most citedComparing effectiveness of regularization methods on text classification: Simple and complex model in data shortage situation

1 citations · 1 across the 6 of their papers we have counts for

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6 papers

cs.CV2026

SAM3Dual: A 3rd Place Solution to the MOSEv2 Track, 8th LSVOS Challenge

JeongRae Kim, Chaehyun Kim, Changwon Lim

We present SAM3Dual, our third-place solution to the MOSEv2 track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge at ECCV 2026. SAM3Dual is a training-free infer…

cs.CV2026

Towards Clinically Faithful Medical Image Captioning via Enhanced Vision-Language Alignment

Yunseo Lee, Hyun Jun Kim, Heeseung Shin +1

Medical image captioning is a technique that accelerates early-stage diagnostic workflows and enhances the interpretability of medical diagnostic AI systems. However, unlike genera…

cs.CV2026

Clinically Structured Surrogate Rewards for Post-SFT Medical Image Captioning

Hyun Jun Kim, Heeseung Shin, Changwon Lim

Medical image captioning requires translating heterogeneous visual evidence into concise clinical descriptions, where errors in findings, assertion states, or anatomical relations…

cs.CV2026

SAM2Dual: Training-Free, Dual Memory for Long-Term Video Object Segmentation

JeongRae Kim, Changwon Lim

Long-term video object segmentation (VOS) remains challenging due to error accumulation under extended occlusions, re-appearance, and scene changes. Although SAM2 provides strong z…

cs.CV2026

Continuity-Driven Representation Learning for Industrial Defect Detection

Minjong Kim, Hyun Jun Kim, Jeongrae Kim +2

Industrial defect detection differs from natural-image object detection because inspection images are captured under controlled conditions and contain large normal-dominant regions…

cs.CL20241 cited

Comparing effectiveness of regularization methods on text classification: Simple and complex model in data shortage situation

Jongga Lee, Jaeseung Yim, Seohee Park +1

Text classification is the task of assigning a document to a predefined class. However, it is expensive to acquire enough labeled documents or to label them. In this paper, we stud…