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20242026
most citedSLIDE: A Framework Integrating Small and Large Language Models for Open-Domain Dialogues Evaluation

1 citations · 2 across the 8 of their papers we have counts for

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cs.CL2026

From Sampled Evidence to Radiology Reports: Objectives, Constraints, and Realization

Kun Zhao, Haoteng Tang, Chenghua Lin +1

Sampling multiple reports creates an inference problem: how should sampled evidence be converted into a final decision, and does a better structured decision yield a better report?…

cs.CL2026

OralAgent: Integrating Reasoning, Tools, and Knowledge for Interactive Dental Image Analysis

Jing Hao, Siyuan Dai, Yongxin Zhang +13

Dental image analysis plays a pivotal role in supporting accurate diagnosis and treatment planning in oral healthcare. Although recent advances have produced dental AI models for s…

cs.CL2025

DRE: An Effective Dual-Refined Method for Integrating Small and Large Language Models in Open-Domain Dialogue Evaluation

Kun Zhao, Bohao Yang, Chen Tang +4

Large Language Models (LLMs) excel at many tasks but struggle with ambiguous scenarios where multiple valid responses exist, often yielding unreliable results. Conversely, Small La…

cs.CL2024

X-ray Made Simple: Lay Radiology Report Generation and Robust Evaluation

Kun Zhao, Chenghao Xiao, Sixing Yan +5

Radiology Report Generation (RRG) has advanced considerably with the development of multimodal generative models. Despite the progress, the field still faces significant challenges…

cs.CL2024★ 1 cited

SLIDE: A Framework Integrating Small and Large Language Models for Open-Domain Dialogues Evaluation

Kun Zhao, Bohao Yang, Chen Tang +2

The long-standing one-to-many problem of gold standard responses in open-domain dialogue systems presents challenges for automatic evaluation metrics. Though prior works have demon…

cs.CL2024

Emphasising Structured Information: Integrating Abstract Meaning Representation into LLMs for Enhanced Open-Domain Dialogue Evaluation

Bohao Yang, Kun Zhao, Dong Liu +3

Automatic open-domain dialogue evaluation has attracted increasing attention, yet remains challenging due to the complexity of assessing response appropriateness. Traditional evalu…