1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2026
Train Overcomplete, Deploy Compact: Scaling Recovery Capacity for Structured LLM Pruning
Seungmin Oh, Donggeon Lee, Jongbin Ryu
Large language models achieve strong performance across diverse tasks, but deployment remains costly because of memory, latency, and energy demands. Structured pruning reduces thes…
cs.CV2026
Re-calibrated Contrastive Loss for Transformation-Aware Prompt Conditioning in Vision-Language Models
Seungmin Oh, Seunghun Kang, Jongbin Ryu
Ensuring effective transfer learning for vision-language models without compromising their generalization performance is crucial. However, many existing methods overlook data chara…
cs.CV2023★ 1 cited
Fine-Grained Self-Supervised Learning with Jigsaw Puzzles for Medical Image Classification
Wongi Park, Jongbin Ryu
Classifying fine-grained lesions is challenging due to minor and subtle differences in medical images. This is because learning features of fine-grained lesions with highly minor d…