Papers by Hyejeong Jeon

2 papers
Open-World Planning via Lifted Regression with LLM-Inferred Affordances for Embodied Agents (2025.acl-long)

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Challenge: Existing open-world planning methods rely on closed-world assumption (CWA) symbolic planners face combinatorial explosion of states and actions due to reliance on grounding.
Approach: They propose an open-world planning approach integrating lifted regression with LLM-generated affordances.
Outcome: The proposed approach outperforms state-of-the-art LLM planners and a grounded planner on three benchmarks.
Overlapping Context with Variable-Length Stride Increases Diversity when Training Large Language Model for Code (2025.acl-industry)

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Challenge: Large language models for code (LLMs) are gaining more and more attention due to their wide applicability.
Approach: They propose a method which extracts overlapping contexts from training data using variable-length stride.
Outcome: The proposed method outperforms the conventional approach of controlling the number of epochs in terms of the pass@k rate.

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