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Can AI Models Appreciate Document Aesthetics? An Exploration of Legibility and Layout Quality in Relation to Prediction Confidence
A well-designed document communicates not only through its words but also through its visual eloquence.
Extracting Complex Named Entities in Legal Documents via Weakly Supervised Object Detection
Accurate Named Entity Recognition (NER) is crucial for various information retrieval tasks in industry.
Amortized Variational Inference for Simple Hierarchical Models
It is difficult to use subsampling with variational inference in hierarchical models since the number of local latent variables scales with the dataset.
Normalizing Flows Across Dimensions
In this paper we introduce noisy injective flows (NIF), a generalization of normalizing flows that can go across dimensions.
Advances in Black-Box VI: Normalizing Flows, Importance Weighting, and Optimization
The combination of these algorithmic components significantly advances the state-of-the-art "out of the box" variational inference.
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