InferenceBench: A Benchmark for Open-Ended LLM Inference Optimization by AI Agents
AI agents are increasingly used to automate research and development tasks, yet existing benchmarks typically evaluate them on prescribed workflows or narrow action spaces. Even nominally open-ended tasks can often be solved by retrieving a well-known recipe and tuning a few hype...
ArXiv CS.AI
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This benchmark is crucial for evaluating AI agents' real-world optimization capabilities by moving beyond pre-defined tasks to assess their ability to self-improve LLM inference performance. The findings highlight a gap between agents' domain knowledge and their capacity for systematic exploration and innovative strategy generation, indicating a need for research into more flexible and diverse problem-solving approaches.
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