story Writing
As neural language models grow in effectiveness, they are increasingly being applied in real-world settings.
A Recipe For Arbitrary Text Style Transfer with Large Language Models
In this paper, we leverage large language models (LMs) to perform zero-shot text style transfer.
SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets
We use our method to curate SynthBio - a new evaluation set for WikiBio - composed of structured attribute lists describing fictional individuals, mapped to natural language biographies.
The Case for a Single Model that can Both Generate Continuations and Fill in the Blank
The task of inserting text into a specified position in a passage, known as fill in the blank (FitB), is useful for a variety of applications where writers interact with a natural language generation (NLG) system to craft text.
The Case for a Single Model that can Both Generate Continuations and Fill-in-the-Blank
While previous work has tackled this problem with models trained specifically to do fill in the blank, a more useful model is one that can effectively perform _both_ FitB and continuation tasks.
Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers
Recent developments in natural language generation (NLG) using neural language models have brought us closer than ever to the goal of building AI-powered creative writing tools.
Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning
In this paper, we explore the use of TracIn to improve model performance in the parameter-efficient tuning (PET) setting.
Towards Agile Text Classifiers for Everyone
Text-based safety classifiers are widely used for content moderation and increasingly to tune generative language model behavior - a topic of growing concern for the safety of digital assistants and chatbots.
ConstitutionalExperts: Training a Mixture of Principle-based Prompts
We also show that we can improve overall performance by learning unique prompts for different semantic regions of the training data and using a mixture-of-experts (MoE) architecture to route inputs at inference time.
