3 papers
cs.LG2026
AE-LLM: Adaptive Efficiency Optimization for Large Language Models
Kaito Tanaka, Masato Ito, Yuji Nishimura +2
Large Language Models (LLMs) have achieved remarkable success across diverse applications, yet their deployment remains challenging due to substantial computational costs, memory r…
cs.LG2026
Contextual Discrepancy-Aware Contrastive Learning for Robust Medical Time Series Diagnosis in Small-Sample Scenarios
Kaito Tanaka, Aya Nakayama, Masato Ito +2
Medical time series data, such as EEG and ECG, are vital for diagnosing neurological and cardiovascular diseases. However, their precise interpretation faces significant challenges…
cs.CV2025
Semantic-Preserving Cross-Style Visual Reasoning for Robust Multi-Modal Understanding in Large Vision-Language Models
Aya Nakayama, Brian Wong, Yuji Nishimura +1
The "style trap" poses a significant challenge for Large Vision-Language Models (LVLMs), hindering robust semantic understanding across diverse visual styles, especially in in-cont…