21 citations · 38 across the 15 of their papers we have counts for
7 papers · 1 filter
Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models
Dohyun Lee, Daniel Rim, Minseok Choi +1
Although language models (LMs) demonstrate exceptional capabilities on various tasks, they are potentially vulnerable to extraction attacks, which represent a significant privacy r…
Translation Deserves Better: Analyzing Translation Artifacts in Cross-lingual Visual Question Answering
ChaeHun Park, Koanho Lee, Hyesu Lim +5
Building a reliable visual question answering~(VQA) system across different languages is a challenging problem, primarily due to the lack of abundant samples for training. To addre…
SimCKP: Simple Contrastive Learning of Keyphrase Representations
Minseok Choi, Chaeheon Gwak, Seho Kim +2
Keyphrase generation (KG) aims to generate a set of summarizing words or phrases given a source document, while keyphrase extraction (KE) aims to identify them from the text. Becau…
PRiSM: Enhancing Low-Resource Document-Level Relation Extraction with Relation-Aware Score Calibration
Minseok Choi, Hyesu Lim, Jaegul Choo
Document-level relation extraction (DocRE) aims to extract relations of all entity pairs in a document. A key challenge in DocRE is the cost of annotating such data which requires…
Learning to Diversify Neural Text Generation via Degenerative Model
Jimin Hong, ChaeHun Park, Jaegul Choo
Neural language models often fail to generate diverse and informative texts, limiting their applicability in real-world problems. While previous approaches have proposed to address…
DEnsity: Open-domain Dialogue Evaluation Metric using Density Estimation
ChaeHun Park, Seungil Chad Lee, Daniel Rim +1
Despite the recent advances in open-domain dialogue systems, building a reliable evaluation metric is still a challenging problem. Recent studies proposed learnable metrics based o…