Human intelligence's adaptability is remarkable, allowing us to adjust to new tasks and multi-modal environments swiftly.
We explore multiple types of help players can give to the AI to guide it and analyze the impact of this help in AI behavior, resulting in performance improvements.
We collect a high-quality dataset, DeFacto, containing human demonstrations and informational natural language feedback consisting of corrective instructions, edited summaries, and explanations with respect to the factual consistency of the summary.
2 code implementations • 12 Nov 2022 • Shrestha Mohanty, Negar Arabzadeh, Milagro Teruel, Yuxuan Sun, Artem Zholus, Alexey Skrynnik, Mikhail Burtsev, Kavya Srinet, Aleksandr Panov, Arthur Szlam, Marc-Alexandre Côté, Julia Kiseleva
Human intelligence can remarkably adapt quickly to new tasks and environments.
1 code implementation • 1 Nov 2022 • Alexey Skrynnik, Zoya Volovikova, Marc-Alexandre Côté, Anton Voronov, Artem Zholus, Negar Arabzadeh, Shrestha Mohanty, Milagro Teruel, Ahmed Awadallah, Aleksandr Panov, Mikhail Burtsev, Julia Kiseleva
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy.
1 code implementation • 27 May 2022 • Julia Kiseleva, Alexey Skrynnik, Artem Zholus, Shrestha Mohanty, Negar Arabzadeh, Marc-Alexandre Côté, Mohammad Aliannejadi, Milagro Teruel, Ziming Li, Mikhail Burtsev, Maartje ter Hoeve, Zoya Volovikova, Aleksandr Panov, Yuxuan Sun, Kavya Srinet, Arthur Szlam, Ahmed Awadallah
Starting from a very young age, humans acquire new skills and learn how to solve new tasks either by imitating the behavior of others or by following provided natural language instructions.
We find that this classifier works well in the Wikipedia, but, as could be expected, performance decreases in a corpus of judgments of the European Court of Human Rights.