3 papers
cs.CL2025
HiKE: Hierarchical Evaluation Framework for Korean-English Code-Switching Speech Recognition
Gio Paik, Yongbeom Kim, Soungmin Lee +2
Despite advances in multilingual automatic speech recognition (ASR), code-switching (CS), the mixing of languages within an utterance common in daily speech, remains a severely und…
cs.CL2025
MMRefine: Unveiling the Obstacles to Robust Refinement in Multimodal Large Language Models
Gio Paik, Geewook Kim, Jinbae Im
This paper introduces MMRefine, a MultiModal Refinement benchmark designed to evaluate the error refinement capabilities of Multimodal Large Language Models (MLLMs). As the emphasi…
cs.CL2024
Improving Fine-grained Visual Understanding in VLMs through Text-Only Training
Dasol Choi, Guijin Son, Soo Yong Kim +2
Visual-Language Models (VLMs) have become a powerful tool for bridging the gap between visual and linguistic understanding. However, the conventional learning approaches for VLMs o…