Danil S. Grigorev
Papers
1
Total Citations
3
H-Index
1
About
Danil S. Grigorev is a researcher at the forefront of integrating common-sense reasoning into artificial intelligence, with a particular focus on plan verification using large language models (LLMs). His most-cited work, "Common Sense Plan Verification with Large Language Models" (2024), addresses a critical gap in AI planning: ensuring that generated plans are not only logically valid but also align with human intuition and everyday knowledge. By leveraging LLMs to detect implausible or impractical steps in automated plans, Grigorev’s research bridges symbolic reasoning and neural approaches, offering a scalable solution for real-world applications like robotics, autonomous systems, and decision support. This contribution has already garnered early attention within the AI community, reflecting its timely relevance as LLMs become central to planning tasks. Though early in his career, Grigorev’s work stands out for its practical impact, demonstrating how common sense can be operationalized to make AI systems more reliable and human-compatible. His research is a must-read for students and researchers exploring the intersection of natural language processing, automated planning, and commonsense reasoning.
Research Focus
Key Achievements
Top Papers
- 1Common Sense Plan Verification with Large Language Models3 citations · 2024