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7 papers · 1 filter
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Hongxiao Wang, Hao Zheng, Jianxu Chen +3
Automatic histopathology image segmentation is crucial to disease analysis. Limited available labeled data hinders the generalizability of trained models under the fully supervised…
Mitigating Bias in Calibration Error Estimation
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens +1
For an AI system to be reliable, the confidence it expresses in its decisions must match its accuracy. To assess the degree of match, examples are typically binned by confidence an…
ABNIRML: Analyzing the Behavior of Neural IR Models
Sean MacAvaney, Sergey Feldman, Nazli Goharian +2
Pretrained contextualized language models such as BERT and T5 have established a new state-of-the-art for ad-hoc search. However, it is not yet well-understood why these methods ar…
Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols
Andrew Head, Kyle Lo, Dongyeop Kang +4
Despite the central importance of research papers to scientific progress, they can be difficult to read. Comprehension is often stymied when the information needed to understand a…
TREC-COVID: Constructing a Pandemic Information Retrieval Test Collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick +6
TREC-COVID is a community evaluation designed to build a test collection that captures the information needs of biomedical researchers using the scientific literature during a pand…
Network Dynamics Governed by Lyapunov Functions: From Memory to Classification
Merav Stern, Eric Shea-Brown
In 1982 John Hopfield published a neural network model for memory retrieval, a model that became a cornerstone in theoretical neuroscience. A key ingredient of the Hopfield model w…