8 papers
FreezeEmpath: Efficient Training for Empathetic Spoken Chatbots with Frozen LLMs
Yun Hong, Yan Zhou, Yang Feng
Empathy is essential for fostering natural interactions in spoken dialogue systems, as it enables machines to recognize the emotional tone of human speech and deliver empathetic re…
Efficient Training for Cross-lingual Speech Language Models
Yan Zhou, Qingkai Fang, Yun Hong +1
Currently, large language models (LLMs) predominantly focus on the text modality. To enable more natural human-AI interaction, speech LLMs are emerging, but building effective end-…
QuarkMedBench: A Real-World Scenario Driven Benchmark for Evaluating Large Language Models
Yao Wu, Kangping Yin, Liang Dong +13
While Large Language Models (LLMs) excel on standardized medical exams, high scores often fail to translate to high-quality responses for real-world medical queries. Current evalua…
Adaptive Diagnostic Reasoning Framework for Pathology with Multimodal Large Language Models
Yunqi Hong, Johnson Kao, Liam Edwards +5
AI tools in pathology have improved screening throughput, standardized quantification, and revealed prognostic patterns that inform treatment. However, adoption remains limited bec…
Uncertainty-Guided Selective Adaptation Enables Cross-Platform Predictive Fluorescence Microscopy
Kai-Wen K. Yang, Andrew Bai, Alexandra Bermudez +7
Deep learning is transforming microscopy, yet models often fail when applied to images from new instruments or acquisition settings. Conventional adversarial domain adaptation (ADD…
QG-CoC: Question-Guided Chain-of-Captions for Large Multimodal Models
Kuei-Chun Kao, Hsu Tzu-Yin, Yunqi Hong +2
Recently, Multimodal Large Language Models (MLLMs) encounter two key issues in multi-image contexts: (1) a lack of fine-grained perception across disparate images, and (2) a dimini…