Papers by Hyejeong Jeon
Open-World Planning via Lifted Regression with LLM-Inferred Affordances for Embodied Agents (2025.acl-long)
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Xiaotian Liu, Ali Pesaranghader, Hanze Li, Punyaphat Sukcharoenchaikul, Jaehong Kim, Tanmana Sadhu, Hyejeong Jeon, Scott Sanner
| 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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Geonmo Gu, Jaeho Kwak, Haksoo Moon, Hyun Seung Shim, Yu Jin Kim, Byoungjip Kim, Moontae Lee, Hyejeong Jeon
| 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. |