Search Results for author:
Found 8 papers, 3 papers with code
QPaug: Question and Passage Augmentation for Open-Domain Question Answering of LLMs
In addition, to compensate for the case where the retrieved passages contain distracting information or divided opinions, we augment the retrieved passages with self-generated passages by LLMs to guide the answer extraction.
Factual Error Correction for Abstractive Summaries Using Entity Retrieval
In this paper, we propose an efficient factual error correction system RFEC based on entities retrieval post-editing process.
CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models
Specifically, we employ a two-stage augmentation pipeline to generate new claims and evidences from existing samples.
Fast End-to-end Coreference Resolution for Korean
Recently, end-to-end neural network-based approaches have shown significant improvements over traditional pipeline-based models in English coreference resolution.
KNU-HYUNDAI's NMT system for Scientific Paper and Patent Tasks onWAT 2019
In this paper, we describe the neural machine translation (NMT) system submitted by the Kangwon National University and HYUNDAI (KNU-HYUNDAI) team to the translation tasks of the 6th workshop on Asian Translation (WAT 2019).
ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples
This paper describes our system, Joint Encoders for Stable Suggestion Inference (JESSI), for the SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums.
SEx BiST: A Multi-Source Trainable Parser with Deep Contextualized Lexical Representations
We describe the SEx BiST parser (Semantically EXtended Bi-LSTM parser) developed at Lattice for the CoNLL 2018 Shared Task (Multilingual Parsing from Raw Text to Universal Dependencies).
KNU CI System at SemEval-2018 Task4: Character Identification by Solving Sequence-Labeling Problem
Character identification is an entity-linking task that finds words referring to the same person among the nouns mentioned in a conversation and turns them into one entity.
