1 code implementation • 4 May 2024 • Maryam Hashemzadeh, Elias Stengel-Eskin, Sarath Chandar, Marc-Alexandre Cote
While Large Language Models (LLMs) have demonstrated significant promise as agents in interactive tasks, their substantial computational requirements and restricted number of calls constrain their practical utility, especially in long-horizon interactive tasks such as decision-making or in scenarios involving continuous ongoing tasks.
no code implementations • ICLR 2021 • Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions.
1 code implementation • IJCNLP 2019 • Xingdi Yuan, Marc-Alexandre Cote, Jie Fu, Zhouhan Lin, Christopher Pal, Yoshua Bengio, Adam Trischler
In QAit, an agent must interact with a partially observable text-based environment to gather information required to answer questions.
1 code implementation • ACL 2020 • Xingdi Yuan, Jie Fu, Marc-Alexandre Cote, Yi Tay, Christopher Pal, Adam Trischler
Existing machine reading comprehension (MRC) models do not scale effectively to real-world applications like web-level information retrieval and question answering (QA).