Information about a model for multi-document summarization and question answering
Machine Learning Research

Bigger Corpora, Better Answers

Models that summarize documents and answer questions work pretty well with limited source material, but they can slip into incoherence when they draw from a sizeable corpus. Recent work addresses this problem.
Graph related to LIME and SHAP methods
Machine Learning Research

Bias Goes Undercover

As black-box algorithms like neural networks find their way into high-stakes fields such as transportation, healthcare, and finance, researchers have developed techniques to help explain models’ decisions. New findings show that some of these methods can be fooled.
Comparison between TrXL and GTrXL
Machine Learning Research

Melding Transformers with RL

Large NLP models like BERT can answer questions about a document thanks to the transformer network, a sequence-processing architecture that retains information across much longer sequences than previous methods. But transformers have had little success in reinforcement learning — until now.
Data related to RPDet
Machine Learning Research

Beyond the Bounding Box

Computer vision models typically draw bounding boxes around objects they spot, but those rectangles are a crude approximation of an object’s outline. A new method finds keypoints on an object’s perimeter to produce state-of-the-art object classification.
Information related to a model that predicts a chemical's smell
Machine Learning Research

Nose Job

Predicting a molecule’s aroma is hard because slight changes in structure lead to huge shifts in perception. Good thing deep learning is developing a sense of smell.
Word vectors
Machine Learning Research

Finer Tuning

A word-embedding model typically learns vector representations from a large, general-purpose corpus like Google News. But to make the resulting vectors useful in a specialized domain, they must be fine-tuned on a smaller, domain-specific dataset. Researchers offer a more accurate method.
OctConv example
Machine Learning Research

Convolution Revolution

Looking at images, people see outlines before the details within them. A replacement for the traditional convolutional layer decomposes images based on this distinction between coarse and fine features.
Examples of finished virtual pencil sketches (shoe and headshot)
Machine Learning Research

Unfinished Artwork? No More

Generative networks can embroider sentences into stories and melodies into full-fledged arrangements. A new model does something similar with drawings.
Robot cooking, controlled by a person
Machine Learning Research

Robotic Control, Easy as Apple Pie

Robots designed to assist people with disabilities have become more capable, but they’ve also become harder to control. New research offers a way to operate such complex mechanical systems more intuitively.
Schematic of the architecture used in experiments related to systematic reasoning in deep reinforcement learning
Machine Learning Research

How Neural Networks Generalize

Humans understand the world by abstraction: If you grasp the concept of grabbing a stick, then you’ll also comprehend grabbing a ball. New work explores deep learning agents’ ability to do the same thing — an important aspect of their ability to generalize.
Process of labeling doctors' notes
Machine Learning Research

Cracking Open Doctors’ Notes

Weak supervision is the practice of assigning likely labels to unlabeled data using a variety of simple labeling functions. Then supervised methods can be used on top of the now-labeled data.
An illustration of filter pruning
Machine Learning Research

High Accuracy, Low Compute

As neural networks have become more accurate, they’ve also ballooned in size and computational cost. That makes many state-of-the-art models impractical to run on phones and potentially smaller, less powerful devices.
Proposed model for abstractive summarization of a scientific article
Machine Learning Research

Two Steps to Better Summaries

Summarizing a document using original words is a longstanding problem for natural language processing. Researchers recently took a step toward human-level performance in this task, known as abstractive summarization, as opposed to extractive summarization.
Pipeline for identifying sentences containing evidence of SDIs and SSIs
Machine Learning Research

Hidden Findings Revealed

Drugs undergo rigorous experimentation and clinical trials to gain regulatory approval, while dietary supplements get less scrutiny. Even when a drug study reveals an interaction with supplements, the discovery tends to receive little attention.
DeepPrivacy results on a diverse set of images
Machine Learning Research

Anonymous Faces

A number of countries restrict commercial use of personal data without consent unless they’re fully anonymized. A new paper proposes a way to anonymize images of faces, purportedly without degrading their usefulness in applications that rely on face recognition.

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