131 citations · 161 across the 12 of their papers we have counts for
21 papers
Program Synthesis via Test-Time Transduction
Kang-il Lee, Jahyun Koo, Seunghyun Yoon +4
We introduce transductive program synthesis, a new formulation of the program synthesis task that explicitly leverages test inputs during synthesis. While prior approaches to progr…
FaithUn: Toward Faithful Forgetting in Language Models by Investigating the Interconnectedness of Knowledge
Nakyeong Yang, Minsung Kim, Seunghyun Yoon +2
Various studies have attempted to remove sensitive or private knowledge from a language model to prevent its unauthorized exposure. However, prior studies have overlooked the compl…
Generating Diverse Hypotheses for Inductive Reasoning
Kang-il Lee, Hyukhun Koh, Dongryeol Lee +3
Inductive reasoning - the process of inferring general rules from a small number of observations - is a fundamental aspect of human intelligence. Recent works suggest that large la…
VLind-Bench: Measuring Language Priors in Large Vision-Language Models
Kang-il Lee, Minbeom Kim, Seunghyun Yoon +4
Large Vision-Language Models (LVLMs) have demonstrated outstanding performance across various multimodal tasks. However, they suffer from a problem known as language prior, where r…
MVMR: A New Framework for Evaluating Faithfulness of Video Moment Retrieval against Multiple Distractors
Nakyeong Yang, Minsung Kim, Seunghyun Yoon +2
With the explosion of multimedia content, video moment retrieval (VMR), which aims to detect a video moment that matches a given text query from a video, has been studied intensive…
How does fake news use a thumbnail? CLIP-based Multimodal Detection on the Unrepresentative News Image
Hyewon Choi, Yejun Yoon, Seunghyun Yoon +1
This study investigates how fake news uses a thumbnail for a news article with a focus on whether a news article's thumbnail represents the news content correctly. A news article s…
Simple Questions Generate Named Entity Recognition Datasets
Hyunjae Kim, Jaehyo Yoo, Seunghyun Yoon +2
Recent named entity recognition (NER) models often rely on human-annotated datasets, requiring the significant engagement of professional knowledge on the target domain and entitie…
KPQA: A Metric for Generative Question Answering Using Keyphrase Weights
Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt +4
In the automatic evaluation of generative question answering (GenQA) systems, it is difficult to assess the correctness of generated answers due to the free-form of the answer. Esp…
Attentive Modality Hopping Mechanism for Speech Emotion Recognition
Seunghyun Yoon, Subhadeep Dey, Hwanhee Lee +1
In this work, we explore the impact of visual modality in addition to speech and text for improving the accuracy of the emotion detection system. The traditional approaches tackle…
Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks
Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim +2
In this study, we propose a novel graph neural network called propagate-selector (PS), which propagates information over sentences to understand information that cannot be inferred…
Surf at MEDIQA 2019: Improving Performance of Natural Language Inference in the Clinical Domain by Adopting Pre-trained Language Model
Jiin Nam, Seunghyun Yoon, Kyomin Jung
While deep learning techniques have shown promising results in many natural language processing (NLP) tasks, it has not been widely applied to the clinical domain. The lack of larg…
Speech Emotion Recognition Using Multi-hop Attention Mechanism
Seunghyun Yoon, Seokhyun Byun, Subhadeep Dey +1
In this paper, we are interested in exploiting textual and acoustic data of an utterance for the speech emotion classification task. The baseline approach models the information fr…
A Compare-Aggregate Model with Latent Clustering for Answer Selection
Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim +2
In this paper, we propose a novel method for a sentence-level answer-selection task that is a fundamental problem in natural language processing. First, we explore the effect of ad…
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Seunghyun Yoon, Kunwoo Park, Joongbo Shin +4
Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume. This…
Multimodal Speech Emotion Recognition Using Audio and Text
Seunghyun Yoon, Seokhyun Byun, Kyomin Jung
Speech emotion recognition is a challenging task, and extensive reliance has been placed on models that use audio features in building well-performing classifiers. In this paper, w…
Comparative Studies of Detecting Abusive Language on Twitter
Younghun Lee, Seunghyun Yoon, Kyomin Jung
The context-dependent nature of online aggression makes annotating large collections of data extremely difficult. Previously studied datasets in abusive language detection have bee…
Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering
Seunghyun Yoon, Joongbo Shin, Kyomin Jung
In this paper, we propose a novel end-to-end neural architecture for ranking candidate answers, that adapts a hierarchical recurrent neural network and a latent topic clustering mo…
Synonym Discovery with Etymology-based Word Embeddings
Seunghyun Yoon, Pablo Estrada, Kyomin Jung
We propose a novel approach to learn word embeddings based on an extended version of the distributional hypothesis. Our model derives word embedding vectors using the etymological…
Efficient Transfer Learning Schemes for Personalized Language Modeling using Recurrent Neural Network
Seunghyun Yoon, Hyeongu Yun, Yuna Kim +2
In this paper, we propose an efficient transfer leaning methods for training a personalized language model using a recurrent neural network with long short-term memory architecture…
Mining the Minds of Customers from Online Chat Logs
Kunwoo Park, Jaewoo Kim, Jaram Park +4
This study investigates factors that may determine satisfaction in customer service operations. We utilized more than 170,000 online chat sessions between customers and agents to i…
GPS Receiver with Enhanced User Positioning Time
Seung-Hyun Yoon, Ji-Woon Jung, Su-Bong Kim +4
This paper introduces a Global Positioning System (GPS) Receiver that locates user's position instantly. Recently, many mobile devices require location information to add user posi…