Papers by Dongjun Min

2 papers
Persona Dynamics: Unveiling the Impact of Persona Traits on Agents in Text-Based Games (2025.acl-long)

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Challenge: Text-based interactive environments have long presented formidable challenges for AI.
Approach: They propose a method for projecting human personality traits onto agents to guide their behavior and integrate them into their policy-learning pipelines.
Outcome: The proposed method induces personality in a text-based game agent by integrating personality profiles directly into the agent's policy-learning pipeline.
Multimodal UNcommonsense: From Odd to Ordinary and Ordinary to Odd (2025.findings-emnlp)

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Challenge: Multimodal UNcommonsense (MUN) is a benchmark designed to evaluate models’ ability to handle scenarios that deviate from typical visual or contextual expectations.
Approach: They propose a retrieval-based in-context learning framework that transfers reasoning capabilities from larger models to smaller ones without additional training.
Outcome: The proposed method improves on baseline ICL methods by 8.3% over previous methods.

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