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Taebaek Hwang

7 accepted papers

2025

Do You Keep an Eye on What I Ask? Mitigating Multimodal Hallucination via Attention-Guided Ensemble Decoding

ICLR 2025poster

Recent advancements in Large Vision-Language Models (LVLMs) have significantly expanded their utility in tasks like image captioning and visual question answering. However, they still struggle with object hallucination, where models generate descriptions that inaccurately reflect the visual content…

Cited by 0SourcePDFScholar
2025

KRETA: A Benchmark for Korean Reading and Reasoning in Text-Rich VQA Attuned to Diverse Visual Contexts

EMNLP 2025

Understanding and reasoning over text within visual contexts poses a significant challenge for Vision-Language Models (VLMs), given the complexity and diversity of real-world scenarios. To address this challenge, text-rich Visual Question Answering (VQA) datasets and benchmarks have emerged for high

2024

On Train-Test Class Overlap and Detection for Image Retrieval

CVPR 2024poster

How important is it for training and evaluation sets to not have class overlap in image retrieval? We revisit Google Landmarks v2 clean the most popular training set by identifying and removing class overlap with Revisited Oxford and Paris the most popular training set. By comparing the original and…

Cited by 7SourcePDFScholar
2024

SyncMask: Synchronized Attentional Masking for Fashion-centric Vision-Language Pretraining

CVPR 2024poster

Vision-language models (VLMs) have made significant strides in cross-modal understanding through large-scale paired datasets. However in fashion domain datasets often exhibit a disparity between the information conveyed in image and text. This issue stems from datasets containing multiple images of…

Cited by 9SourcePDFScholar
2023

Conditional Cross Attention Network for Multi-Space Embedding without Entanglement in Only a SINGLE Network

ICCV 2023poster

Many studies in vision tasks have aimed to create effective embedding spaces for single-label object prediction within an image. However, in reality, most objects possess multiple specific attributes, such as shape, color, and length, with each attribute composed of various classes. To apply models…

Cited by 2PDFScholar
2022

GRIT-VLP: Grouped Mini-Batch Sampling for Efficient Vision and Language Pre-training

ECCV 2022poster

"Most of the currently existing vision and language pre-training (VLP) methods have mainly focused on how to extract and align vision and text features. In contrast to the mainstream VLP methods, we highlight that two routinely applied steps during pre-training have crucial impact on the performance…

2021

CPR: Classifier-Projection Regularization for Continual Learning

ICLR 2021poster

We propose a general, yet simple patch that can be applied to existing regularization-based continual learning methods called classifier-projection regularization (CPR). Inspired by both recent results on neural networks with wide local minima and information theory, CPR adds an additional regulariz…