1 citations · 2 across the 4 of their papers we have counts for
5 papers
Coffee-Gym: An Environment for Evaluating and Improving Natural Language Feedback on Erroneous Code
Hyungjoo Chae, Taeyoon Kwon, Seungjun Moon +7
This paper presents Coffee-Gym, a comprehensive RL environment for training models that provide feedback on code editing. Coffee-Gym includes two major components: (1) Coffee, a da…
BotsTalk: Machine-sourced Framework for Automatic Curation of Large-scale Multi-skill Dialogue Datasets
Minju Kim, Chaehyeong Kim, Yongho Song +2
To build open-domain chatbots that are able to use diverse communicative skills, we propose a novel framework BotsTalk, where multiple agents grounded to the specific target skills…
Dual Task Framework for Improving Persona-grounded Dialogue Dataset
Minju Kim, Beong-woo Kwak, Youngwook Kim +3
This paper introduces a simple yet effective data-centric approach for the task of improving persona-conditioned dialogue agents. Prior model-centric approaches unquestioningly dep…
TrustAL: Trustworthy Active Learning using Knowledge Distillation
Beong-woo Kwak, Youngwook Kim, Yu Jin Kim +2
Active learning can be defined as iterations of data labeling, model training, and data acquisition, until sufficient labels are acquired. A traditional view of data acquisition is…
Meta-path Free Semi-supervised Learning for Heterogeneous Networks
Shin-woo Park, Byung Jun Bae, Jinyoung Yeo +1
Graph neural networks (GNNs) have been widely used in representation learning on graphs and achieved superior performance in tasks such as node classification. However, analyzing h…