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Visually Dehallucinative Instruction Generation: Know What You Don't Know

Autor: Cha, Sungguk, Lee, Jusung, Lee, Younghyun, Yang, Cheoljong

"When did the emperor Napoleon invented iPhone?" Such hallucination-inducing question is well known challenge in generative language modeling. In this study, we present an innovative concept of visual hallucination, referred to as "I Know (IK)" hallu

Externí odkaz: http://arxiv.org/abs/2402.09717

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Visual Question Answering Instruction: Unlocking Multimodal Large Language Model To Domain-Specific Visual Multitasks

Autor: Lee, Jusung, Cha, Sungguk, Lee, Younghyun, Yang, Cheoljong

Having revolutionized natural language processing (NLP) applications, large language models (LLMs) are expanding into the realm of multimodal inputs. Owing to their ability to interpret images, multimodal LLMs (MLLMs) have been primarily used for vis

Externí odkaz: http://arxiv.org/abs/2402.08360

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Visually Dehallucinative Instruction Generation

Autor: Cha, Sungguk, Lee, Jusung, Lee, Younghyun, Yang, Cheoljong

In recent years, synthetic visual instructions by generative language model have demonstrated plausible text generation performance on the visual question-answering tasks. However, challenges persist in the hallucination of generative language models

Externí odkaz: http://arxiv.org/abs/2402.08348

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Akademický článek

Dual-Coated Antireflective Film for Flexible and Robust Multi-Environmental Optoelectronic Applications

Autor: Hyuk Jae Jang, Jaemin Jeon, Joo Ho Yun, Iqbal Shudha Tasnim, Soyeon Han, Heeyoung Lee, Sungguk An, Seungbeom Kang, Dongyeon Kim, Young Min Song

Publikováno v: Biomimetics, Vol 9, Iss 10, p 644 (2024)

Artificial antireflective nanostructured surfaces, inspired by moth eyes, effectively reduce optical losses at interfaces, offering significant advantages in enhancing optical performance in various optoelectronic applications, including solar cells,

Externí odkaz: https://doaj.org/article/9286ff7f863e404c8bcef234e29c01cb

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Zero-Shot Semantic Segmentation via Spatial and Multi-Scale Aware Visual Class Embedding

Autor: Cha, Sungguk, Wang, Yooseung

Fully supervised semantic segmentation technologies bring a paradigm shift in scene understanding. However, the burden of expensive labeling cost remains as a challenge. To solve the cost problem, recent studies proposed language model based zero-sho

Externí odkaz: http://arxiv.org/abs/2111.15181

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