156 citations · 157 across the 3 of their papers we have counts for
3 papers
cs.CL2023
Data Similarity is Not Enough to Explain Language Model Performance
Gregory Yauney, Emily Reif, David Mimno
Large language models achieve high performance on many but not all downstream tasks. The interaction between pretraining data and task data is commonly assumed to determine this va…
cs.CL2022★ 1 cited
The Case for a Single Model that can Both Generate Continuations and Fill in the Blank
Daphne Ippolito, Liam Dugan, Emily Reif +3
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…
stat.ML2016★ 156 cited
Embedding Projector: Interactive Visualization and Interpretation of Embeddings
Daniel Smilkov, Nikhil Thorat, Charles Nicholson +3
Embeddings are ubiquitous in machine learning, appearing in recommender systems, NLP, and many other applications. Researchers and developers often need to explore the properties o…