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cs.CL2025
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…
cs.CL2025
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…