1 citations · 1 across the 15 of their papers we have counts for
6 papers · 2 filters
Dynamic Label Name Refinement for Few-Shot Dialogue Intent Classification
Gyutae Park, Ingeol Baek, ByeongJeong Kim +2
Dialogue intent classification aims to identify the underlying purpose or intent of a user's input in a conversation. Current intent classification systems encounter considerable c…
Probing-RAG: Self-Probing to Guide Language Models in Selective Document Retrieval
Ingeol Baek, Hwan Chang, Byeongjeong Kim +2
Retrieval-Augmented Generation (RAG) enhances language models by retrieving and incorporating relevant external knowledge. However, traditional retrieve-and-generate processes may…
Crafting the Path: Robust Query Rewriting for Information Retrieval
Ingeol Baek, Jimin Lee, Joonho Yang +1
Query rewriting aims to generate a new query that can complement the original query to improve the information retrieval system. Recent studies on query rewriting, such as query2do…
Conversational Query Reformulation with the Guidance of Retrieved Documents
Jeonghyun Park, Hwanhee Lee
Conversational search seeks to retrieve relevant passages for the given questions in conversational question answering. Conversational Query Reformulation (CQR) improves conversati…
Low-Resource Cross-Lingual Summarization through Few-Shot Learning with Large Language Models
Gyutae Park, Seojin Hwang, Hwanhee Lee
Cross-lingual summarization (XLS) aims to generate a summary in a target language different from the source language document. While large language models (LLMs) have shown promisi…
KoCoSa: Korean Context-aware Sarcasm Detection Dataset
Yumin Kim, Heejae Suh, Mingi Kim +2
Sarcasm is a way of verbal irony where someone says the opposite of what they mean, often to ridicule a person, situation, or idea. It is often difficult to detect sarcasm in the d…