Papers by Kihyuk Sohn

2 papers
Where is the answer? An empirical study of positional bias for parametric knowledge extraction in language model (2025.naacl-long)

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Challenge: Language model (LM) stores diverse factual knowledge in their parameters, which is learned during self-supervised training on unlabeled documents.
Approach: They investigate the issue of "perplexity curse" in the continued training of language model (LM) they find that all studied LMs suffer from positional bias in the training document .
Outcome: The proposed model is able to extract information from multiple questions with diverse queries.
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction (2023.acl-long)

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Challenge: Existing approaches that extend the mask language modeling to other modalities require careful multi-task tuning, complex reconstruction target designs, or additional pre-training data.
Approach: They propose a centralized multimodal graph contrastive learning strategy to unify self-supervised pre-training for all modalities in one loss.
Outcome: The proposed model achieves state-of-the-art performance on FUNSD, CORD, SROIE and Payment benchmarks with a more compact model size.

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