activity
20202026
most citedPyTorch Metric Learning

21 citations · 23 across the 5 of their papers we have counts for

collaborators

7 papers

cs.SE2026

Kozuchi Agent: A Language-Agnostic Open-Weight Agent for Software Repair

Mehdi Bahrami, Kosaku Kimura, Satoshi Munakata +24

Industrial software-engineering teams increasingly need LLM agents that turn bug reports into correct patches, yet benchmark-scale operation adds long horizons, tool-use discipline…

cs.CV2025

All You Need to Know About Training Image Retrieval Models

Gabriele Berton, Kevin Musgrave, Carlo Masone

Image retrieval is the task of finding images in a database that are most similar to a given query image. The performance of an image retrieval pipeline depends on many training-ti…

cs.LG2022

PyTorch Adapt

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

PyTorch Adapt is a library for domain adaptation, a type of machine learning algorithm that re-purposes existing models to work in new domains. It is a fully-featured toolkit, allo…

cs.CV2022★ 2 cited

Three New Validators and a Large-Scale Benchmark Ranking for Unsupervised Domain Adaptation

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

Changes to hyperparameters can have a dramatic effect on model accuracy. Thus, the tuning of hyperparameters plays an important role in optimizing machine-learning models. An integ…

cs.CV2021

Unsupervised Domain Adaptation: A Reality Check

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

Interest in unsupervised domain adaptation (UDA) has surged in recent years, resulting in a plethora of new algorithms. However, as is often the case in fast-moving fields, baselin…

cs.CV2020★ 21 cited

PyTorch Metric Learning

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

Deep metric learning algorithms have a wide variety of applications, but implementing these algorithms can be tedious and time consuming. PyTorch Metric Learning is an open source…

cs.CV2020

A Metric Learning Reality Check

Kevin Musgrave, Serge Belongie, Ser-Nam Lim

Deep metric learning papers from the past four years have consistently claimed great advances in accuracy, often more than doubling the performance of decade-old methods. In this p…