Researchers introduced E-Commerce Bench, a benchmark for evaluating LLM agents on long-horizon autonomous business operations, addressing the need for tasks that require continual exploration and adaptation over thousands of steps. The benchmark focuses on dynamic environments and long-range dependencies, pushing beyond simple task chaining.
Long-horizon agentic tasks go beyond chaining short tasks over more interaction turns. Their evolving dynamic environments and long-range dependencies require Large Language Models (LLMs) to continually explore, learn from experience, and adapt their policies over thousands of steps. We introduce E-
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