activity
20202022
most citedCollaborative Training of GANs in Continuous and Discrete Spaces for Text Generation

2 citations · 6 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CL20221 cited

Medical Question Understanding and Answering with Knowledge Grounding and Semantic Self-Supervision

Khalil Mrini, Harpreet Singh, Franck Dernoncourt +5

Current medical question answering systems have difficulty processing long, detailed and informally worded questions submitted by patients, called Consumer Health Questions (CHQs).…

cs.CL2022

Factual Error Correction for Abstractive Summaries Using Entity Retrieval

Hwanhee Lee, Cheoneum Park, Seunghyun Yoon +4

Despite the recent advancements in abstractive summarization systems leveraged from large-scale datasets and pre-trained language models, the factual correctness of the summary is…

cs.CL2022

CAISE: Conversational Agent for Image Search and Editing

Hyounghun Kim, Doo Soon Kim, Seunghyun Yoon +3

Demand for image editing has been increasing as users' desire for expression is also increasing. However, for most users, image editing tools are not easy to use since the tools re…

cs.CL20221 cited

MACRONYM: A Large-Scale Dataset for Multilingual and Multi-Domain Acronym Extraction

Amir Pouran Ben Veyseh, Nicole Meister, Seunghyun Yoon +3

Acronym extraction is the task of identifying acronyms and their expanded forms in texts that is necessary for various NLP applications. Despite major progress for this task in rec…

cs.CL2021

Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning

Jianguo Zhang, Trung Bui, Seunghyun Yoon +6

In this work, we focus on a more challenging few-shot intent detection scenario where many intents are fine-grained and semantically similar. We present a simple yet effective few-…

cs.CL2021

QACE: Asking Questions to Evaluate an Image Caption

Hwanhee Lee, Thomas Scialom, Seunghyun Yoon +2

In this paper, we propose QACE, a new metric based on Question Answering for Caption Evaluation. QACE generates questions on the evaluated caption and checks its content by asking…