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Niklas Stoehr

ETH Zurich, Institute for Machine Learning

5 papers hereh-index 14506 citations41 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.CV1
affiliations
  • ETH Zurich, Institute for Machine Learning
HomepageORCID 0000-0003-2867-0236

identity via Semantic Scholar / OpenAlex

collaborators

5 papers

cs.CL2026

Agentic Insight Generation in VSM Simulations

Micha Selak, Dirk Krechel, Adrian Ulges +3

Extracting actionable insights from complex value stream map simulations can be challenging, time-consuming, and error-prone. Recent advances in large language models offer new ave…

cs.CL2025

Measuring Scalar Constructs in Social Science with LLMs

Hauke Licht, Rupak Sarkar, Patrick Y. Wu +4

Many constructs that characterize language, like its complexity or emotionality, have a naturally continuous semantic structure; a public speech is not just "simple" or "complex,"…

cs.CL2025

Controllable Context Sensitivity and the Knob Behind It

Julian Minder, Kevin Du, Niklas Stoehr +4

When making predictions, a language model must trade off how much it relies on its context vs. its prior knowledge. Choosing how sensitive the model is to its context is a fundamen…

cs.CV2025

Taxonomy-Aware Evaluation of Vision-Language Models

Vésteinn Snæbjarnarson, Kevin Du, Niklas Stoehr +4

When a vision-language model (VLM) is prompted to identify an entity depicted in an image, it may answer 'I see a conifer,' rather than the specific label 'norway spruce'. This rai…

cs.CL2025

World Models for Math Story Problems

Andreas Opedal, Niklas Stoehr, Abulhair Saparov +1

Solving math story problems is a complex task for students and NLP models alike, requiring them to understand the world as described in the story and reason over it to compute an a…

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