Zoya Volovikova
Papers
1
Total Citations
1
H-Index
1
About
Zoya Volovikova is a researcher at the intersection of embodied AI and human-robot interaction, with a primary focus on enabling robots to navigate and resolve ambiguity in real-world environments. Her most notable contribution is the creation of **AmbiK**, the first comprehensive dataset of ambiguous tasks set in kitchen environments, introduced in her 2025 paper. This work addresses a critical gap in embodied agent research: while Large Language Models (LLMs) excel at behavior planning from natural language instructions, they struggle with the inherent vagueness of human commands. Volovikova’s dataset systematically catalogs scenarios where instructions are unclear—such as “clean the counter” when multiple items are present—providing a benchmark for developing ambiguity detection and resolution methods. Her research has quickly garnered attention, with the AmbiK paper already accumulating citations, signaling its importance to the field. By tackling this fundamental challenge, Volovikova is helping to bridge the gap between controlled lab settings and the messy, unpredictable nature of real-world human-robot collaboration, making her work essential reading for anyone interested in robust, user-friendly embodied AI systems.
Research Focus
Key Achievements
Top Papers
- 1AmbiK: Dataset of Ambiguous Tasks in Kitchen Environment1 citations · 2025