When is an Embedding Model More Promising than Another?

NeurIPS'24

Maxime DARRIN*, Philippe FORMONT*, Ismail BEN AYED, Jackie Chi Kit CHEUNG, Pablo PIANTANIDA

[ArXiv]

This repository contains the code for the paper: When is an Embedding Model More Promising than Another? It is divided in three main components:

1. emir: Contains the code to estimate the information sufficiency between two models.
2. molecule: Contains the code used for the molecular modeling experiments.
3. nlp_embeddings: Contains the code used for the NLP experiments

All directories contain there specific Readme files.

Introduction

Installation

pip install -e . 

Cite us

Coming soon