ru
ru
Source
NeurIPS Workshop
DATE OF PUBLICATION
03/21/2022
Authors
Mikhail Burtsev Alexander Panov Alexey Skrynnik Artem Zholus Shrestha Mohanty Julia Kiseleva Kavya Srinet Arthur Szlam Yuxuan Sun Marc-Alexandre Cotˆe Negar Arabzadeh Milagro Teruel
Share

Collecting Interactive Multi-modal Datasets for Grounded Language Understanding.

Abstract

Human intelligence can remarkably adapt quickly to new tasks and environments. 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. To facilitate research which can enable similar capabilities in machines, we made the following contributions (1) formalized the collaborative embodied agent using natural language task; (2) developed a tool for extensive and scalable data collection; and (3) collected the first dataset for interactive grounded language understanding.

Full text

Similar publications

AAAI
Decentralized Monte Carlo Tree Search for Partially Observable Multi-agent Pathfinding
Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Alexander Panov
SOURCE
AAAI
TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers
Anton Andreychuk, Alexander Panov, Konstantin Yakovlev, Daniil Kirilenko
SOURCE
NAACL
Biomedical Entity Representation with Graph-Augmented Multi-Objective Transformer
Artur Kadurin, Elena Tutubalina
SOURCE
IEEE Access
Interactive Semantic Map Representation for Skill-Based Visual Object Navigation
Tatiana Zemskova, Aleksei Staroverov, Kirill Muravyev, Dmitry Yudin, Alexander Panov
SOURCE
ECIR
BioASQ at CLEF2024: The Twelfth Edition of the Large-Scale Biomedical Semantic Indexing and Question Answering Challeng
Anastasios Nentidis, Anastasia Krithara, Georgios Paliouras, Martin Krallinger, Luis Gasco Sánchez, Salvador Lima, Eulalia Farre, , Natalia Loukachevitch, Vera Davydova, Elena Tutubalina
SOURCE
Logic Journal of the IGPL
Sign-based image criteria for social interaction visual question answering
Anfisa Chuganskaya, Alexey Kovalev, Alexander Panov
SOURCE
AAAI
Beyond Attention: Breaking the Limits of Transformer Context Length with Recurrent Memory
Aydar Bulatov, Yuri Kuratov, Yermek Kapushev, Mikhail Burtsev
SOURCE
Contact us
Join AIRI
You can ask us a question or suggest a joint project in the field of AI

Message sent.

Thank you!

Something went wrong. Try again