Papers by Jaehong Kim

5 papers
Parallel Communities Across the Surface Web and the Dark Web (2025.findings-emnlp)

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Challenge: Sense of Community is a social motivation that is reflected in the social behavior of humans.
Approach: They compile a large collection of parallel community datasets comprising over 7 million posts and comments from Reddit and 200,000 posts and comment from Dread, a dark web discussion forum, covering similar topics.
Outcome: The results show that users on Reddit exhibit a stronger sense of community membership despite the dark web’s restricted accessibility.
Machine Behavior in Relational Moral Dilemmas: Moral Rightness, Predicted Human Behavior, and Model Decisions (2026.findings-acl)

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Challenge: Human moral judgment is context-dependent and changes based on interpersonal relationships.
Approach: They characterize LLM behavior using the Whistleblower’s Dilemma . they find moral rightness remains consistently fairness-oriented .
Outcome: The model decisions mirror moral rightness judgments, rather than their behavioral predictions.
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.
How Do Moral Emotions Shape Political Participation? A Cross-Cultural Analysis of Online Petitions Using Language Models (2024.findings-acl)

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Challenge: Using cross-cultural online petition data, we examine how moral emotions influence user participation and political participation.
Approach: They construct and share a moral emotion dataset comprising 50,000 petition sentences in Korean and English each, along with emotion labels annotated by a fine-tuned LLM.
Outcome: The results show that moral emotions like other-suffering increase both forms of participation and help petitions go viral, while self-conscious have the opposite effect.
Carpe diem: On the Evaluation of World Knowledge in Lifelong Language Models (2024.naacl-long)

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Challenge: Current language models are trained on static data, implying that the encoded knowledge could go wrong as time passes.
Approach: They propose a temporally evolving question-answering benchmark for language models . they use Wikipedia databases to test language models for dynamic knowledge in ever-changing world .
Outcome: The proposed task aims to model the evolution-adaptability of language models in the real world.

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