3 papers
cs.CL2025
OMHBench: Benchmarking Balanced and Grounded Omni-Modal Multi-Hop Reasoning
Seunghee Kim, Ingyu Bang, Seokgyu Jang +5
Multimodal Large Language Models (MLLMs) have increasingly supported omni-modal processing across text, vision, and speech. However, existing evaluation frameworks for such models…
cs.CL2024
FCMR: Robust Evaluation of Financial Cross-Modal Multi-Hop Reasoning
Seunghee Kim, Changhyeon Kim, Taeuk Kim
Real-world decision-making often requires integrating and reasoning over information from multiple modalities. While recent multimodal large language models (MLLMs) have shown prom…
cs.CL2024
Hyper-CL: Conditioning Sentence Representations with Hypernetworks
Young Hyun Yoo, Jii Cha, Changhyeon Kim +1
While the introduction of contrastive learning frameworks in sentence representation learning has significantly contributed to advancements in the field, it still remains unclear w…