RUT-Bench
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Beyond Ideal Instruction: A Comprehensive Framework for Evaluating LLMs in Realistic Interactions
arXiv:2606.03318v1 Announce Type: new Abstract: Despite great advances in tool-use capabilities of large language models (LLMs), existing evaluation benchmarks struggle to fully align with real-world scenarios. Such benchmarks mostly rely on simulated idealized user assumptions and lacks experience-oriented evaluation. These limitations fail to account for the ambiguity, uncooperative behaviors, and shifting intentions characteristic of real-world users.
Beyond Ideal Instruction: A Comprehensive Framework for Evaluating LLMs in Realistic Interactions
arXiv:2606.03318v2 Announce Type: replace Abstract: Despite great advances in tool-use capabilities of large language models (LLMs), existing evaluation benchmarks struggle to fully align with real-world scenarios. Such benchmarks mostly rely on simulated idealized user assumptions and lacks experience-oriented evaluation. These limitations fail to account for the ambiguity, uncooperative behaviors, and shifting intentions characteristic of real-world users.