35 citations · 48 across the 5 of their papers we have counts for
7 papers · 1 filter
Are Pre-trained Language Models Aware of Phrases? Simple but Strong Baselines for Grammar Induction
Taeuk Kim, Jihun Choi, Daniel Edmiston +1
With the recent success and popularity of pre-trained language models (LMs) in natural language processing, there has been a rise in efforts to understand their inner workings. In…
A Cross-Sentence Latent Variable Model for Semi-Supervised Text Sequence Matching
Jihun Choi, Taeuk Kim, Sang-goo Lee
We present a latent variable model for predicting the relationship between a pair of text sequences. Unlike previous auto-encoding--based approaches that consider each sequence sep…
SNU_IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification
Sanghwan Bae, Jihun Choi, Sang-goo Lee
We present several techniques to tackle the mismatch in class distributions between training and test data in the Contextual Emotion Detection task of SemEval 2019, by extending th…
Dynamic Compositionality in Recursive Neural Networks with Structure-aware Tag Representations
Taeuk Kim, Jihun Choi, Daniel Edmiston +2
Most existing recursive neural network (RvNN) architectures utilize only the structure of parse trees, ignoring syntactic tags which are provided as by-products of parsing. We pres…
Cell-aware Stacked LSTMs for Modeling Sentences
Jihun Choi, Taeuk Kim, Sang-goo Lee
We propose a method of stacking multiple long short-term memory (LSTM) layers for modeling sentences. In contrast to the conventional stacked LSTMs where only hidden states are fed…
SNU_IDS at SemEval-2018 Task 12: Sentence Encoder with Contextualized Vectors for Argument Reasoning Comprehension
Taeuk Kim, Jihun Choi, Sang-goo Lee
We present a novel neural architecture for the Argument Reasoning Comprehension task of SemEval 2018. It is a simple neural network consisting of three parts, collectively judging…