activity
20162021
most citedCombining LSTM and Latent Topic Modeling for Mortality Prediction

25 citations · 27 across the 6 of their papers we have counts for

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Showing cs.CLShow all

7 papers · 1 filter

cs.CL2021

Knowledge-Enhanced Evidence Retrieval for Counterargument Generation

Yohan Jo, Haneul Yoo, JinYeong Bak +3

Finding counterevidence to statements is key to many tasks, including counterargument generation. We build a system that, given a statement, retrieves counterevidence from diverse…

cs.CL20211 cited

Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes

Yohan Jo, Seojin Bang, Chris Reed +1

While argument mining has achieved significant success in classifying argumentative relations between statements (support, attack, and neutral), we have a limited computational und…

cs.CL2020

Detecting Attackable Sentences in Arguments

Yohan Jo, Seojin Bang, Emaad Manzoor +2

Finding attackable sentences in an argument is the first step toward successful refutation in argumentation. We present a first large-scale analysis of sentence attackability in on…

cs.CL20201 cited

Extracting Implicitly Asserted Propositions in Argumentation

Yohan Jo, Jacky Visser, Chris Reed +1

Argumentation accommodates various rhetorical devices, such as questions, reported speech, and imperatives. These rhetorical tools usually assert argumentatively relevant propositi…

cs.CL2018

Attentive Interaction Model: Modeling Changes in View in Argumentation

Yohan Jo, Shivani Poddar, Byungsoo Jeon +3

We present a neural architecture for modeling argumentative dialogue that explicitly models the interplay between an Opinion Holder's (OH's) reasoning and a challenger's argument,…

cs.CL201725 cited

Combining LSTM and Latent Topic Modeling for Mortality Prediction

Yohan Jo, Lisa Lee, Shruti Palaskar

There is a great need for technologies that can predict the mortality of patients in intensive care units with both high accuracy and accountability. We present joint end-to-end ne…