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Taeho Kil
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2020 – today
- 2024
- [c4]Hyunjong Ok, Taeho Kil, Sukmin Seo, Jaeho Lee:
SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities. NAACL-HLT 2024: 7725-7737 - [i5]Hyunjong Ok, Taeho Kil, Sukmin Seo, Jaeho Lee:
SCANNER: Knowledge-Enhanced Approach for Robust Multi-modal Named Entity Recognition of Unseen Entities. CoRR abs/2404.01914 (2024) - 2023
- [c3]Taeho Kil, Seonghyeon Kim, Sukmin Seo, Yoonsik Kim, Daehee Kim:
Towards Unified Scene Text Spotting Based on Sequence Generation. CVPR 2023: 15223-15232 - [c2]Geewook Kim, Hodong Lee, Daehee Kim, Haeji Jung, Sanghee Park, Yoonsik Kim, Sangdoo Yun, Taeho Kil, Bado Lee, Seunghyun Park:
Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models. EMNLP 2023: 11989-12010 - [c1]Daehee Kim, Yoonsik Kim, Donghyun Kim
, Yumin Lim, Geewook Kim, Taeho Kil:
SCOB: Universal Text Understanding via Character-wise Supervised Contrastive Learning with Online Text Rendering for Bridging Domain Gap. ICCV 2023: 19505-19516 - [i4]Taeho Kil, Seonghyeon Kim, Sukmin Seo, Yoonsik Kim, Daehee Kim:
Towards Unified Scene Text Spotting based on Sequence Generation. CoRR abs/2304.03435 (2023) - [i3]Geewook Kim, Hodong Lee, Daehee Kim, Haeji Jung, Sanghee Park, Yoonsik Kim, Sangdoo Yun, Taeho Kil, Bado Lee, Seunghyun Park:
Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models. CoRR abs/2305.15080 (2023) - [i2]Daehee Kim, Yoonsik Kim, Donghyun Kim, Yumin Lim, Geewook Kim, Taeho Kil:
SCOB: Universal Text Understanding via Character-wise Supervised Contrastive Learning with Online Text Rendering for Bridging Domain Gap. CoRR abs/2309.12382 (2023) - 2022
- [i1]Seonghyeon Kim, Seung Shin, Yoonsik Kim, Hancheol Cho, Taeho Kil, Jaeheung Surh, Seunghyun Park, Bado Lee, Youngmin Baek:
DEER: Detection-agnostic End-to-End Recognizer for Scene Text Spotting. CoRR abs/2203.05122 (2022)
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last updated on 2024-10-07 21:20 CEST by the dblp team
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