Papers by Juyeon Heo

2 papers
On Evaluating LLMs’ Capabilities as Functional Approximators: A Bayesian Evaluation Framework (2025.coling-main)

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Challenge: Large Language Models (LLMs) have revolutionized the way we can formulate tasks in text-in-text-out format.
Approach: They propose a new evaluation framework to comprehensively assess LLMs’ function modeling abilities by adopting a Bayesian perspective of function modeling.
Outcome: The proposed evaluation framework enables LLMs to excel in utilizing prior knowledge to develop a strong understanding of the underlying function.
LLMs on interactive feature collections with implicit dynamic decision strategy (2025.coling-main)

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Challenge: Large Language Models (LLMs) struggle to efficiently narrow down the search space . external engineered systems may not fully utilize the inherent problem-solving capabilities of LLMs .
Approach: They propose to implicitly guide Large Language Models to enhance their interactive feature collection abilities within a single prompt.
Outcome: The proposed approach improves the performance of large language models in real-world scenarios.

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