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Found 5 papers, 1 papers with code
Copula-Based Deep Survival Models for Dependent Censoring
A survival dataset describes a set of instances (e. g. patients) and provides, for each, either the time until an event (e. g. death), or the censoring time (e. g. when lost to follow-up - which is a lower bound on the time until the event).
MOMA: Multi-Object Multi-Actor Activity Parsing
This paper introduces Activity Parsing as the overarching task of temporal segmentation and classification of activities, sub-activities, atomic actions, along with an instance-level understanding of actors, objects, and their relationships in videos.
CompLex --- A New Corpus for Lexical Complexity Prediction from Likert Scale Data
Predicting which words are considered hard to understand for a given target population is a vital step in many NLP applications such astext simplification.
CombiNMT: An Exploration into Neural Text Simplification Models
This work presents a replication study of Exploring Neural Text Simplification Models (Nisioi et al., 2017).
CompLex: A New Corpus for Lexical Complexity Prediction from Likert Scale Data
With a few exceptions, previous studies have approached the task as a binary classification task in which systems predict a complexity value (complex vs. non-complex) for a set of target words in a text.
