agent adaptability 1dynamic tool evolution 1LLM agents 1model context protocol 1tool-use benchmarking 1
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cs.AI2026
MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers
Huanxi Liu, Kun Hu, Jiaqi Liao +6
The paper introduces MCPEvol-Bench, a benchmark that tests how well large language model agents adapt to changing tool interfaces and functionalities in Model Context Protocol (MCP…
cs.AI2026
Beyond Scores: Diagnostic LLM Evaluation via Fine-Grained Abilities
Xu Zhang, Xudong Gong, Jiacheng Qin +5
Current evaluations of large language models aggregate performance across diverse tasks into single scores. This obscures fine-grained ability variation, limiting targeted model im…
cs.AI2025
Pay More Attention to the Robustness of Prompt for Instruction Data Mining
Qiang Wang, Dawei Feng, Xu Zhang +4
Instruction tuning has emerged as a paramount method for tailoring the behaviors of LLMs. Recent work has unveiled the potential for LLMs to achieve high performance through fine-t…