Papers by YeonJoon Jung
Debiasing Event Understanding for Visual Commonsense Tasks (2022.findings-acl)
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| Challenge: | a recent study shows that object-based event understanding is purely likelihood-based, leading to incorrect event prediction. |
| Approach: | They propose to mitigate object-based event understanding by optimizing aggregation with association-based prediction. |
| Outcome: | The proposed approach improves visual commonsense reasoning tasks by combining do-calculus with association-based prediction. |
COMMIT: Code-Mixing English-Centric Large Language Model for Multilingual Instruction Tuning (2024.findings-naacl)
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| Challenge: | COMMIT improves the exact match score of low-resource language QA by 32x. |
| Approach: | They propose to specialize instruction tuning to deviate from English-centric instruction tuning . they propose to perform cross-lingual alignment to overcome data imbalance . |
| Outcome: | The proposed method improves the exact match score of low-resource language QA by 32x. |
Interventional Speech Noise Injection for ASR Generalizable Spoken Language Understanding (2024.emnlp-main)
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| Challenge: | Existing methods to increase the robustness of pre-trained language models (PLMs) against unseen ASR systems produce noisy inputs for SLU models, which can significantly degrade their performance. |
| Approach: | They propose to introduce ASR-plausible noises into pre-trained language models by cutting off the non-causal effect of noises. |
| Outcome: | The proposed method improves the robustness and generalizability of SLU models against unseen ASR systems by cutting off the non-causal effect of noises. |