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

1 citations · 3 across the 9 of their papers we have counts for

collaborators

12 papers

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

Rate-Resolved Text Evaluation with Masked Diffusion Language Models

Yiqi Liu, Kun Zhao, Chenghua Lin +1

A single evaluation score can rank generation systems but rarely reveals what failed. We propose rate-resolved text evaluation, which turns the masking rate of masked diffusion lan…

cs.CL2026

JudgeMoE: Distributional Aggregation for LLM-as-a-Judge

Yiqi Liu, Joseph James, Yang Wang +3

When an LLM judge scores an output, its score distribution retains uncertainty and disagreement information that is lost after scalar compression. We introduce JudgeMoE, a lightwei…

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.CL2025

GRAPHMOE: Amplifying Cognitive Depth of Mixture-of-Experts Network via Introducing Self-Rethinking Mechanism

Bo Lv, Chen Tang, Zifan Zheng +8

Traditional Mixture-of-Experts (MoE) networks benefit from utilizing multiple smaller expert models as opposed to a single large network. However, these experts typically operate i…

cs.CL2024★ 1 cited

BioMNER: A Dataset for Biomedical Method Entity Recognition

Chen Tang, Bohao Yang, Kun Zhao +4

Named entity recognition (NER) stands as a fundamental and pivotal task within the realm of Natural Language Processing. Particularly within the domain of Biomedical Method NER, th…

cs.CL2024★ 1 cited

Crafting Customisable Characters with LLMs: A Persona-Driven Role-Playing Agent Framework

Bohao Yang, Dong Liu, Chenghao Xiao +6

Large Language Models (LLMs) demonstrate remarkable ability to comprehend instructions and generate human-like text, enabling sophisticated agent simulation beyond basic behavior r…

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.LG2024

Interpretable Spatio-Temporal Embedding for Brain Structural-Effective Network with Ordinary Differential Equation

Haoteng Tang, Guodong Liu, Siyuan Dai +9

The MRI-derived brain network serves as a pivotal instrument in elucidating both the structural and functional aspects of the brain, encompassing the ramifications of diseases and…

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…

cs.CV2024

Constrained Multiview Representation for Self-supervised Contrastive Learning

Siyuan Dai, Kai Ye, Kun Zhao +3

Representation learning constitutes a pivotal cornerstone in contemporary deep learning paradigms, offering a conduit to elucidate distinctive features within the latent space and…