1 citations · 1 across the 5 of their papers we have counts for
5 papers
K-EXAONE 2.0 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +74
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundatio…
EXAONE 4.5 Technical Report
Eunbi Choi, Kibong Choi, Sehyun Chun +55
This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…
Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection
Kwangrok Ryoo, Yeonsik Jo, Seungjun Lee +5
For object detection task with noisy labels, it is important to consider not only categorization noise, as in image classification, but also localization noise, missing annotations…
Misalign, Contrast then Distill: Rethinking Misalignments in Language-Image Pretraining
Bumsoo Kim, Yeonsik Jo, Jinhyung Kim +1
Contrastive Language-Image Pretraining has emerged as a prominent approach for training vision and text encoders with uncurated image-text pairs from the web. To enhance data-effic…
Expediting Contrastive Language-Image Pretraining via Self-distilled Encoders
Bumsoo Kim, Jinhyung Kim, Yeonsik Jo +1
Recent advances in vision language pretraining (VLP) have been largely attributed to the large-scale data collected from the web. However, uncurated dataset contains weakly correla…