Search Results for author: Doo Soon Kim

Found 24 papers, 12 papers with code

CAISE: Conversational Agent for Image Search and Editing

1 code implementation24 Feb 2022 Hyounghun Kim, Doo Soon Kim, Seunghyun Yoon, Franck Dernoncourt, Trung Bui, Mohit Bansal

To our knowledge, this is the first dataset that provides conversational image search and editing annotations, where the agent holds a grounded conversation with users and helps them to search and edit images according to their requests.

Image Retrieval

End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline

no code implementations4 Jul 2021 Tuan Manh Lai, Trung Bui, Doo Soon Kim

Since the first end-to-end neural coreference resolution model was introduced, many extensions to the model have been proposed, ranging from using higher-order inference to directly optimizing evaluation metrics using reinforcement learning.


Learning to Fuse Sentences with Transformers for Summarization

1 code implementation EMNLP 2020 Logan Lebanoff, Franck Dernoncourt, Doo Soon Kim, Lidan Wang, Walter Chang, Fei Liu

The ability to fuse sentences is highly attractive for summarization systems because it is an essential step to produce succinct abstracts.

Sentence Sentence Fusion

DSTC8-AVSD: Multimodal Semantic Transformer Network with Retrieval Style Word Generator

no code implementations1 Apr 2020 Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Kyomin Jung

Audio Visual Scene-aware Dialog (AVSD) is the task of generating a response for a question with a given scene, video, audio, and the history of previous turns in the dialog.

Decoder Retrieval +1

A Multimodal Dialogue System for Conversational Image Editing

no code implementations16 Feb 2020 Tzu-Hsiang Lin, Trung Bui, Doo Soon Kim, Jean Oh

In this paper, we present a multimodal dialogue system for Conversational Image Editing.

Analyzing Sentence Fusion in Abstractive Summarization

no code implementations WS 2019 Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu

While recent work in abstractive summarization has resulted in higher scores in automatic metrics, there is little understanding on how these systems combine information taken from multiple document sentences.

Abstractive Text Summarization Sentence +1

Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks

1 code implementation LREC 2020 Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Kyomin Jung

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 when considering sentences in isolation.

Answer Selection Graph Neural Network +1

A Compare-Aggregate Model with Latent Clustering for Answer Selection

no code implementations30 May 2019 Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Kyomin Jung

In this paper, we propose a novel method for a sentence-level answer-selection task that is a fundamental problem in natural language processing.

Answer Selection Clustering +3

Detecting Table Region in PDF Documents Using Distant Supervision

no code implementations29 Jun 2015 Miao Fan, Doo Soon Kim

Extensive evaluations demonstrate that our paradigm is compatible enough to leverage various features and learning models for open-domain table region detection within PDF files.

Table Detection Table Recognition

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