2 papers
cs.AI2026
ParaTool: Shifting Tool Representations from Context to Parameters
Zekai Yu, Qi Meng, Qizhi Chu +3
Tool calling extends large language models (LLMs) by enabling grounded interaction with external executable interfaces, thereby supporting environment-coupled problem solving. Howe…
cs.LG2026
Disentangled Graph Prompting for Out-Of-Distribution Detection
Cheng Yang, Yu Hao, Qi Zhang +1
When testing data and training data come from different distributions, deep neural networks (DNNs) will face significant safety risks in practical applications. Therefore, out-of-d…