I am a PhD student in Natural Language Processing and Machine Learning
at CIS (Center for Information and Language Processing), Munich University
(LMU Munich), supervised by Prof. Dr. Hinrich Schütze.
My current research focus lies in computational models of context-sensitive relation inference.
- Deep Learning and Neural Networks for NLP
- Machine Learning for Knowledge Graphs (cf. the MLWin project)
- Representation Learning (Character, Word, Phrase Embeddings)
- Character-Level Models
- Lexical Semantics
- Multimodal Learning (esp. Visual Grounding)
- Common Sense Reasoning
Martin Schmitt and Hinrich Schütze.
SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference.
In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL),
Florence, Italy, July 2019. (Acceptance rate: 25.7%)
Stefan Evert, Philipp Heinrich, Klaus Henselmann, Ulrich Rabenstein, Elisabeth Scherr, Martin Schmitt and Lutz Schröder.
Combining Machine Learning and Semantic Features in the Classification of Corporate Disclosures.
In: Journal of Logic, Language and Information (JoLLI), 2019. (Impact factor: 0.536)
Martin Schmitt, Simon Steinheber, Konrad Schreiber and Benjamin Roth.
Joint Aspect and Polarity Classification for Aspect-based Sentiment Analysis with End-to-End Neural Networks .
In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP, Short Paper),
Brussels, Belgium, November 2018. (Acceptance rate: 23.2%)
Philipp Dufter, Mengjie Zhao, Martin Schmitt, Alexander Fraser and Hinrich Schütze.
Embedding Learning Through Multilingual Concept Induction.
In: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL),
Melbourne, Australia, July 2018. (Acceptance rate: 25.3%)
Honors and Awards
I was awarded a Ph.D. scholarship by the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes).