266 citations · 497 across the 7 of their papers we have counts for
8 papers
Ask Me Anything: A simple strategy for prompting language models
Simran Arora, Avanika Narayan, Mayee F. Chen +6
Large language models (LLMs) transfer well to new tasks out-of-the-box simply given a natural language prompt that demonstrates how to perform the task and no additional training.…
Can Foundation Models Wrangle Your Data?
Avanika Narayan, Ines Chami, Laurel Orr +2
Foundation Models (FMs) are models trained on large corpora of data that, at very large scale, can generalize to new tasks without any task-specific finetuning. As these models con…
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Ines Chami, Albert Gu, Dat Nguyen +1
This paper studies Principal Component Analysis (PCA) for data lying in hyperbolic spaces. Given directions, PCA relies on: (1) a parameterization of subspaces spanned by these dir…
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
Ines Chami, Albert Gu, Vaggos Chatziafratis +1
Similarity-based Hierarchical Clustering (HC) is a classical unsupervised machine learning algorithm that has traditionally been solved with heuristic algorithms like Average-Linka…
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
Ines Chami, Sami Abu-El-Haija, Bryan Perozzi +2
There has been a surge of recent interest in learning representations for graph-structured data. Graph representation learning methods have generally fallen into three main categor…
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
Ines Chami, Adva Wolf, Da-Cheng Juan +3
Knowledge graph (KG) embeddings learn low-dimensional representations of entities and relations to predict missing facts. KGs often exhibit hierarchical and logical patterns which…
Hyperbolic Graph Convolutional Neural Networks
Ines Chami, Rex Ying, Christopher Ré +1
Graph convolutional neural networks (GCNs) embed nodes in a graph into Euclidean space, which has been shown to incur a large distortion when embedding real-world graphs with scale…
Referring Relationships
Ranjay Krishna, Ines Chami, Michael Bernstein +1
Images are not simply sets of objects: each image represents a web of interconnected relationships. These relationships between entities carry semantic meaning and help a viewer di…