16 citations · 19 across the 10 of their papers we have counts for
3 papers · 1 filter
A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks
Nicholas Monath, Will Grathwohl, Michael Boratko +3
In dense retrieval, deep encoders provide embeddings for both inputs and targets, and the softmax function is used to parameterize a distribution over a large number of candidate t…
Improving Dual-Encoder Training through Dynamic Indexes for Negative Mining
Nicholas Monath, Manzil Zaheer, Kelsey Allen +1
Dual encoder models are ubiquitous in modern classification and retrieval. Crucial for training such dual encoders is an accurate estimation of gradients from the partition functio…
Sublinear Time Approximation of Text Similarity Matrices
Archan Ray, Nicholas Monath, Andrew McCallum +1
We study algorithms for approximating pairwise similarity matrices that arise in natural language processing. Generally, computing a similarity matrix for data points requires…