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publications

Evaluating Prior Knowledge of ARC Using World Models

Published in KSC, 2023

In this study, we propose a new method that uses the World Model algorithm to analyze the influence of prior knowledge when solving the ARC benchmark, as well as the types of prior knowledge included in the ARC.

Recommended citation: https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11705080&googleIPSandBox=false&mark=0&ipRange=false&b2cLoginYN=false&aiChatView=A&readTime=5-10&isPDFSizeAllowed=true&accessgl=Y&language=ko_KR&hasTopBanner=true

Extracting the core knowledge of ARC with the World Model

Published in KSC, 2023

In this study, we design an experiment to verify that the World Model extracts core knowledge from the ARC dataset, and propose future research directions for utilizing this extracted core knowledge.

Recommended citation: https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE11705335&googleIPSandBox=false&mark=0&ipRange=false&b2cLoginYN=false&aiChatView=A&readTime=5-10&isPDFSizeAllowed=true&accessgl=Y&language=ko_KR&hasTopBanner=true

Published in , 1900

Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus

Published in ACM TIST submitted, 2024

The existing methods for evaluating the inference abilities of Large Language Models (LLMs) have been results-centric, making it difficult to assess the inference process. We introduce a new approach using the Abstract and Reasoning Corpus (ARC) dataset to evaluate the inference and contextual understanding abilities of large language models in a process-centric manner. ARC demands rigorous logical structures for problem-solving, making it a benchmark that facilitates the comparison of model inference abilities with humans. Experimental results confirm that while large language models possess weak inference abilities, they still lag in terms of logical coherence, compositionality, and productivity. Our experiments highlight the reasoning capabilities of LLMs, proposing development paths for achieving human-level reasoning.

Recommended citation: https://arxiv.org/abs/2403.11793

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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