3 papers
cs.CV2026
Reducing Peak Memory Usage for Modern Multimodal Large Language Model Pipelines
Junwan Kim, Hyunkyung Bae
Multimodal large language models (MLLMs) have recently demonstrated strong capabilities in understanding and generating responses from diverse visual inputs, including high-resolut…
cs.CL2025
SWITCH: Studying with Teacher for Knowledge Distillation of Large Language Models
Jahyun Koo, Yerin Hwang, Yongil Kim +3
Despite the success of Large Language Models (LLMs), they still face challenges related to high inference costs and memory requirements. To address these issues, Knowledge Distilla…
cs.CL2025
LLMs can be easily Confused by Instructional Distractions
Yerin Hwang, Yongil Kim, Jahyun Koo +3
Despite the fact that large language models (LLMs) show exceptional skill in instruction following tasks, this strength can turn into a vulnerability when the models are required t…