12 citations · 14 across the 5 of their papers we have counts for
5 papers
Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language Models
Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim +8
Algorithmic reasoning refers to the ability to understand the complex patterns behind the problem and decompose them into a sequence of reasoning steps towards the solution. Such n…
Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents
Hyungjoo Chae, Yongho Song, Kai Tzu-iunn Ong +6
Human-like chatbots necessitate the use of commonsense reasoning in order to effectively comprehend and respond to implicit information present within conversations. Achieving such…
CoTEVer: Chain of Thought Prompting Annotation Toolkit for Explanation Verification
Seungone Kim, Se June Joo, Yul Jang +2
Chain-of-thought (CoT) prompting enables large language models (LLMs) to solve complex reasoning tasks by generating an explanation before the final prediction. Despite it's promis…
TUTORING: Instruction-Grounded Conversational Agent for Language Learners
Hyungjoo Chae, Minjin Kim, Chaehyeong Kim +4
In this paper, we propose Tutoring bot, a generative chatbot trained on a large scale of tutor-student conversations for English-language learning. To mimic a human tutor's behavio…
Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization
Seungone Kim, Se June Joo, Hyungjoo Chae +3
In this paper, we propose to leverage the unique characteristics of dialogues sharing commonsense knowledge across participants, to resolve the difficulties in summarizing them. We…