5 papers
TK-Mamba: Marrying KAN With Mamba for Text-Driven 3D Medical Image Segmentation
Haoyu Yang, Yutong Guan, Meixing Shi +8
3D medical image segmentation is important for clinical diagnosis and treatment but faces challenges from high-dimensional data and complex spatial dependencies. Traditional single…
dots.llm1 Technical Report
Bi Huo, Bin Tu, Cheng Qin +24
Mixture of Experts (MoE) models have emerged as a promising paradigm for scaling language models efficiently by activating only a subset of parameters for each input token. In this…
Flow2Code: Evaluating Large Language Models for Flowchart-based Code Generation Capability
Mengliang He, Jiayi Zeng, Yankai Jiang +4
While large language models (LLMs) show promise in code generation, existing benchmarks neglect the flowchart-based code generation. To promote further research on flowchart-based…
Mis-prompt: Benchmarking Large Language Models for Proactive Error Handling
Jiayi Zeng, Yizhe Feng, Mengliang He +5
Large language models (LLMs) have demonstrated significant advancements in error handling. Current error-handling works are performed in a passive manner, with explicit error-handl…
Coherency Improved Explainable Recommendation via Large Language Model
Shijie Liu, Ruixing Ding, Weihai Lu +4
Explainable recommender systems are designed to elucidate the explanation behind each recommendation, enabling users to comprehend the underlying logic. Previous works perform rati…