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Found 8 papers, 8 papers with code
Ask Me Anything: A simple strategy for prompting language models
Prompting is a brittle process wherein small modifications to the prompt can cause large variations in the model predictions, and therefore significant effort is dedicated towards designing a painstakingly "perfect prompt" for a task.
Ranked #1 on
Question Answering
on Story Cloze
Can Foundation Models Wrangle Your Data?
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.
Ranked #10 on
Entity Resolution
on Amazon-Google
HoroPCA: Hyperbolic Dimensionality Reduction via Horospherical Projections
Given directions, PCA relies on: (1) a parameterization of subspaces spanned by these directions, (2) a method of projection onto subspaces that preserves information in these directions, and (3) an objective to optimize, namely the variance explained by projections.
From Trees to Continuous Embeddings and Back: Hyperbolic Hierarchical Clustering
Recently, Dasgupta reframed HC as a discrete optimization problem by introducing a global cost function measuring the quality of a given tree.
Machine Learning on Graphs: A Model and Comprehensive Taxonomy
The second, graph regularized neural networks, leverages graphs to augment neural network losses with a regularization objective for semi-supervised learning.
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
However, existing hyperbolic embedding methods do not account for the rich logical patterns in KGs.
Ranked #5 on
Link Prediction
on YAGO3-10
Hyperbolic Graph Convolutional Neural Networks
Here we propose Hyperbolic Graph Convolutional Neural Network (HGCN), the first inductive hyperbolic GCN that leverages both the expressiveness of GCNs and hyperbolic geometry to learn inductive node representations for hierarchical and scale-free graphs.
Ranked #1 on
Link Prediction
on PPI
(Accuracy metric)
Referring Relationships
We formulate the cyclic condition between the entities in a relationship by modelling predicates that connect the entities as shifts in attention from one entity to another.
