6 citations · 18 across the 7 of their papers we have counts for
7 papers
Collaborative Remote Control of Unmanned Ground Vehicles in Virtual Reality
Ziming Li, Yiming Luo, Jialin Wang +3
Virtual reality (VR) technology is commonly used in entertainment applications; however, it has also been deployed in practical applications in more serious aspects of our lives, s…
IGLU 2022: Interactive Grounded Language Understanding in a Collaborative Environment at NeurIPS 2022
Julia Kiseleva, Alexey Skrynnik, Artem Zholus +14
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…
Interactive Grounded Language Understanding in a Collaborative Environment: IGLU 2021
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +18
Human intelligence has the remarkable ability to quickly adapt to new tasks and environments. Starting from a very young age, humans acquire new skills and learn how to solve new t…
NeurIPS 2021 Competition IGLU: Interactive Grounded Language Understanding in a Collaborative Environment
Julia Kiseleva, Ziming Li, Mohammad Aliannejadi +12
Human intelligence has the remarkable ability to adapt to new tasks and environments quickly. Starting from a very young age, humans acquire new skills and learn how to solve new t…
DEUS: A Data-driven Approach to Estimate User Satisfaction in Multi-turn Dialogues
Ziming Li, Dookun Park, Julia Kiseleva +2
Digital assistants are experiencing rapid growth due to their ability to assist users with day-to-day tasks where most dialogues are happening multi-turn. However, evaluating multi…
Optimizing Interactive Systems via Data-Driven Objectives
Ziming Li, Julia Kiseleva, Alekh Agarwal +2
Effective optimization is essential for real-world interactive systems to provide a satisfactory user experience in response to changing user behavior. However, it is often challen…
Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning
Ziming Li, Julia Kiseleva, Maarten de Rijke
The performance of adversarial dialogue generation models relies on the quality of the reward signal produced by the discriminator. The reward signal from a poor discriminator can…