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Found 14 papers, 0 papers with code
Operationalizing the Legal Principle of Data Minimization for Personalization
Article 5(1)(c) of the European Union's General Data Protection Regulation (GDPR) requires that "personal data shall be [...] adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed (`data minimisation')".
Playing log(N)-Questions over Sentences
We propose a two-agent game wherein a questioner must be able to conjure discerning questions between sentences, incorporate responses from an answerer, and keep track of a hypothesis state.
Ranking Passages for Argument Convincingness
We detail the process of extracting topical passages for queries submitted to a search engine, creating annotated sets of passages aligned to different stances on a topic, and assessing argument convincingness of passages using pairwise annotation.
The Effect of Downstream Classification Tasks for Evaluating Sentence Embeddings
One popular method for quantitatively evaluating the utility of sentence embeddings involves using them in downstream language processing tasks that require sentence representations as input.
Length, Interchangeability, and External Knowledge: Observations from Predicting Argument Convincingness
In this work, we provide insight into three key aspects related to predicting argument convincingness.
Towards Debate Automation: a Recurrent Model for Predicting Debate Winners
In this paper we introduce a practical first step towards the creation of an automated debate agent: a state-of-the-art recurrent predictive model for predicting debate winners.
Tracking Bias in News Sources Using Social Media: the Russia-Ukraine Maidan Crisis of 2013--2014
We show that on the task of predicting which side is likely to prefer a given article, a Naive Bayes classifier can record 90. 3{\%} accuracy looking only at domain names of the news sources.
SemEval-2017 Task 6: \#HashtagWars: Learning a Sense of Humor
This paper describes a new shared task for humor understanding that attempts to eschew the ubiquitous binary approach to humor detection and focus on comparative humor ranking instead.
Here's My Point: Joint Pointer Architecture for Argument Mining
One of the major goals in automated argumentation mining is to uncover the argument structure present in argumentative text.
#HashtagWars: Learning a Sense of Humor
Our best supervised system achieved 63. 7% accuracy, suggesting that this task is much more difficult than comparable humor detection tasks.
Evaluating Creative Language Generation: The Case of Rap Lyric Ghostwriting
The goal of this paper is to develop evaluation methods for one such task, ghostwriting of rap lyrics, and to provide an explicit, quantifiable foundation for the goals and future directions of this task.
