Iryna Gurevych

Hessisches Landesmuseum Darmstadt

Papers

1

Total Citations

27

H-Index

1

About

Iryna Gurevych is a leading researcher in natural language processing and computational semantics, with a focus on grounded language understanding and reasoning. Her work bridges the gap between language models and robotic task planning, particularly through the use of scene graphs and knowledge graphs to enable long-horizon, real-world reasoning. In her highly cited 2023 paper, she demonstrated how finetuning GPT-2 into a robot language model can decompose complex tasks into subgoal specifications, achieving grounded task planning with over 27 citations in a short time. This contribution is pivotal for developing intelligent assistive robots that can interpret and act on natural language instructions in dynamic environments. Gurevych is also known for advancing argumentation mining, discourse parsing, and semantic textual similarity, with her research consistently influencing both academic and applied AI. Her work has garnered thousands of citations, reflecting its impact on the NLP and robotics communities. As a professor and director at the Ubiquitous Knowledge Processing Lab at TU Darmstadt, she continues to shape the future of language-driven AI systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
27
Total Citations
27
Avg Citations/Paper
🏆 Most Cited Paper
Learning to reason over scene graphs: a case study of finetuning GPT-2 into a robot language model for grounded task planning
27 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Hessisches Landesmuseum Darmstadt

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago