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Despite the potential of language model-based agents to solve real-world tasks such as web navigation, current methods still struggle with long-horizon tasks with complex action trajectories. In contrast, humans can flexibly solve complex tasks by learning reusable task workflows from past experiences and using them to guide future actions. To buil...
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... Results As shown in Table 6, compared to AWM rule , AWM lm improves by a 2.8 margin. While augmenting concrete, full examples may bias agents to select elements similar to those presented in the given examples, AWM lm introduces less bias on element selection via its abstract representation of example-specific contexts in workflows. ...Similar publications
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