4 papers
Synergy-CLIP: Extending CLIP with Multi-modal Integration for Robust Representation Learning
Sangyeon Cho, Jangyeong Jeon, Mingi Kim +1
Multi-modal representation learning has become a pivotal area in artificial intelligence, enabling the integration of diverse modalities such as vision, text, and audio to solve co…
ConCSE: Unified Contrastive Learning and Augmentation for Code-Switched Embeddings
Jangyeong Jeon, Sangyeon Cho, Minuk Ma +1
This paper examines the Code-Switching (CS) phenomenon where two languages intertwine within a single utterance. There exists a noticeable need for research on the CS between Engli…
BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched EMR
Jangyeong Jeon, Sangyeon Cho, Dongjoon Lee +2
Pediatric Emergency Department (PED) overcrowding presents a significant global challenge, prompting the need for efficient solutions. This paper introduces the BioBridge framework…
DSG-KD: Knowledge Distillation from Domain-Specific to General Language Models
Sangyeon Cho, Jangyeong Jeon, Dongjoon Lee +2
The use of pre-trained language models fine-tuned to address specific downstream tasks is a common approach in natural language processing (NLP). However, acquiring domain-specific…