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Found 6 papers, 4 papers with code
Modeling Label Semantics for Predicting Emotional Reactions
Predicting how events induce emotions in the characters of a story is typically seen as a standard multi-label classification task, which usually treats labels as anonymous classes to predict.
Ranked #1 on
Emotion Classification
on ROCStories
Author's Sentiment Prediction
We introduce PerSenT, a dataset of crowd-sourced annotations of the sentiment expressed by the authors towards the main entities in news articles.
SuMe: A Dataset Towards Summarizing Biomedical Mechanisms
We leverage this structure and create a summarization task, where the input is a collection of sentences and the main entities in an abstract, and the output includes the relationship and a sentence that summarizes the mechanism.
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples
We introduce a novel semi-supervised procedure that bootstraps an NLI dataset from existing biomedical dataset that pairs mechanisms with experimental evidence in abstracts.
Ranked #1 on
Natural Language Inference
on BioNLI
Neural Machine Translation on Scarce-Resource Condition: A case-study on Persian-English
This new loss function yields a total of 1. 87 point improvements in terms of BLEU score in the translation quality.
A Preordered RNN Layer Boosts Neural Machine Translation in Low Resource Settings
Neural Machine Translation (NMT) models are strong enough to convey semantic and syntactic information from the source language to the target language.
