Welcome to the Statistical Natural Language Processing Group at the Institute for Computational Linguistics at Heidelberg University. Our research is on the intersection of machine learning and natural language processing, with a special focus on interactive statistical learning techniques. For example, we work on interactive neural machine translation and neural question answering systems, where an artificial intelligence agent learns from human reinforcement/bandit feedback.
We organize the weekly Statistical NLP Colloquium.
New research from the StatNLP group on Error-Aware Interactive Semantic Parsing of OpenStreetMap has been accepted at the SpLU-RoboNLP Workshop @ACL-IJCNLP 2021.
A new paper from our group: Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP will appear in the Challenges of Real-World RL Workshop at NeurIPS 2020. Please access the paper on arxiv.