2 citations · 5 across the 17 of their papers we have counts for
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A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data
Kaituo Zhang, Mingzhi Hu, Hoang Anh Duy Le +9
Large Language Models (LLMs) have emerged as powerful tools for generating data across various modalities. By transforming data from a scarce resource into a controllable asset, LL…
DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
Zicheng Xu, Xiuyi Lou, Guanchu Wang +6
Large Reasoning Models (LRMs) achieve remarkable inference-time improvements through parallel thinking. However, existing methods rely on redundant sampling of reasoning trajectori…
Training-Free Time Series Classification via In-Context Reasoning with LLM Agents
Songyuan Sui, Zihang Xu, Xia Hu
Time series classification (TSC) spans diverse application scenarios, yet labeled data are often scarce, making task-specific training costly and inflexible. Recent reasoning-orien…
Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data
Aokun Chen, Qian Li, Yu Huang +7
A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for…
Mitigating Relational Bias on Knowledge Graphs
Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang +4
Knowledge graph data are prevalent in real-world applications, and knowledge graph neural networks (KGNNs) are essential techniques for knowledge graph representation learning. Alt…