
Tobias Falke
Researcher in Machine Learning and Foundation Models
I’m a Principal Applied Scientist at Amazon AGI in Berlin, working on foundation model pretraining. My work spans the full pretraining stack: model architecture (MoEs in particular), training recipes, scaling, experimental design and evaluation. Most recently, I also worked on automating research, agentic systems and self-improving systems.
I joined Amazon in 2019 after completing my PhD at UKP Lab, Technische Universität Darmstadt, where I worked on NLP for document exploration: text summarization, information extraction and interactive learning. Before moving into LLM pretraining, I spent several years working on language understanding for Amazon Alexa.
Writing
- Sep 2026 MoEs Over Time: What Changed And How Much Does it Matter?
- Aug 2026 Why I don't trust any single paper's claims
- Jul 2026 A Routing Testbed for MoEs, Part 2: Visualizing Balancing Methods
Publications
2026
2023
Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models
Findings of ACL 2023. Toronto, Canada.
Regression-Free Model Updates for Spoken Language Understanding
ACL 2023 (Industry Track). Toronto, Canada.
2021
Feedback Attribution for Counterfactual Bandit Learning in Multi-Domain Spoken Language Understanding
EMNLP 2021. Virtual.
2020
Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances
COLING 2020 (Industry Track). Virtual.
★ Best Paper Award — Industry Track
2019
Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference
ACL 2019. Florence, Italy.
Fast Concept Mention Grouping for Concept-Map-Based Multi-Document Summarization
NAACL 2019. Minneapolis, MN, USA.
2018
2017
System Z^FO: Default Reasoning with System Z-like Ranking Functions for Unary First-Order Conditional Knowledge Bases
International Journal of Approximate Reasoning, Volume 90, 2017.
Concept-Map-Based Multi-Document Summarization using Concept Coreference Resolution and Global Importance Optimization
IJCNLP 2017. Taipei, Taiwan.
Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps
EMNLP 2017. Copenhagen, Denmark.
★ Best Resource Paper Award
GraphDocExplore: A Framework for the Experimental Comparison of Graph-based Document Exploration Techniques
EMNLP 2017 (Demo). Copenhagen, Denmark.