Papers by Minjoon Jung
Two Examples are Better than One: Context Regularization for Gradient-based Prompt Tuning (2023.findings-acl)
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| Challenge: | Prompting has gained tremendous attention as an efficient method for the adaptation of large-scale language models. |
| Approach: | They propose a regularization method that guides a prompt to produce a task context properly. |
| Outcome: | The proposed method improves prediction performance in a zero-shot in-context learning setting without demonstration examples for in-constitu learning. |
Modal-specific Pseudo Query Generation for Video Corpus Moment Retrieval (2022.emnlp-main)
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| Challenge: | Existing studies have shown promising results in video corpus moment retrieval . however, they relied on the expensive query annotations for the VCMR . |
| Approach: | They propose a self-supervised learning framework to localize video corpus moment without annotations. |
| Outcome: | The proposed framework can localize the video corpus moment without any explicit annotation on TVR dataset. |
Confidence-guided Refinement Reasoning for Zero-shot Question Answering (2025.emnlp-main)
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| Challenge: | Existing frameworks that generate single-step reasoning do not improve QA reasoning . |
| Approach: | They propose a framework that strategically constructs and refines sub-questions and their answers (sub-QAs) they argue that sub-QA does not always enhance QA reasoning . |
| Outcome: | The proposed framework can be integrated with existing QA models and benchmarks. |