Conversational Web Navigation
2 papers with code • 1 benchmarks • 1 datasets
The problem of conversational web navigation is described as follow: a digital agent controls a web browser and follows user instructions to solve real-world tasks in a multi-turn dialogue fashion. It was introduced alongside the WebLINX benchmark (Lù, Kasner, Reddy, 2024), and complements tasks such as Autonomous Web Navigation. It is one of many problems tackled by generalist (web) agents.
Benchmarks
These leaderboards are used to track progress in Conversational Web Navigation
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WebLINX
Most implemented papers
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
We propose the problem of conversational web navigation, where a digital agent controls a web browser and follows user instructions to solve real-world tasks in a multi-turn dialogue fashion.
On the Multi-turn Instruction Following for Conversational Web Agents
magicgh/self-map
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Web agents powered by Large Language Models (LLMs) have demonstrated remarkable abilities in planning and executing multi-step interactions within complex web-based environments, fulfilling a wide range of web navigation tasks.
