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Found 4 papers, 4 papers with code
The BrowserGym Ecosystem for Web Agent Research
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those leveraging automation and Large Language Models (LLMs) for web interaction tasks.
In-context learning and Occam's razor
While the No Free Lunch Theorem states that we cannot obtain theoretical guarantees for generalization without further assumptions, in practice we observe that simple models which explain the training data generalize best: a principle called Occam's razor.
WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers.
Learning a Generic Value-Selection Heuristic Inside a Constraint Programming Solver
Important design choices in a solver are the branching heuristics, which are designed to lead the search to the best solutions in a minimum amount of time.
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