May 19, 2023 · We propose an instruction-following multimodal agent, WebGUM, that observes both webpage screenshots and HTML pages and outputs web navigation actions.
Nov 22, 2023 · We propose an offline multimodal agent for autonomous web navigation based on instruction-finetuned large language models, that achieves comparable performance ...
Feb 25, 2024 · In this work, we study data-driven offline training for web agents with vision-language foundation models. We propose an instruction-following ...
This work proposes an instruction-following multimodal agent, WebGUM, that observes both webpage screenshots and HTML pages and outputs web navigation ...
We propose an instruction-aligned multimodal agent for autonomous web navi- gation – i.e., sequential decision making tasks employing a computer interface.
WebGUM is a multimodal encoder-decoder transformer model. It takes screenshots, action history, instruction, and HTML as inputs.
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Workshop: Mathematical and Empirical Understanding of Foundation Models (ME-FoMo). Instruction-Finetuned Foundation Models for Multimodal Web Navigation.
Richard Seroter on X: "Multimodal Web Navigation with Instruction ...
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Sep 9, 2024 · Multimodal Web Navigation with Instruction-Finetuned Foundation Models https://t.co/vnJBriCGln < new @GoogleDeepMind (and Univ of Tokyo) ...
This work proposes an instruction-aligned multimodal agent for autonomous web navigation, based on supervised finetuning of vision and language foundation ...
Jul 25, 2023 · We also collect 347K high-quality demonstrations using our trained models, 38 times larger than prior work, and
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