40 citations · 67 across the 12 of their papers we have counts for
13 papers · 1 filter
FaithUn: Toward Faithful Forgetting in Language Models by Investigating the Interconnectedness of Knowledge
Nakyeong Yang, Minsung Kim, Seunghyun Yoon +2
Various studies have attempted to remove sensitive or private knowledge from a language model to prevent its unauthorized exposure. However, prior studies have overlooked the compl…
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…
Deep Exploration of Cross-Lingual Zero-Shot Generalization in Instruction Tuning
Janghoon Han, Changho Lee, Joongbo Shin +3
Instruction tuning has emerged as a powerful technique, significantly boosting zero-shot performance on unseen tasks. While recent work has explored cross-lingual generalization by…
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners
Seonghyeon Ye, Doyoung Kim, Joel Jang +2
Meta-training, which fine-tunes the language model (LM) on various downstream tasks by maximizing the likelihood of the target label given the task instruction and input instance,…
External Knowledge Selection with Weighted Negative Sampling in Knowledge-grounded Task-oriented Dialogue Systems
Janghoon Han, Joongbo Shin, Hosung Song +4
Constructing a robust dialogue system on spoken conversations bring more challenge than written conversation. In this respect, DSTC10-Track2-Task2 is proposed, which aims to build…
TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Joel Jang, Seonghyeon Ye, Changho Lee +5
Language Models (LMs) become outdated as the world changes; they often fail to perform tasks requiring recent factual information which was absent or different during training, a p…
Towards Continual Knowledge Learning of Language Models
Joel Jang, Seonghyeon Ye, Sohee Yang +5
Large Language Models (LMs) are known to encode world knowledge in their parameters as they pretrain on a vast amount of web corpus, which is often utilized for performing knowledg…
KPQA: A Metric for Generative Question Answering Using Keyphrase Weights
Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt +4
In the automatic evaluation of generative question answering (GenQA) systems, it is difficult to assess the correctness of generated answers due to the free-form of the answer. Esp…
Fast and Accurate Deep Bidirectional Language Representations for Unsupervised Learning
Joongbo Shin, Yoonhyung Lee, Seunghyun Yoon +1
Even though BERT achieves successful performance improvements in various supervised learning tasks, applying BERT for unsupervised tasks still holds a limitation that it requires r…
Effective Sentence Scoring Method using Bidirectional Language Model for Speech Recognition
Joongbo Shin, Yoonhyung Lee, Kyomin Jung
In automatic speech recognition, many studies have shown performance improvements using language models (LMs). Recent studies have tried to use bidirectional LMs (biLMs) instead of…
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
Seunghyun Yoon, Kunwoo Park, Joongbo Shin +4
Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume. This…
Improving Neural Question Generation using Answer Separation
Yanghoon Kim, Hwanhee Lee, Joongbo Shin +1
Neural question generation (NQG) is the task of generating a question from a given passage with deep neural networks. Previous NQG models suffer from a problem that a significant p…
Learning to Rank Question-Answer Pairs using Hierarchical Recurrent Encoder with Latent Topic Clustering
Seunghyun Yoon, Joongbo Shin, Kyomin Jung
In this paper, we propose a novel end-to-end neural architecture for ranking candidate answers, that adapts a hierarchical recurrent neural network and a latent topic clustering mo…