Ulrike Hahn

dblp:76/4959 · DBLP profile ↗
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42ranked-venue papers
6as first author
16since 2021 · last 2025
0000-0002-7744-8589ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 42 · 6 first-author · 16 since 2021Applied, interdisciplinary, general and emerging computing · 40 · 5 first-author · 15 since 2021
YearPublicationVenuePosition
2025 Framing in context: Disabling conditions and alternative causes in health communication
Peter Collins, Karolina Krzyzanowska, Ulrike Hahn
CogSci3
2025 Flooding the Zone: An Agent-based Exploration
Ulrike Hahn, Leon Assaad, Klee Schöppl
CogSci1
2025 Order Effects in Evidence Chains: Normative and Naïve Evaluations
Kirsty Phillips, Ulrike Hahn
CogSci2
2025 Evaluating testimony from multiple witnesses: exploring qualitative intuitions
Kirsty Phillips, Ulrike Hahn, Toby D. Pilditch
CogSci2
2024 Rational Polarization: Sharing Only One's Best Evidence Can Lead to Group Polarization
Leon Assaad, Ulrike Hahn
CogSci2
2024 Testing the Maximum Entropy Approach to Awareness Growth in Bayesian Epistemology and Decision Theory
Rafael Fuchs, Marko Tesic, Ulrike Hahn
CogSci3
2024 Opinion Averaging versus Argument Exchange
Ulrike Hahn, Leon Assaad, Jason W. Burton
CogSci1
2024 Chain Versus Common Cause: Biased Causal Strength Judgments in Humans and Large Language Models
Anita Keshmirian, Moritz Willig, Babak Hemmatian, Kristian Kersting, Ulrike Hahn, Tobias Gerstenberg
CogSci5
2024 Exploring Effects of Self-Censoring through Agent-Based Simulation
Klee Schöppl, Ulrike Hahn
CogSci2
2024 Expanding the Scope of Bayesian Argumentation
abstract
A Bayesian approach to argumentation has, arguably, made great strides in illuminating long-standing questions about argument quality. In particular, the Bayesian framework allows nuanced evaluation of content-based differences in argument strength for individual arguments –both for arguments about facts and for practical arguments. It also provides a principled approach to summary evaluation in contexts of multiple, both mutually supporting and competing arguments, in final reckoning. What it has not done, however, is contribute systematically to an understanding of the dialectical process of argumentation, either in dyads or across large collectives. The talk reviews the literature on argument quality, but then focusses on recent work within the Bayesian framework to address this dialectical challenge.
Ulrike Hahn
COMMA1
2023 Causal Structure and Argumentative Value
Ulrike Hahn, Borut Trpin, Stephan Hartmann 0001, Marko Tesic, Anita Keshmirian, Corina Strößner
CogSci1
2023 Perceived Causal Strength in Chains vs. Common Causes
Anita Keshmirian, Babak Hemmatian, Ulrike Hahn, Stephan Hartmann 0001
CogSci3
2023 Evaluating testimony from multiple witnesses: consistent undervaluing and selective devaluing of corroborating reports
Kirsty Phillips, Ulrike Hahn, Toby D. Pilditch
CogSci2
2023 How Well Do Humans Learn Conditional Probabilities?
Corina Strößner, Ulrike Hahn
CogSci2
2021 How to Revise Beliefs from Conditionals: A New Proposal
Stephan Hartmann 0001, Ulrike Hahn
CogSci2
2021 Rewiring the Wisdom of the Crowd
Jason W. Burton, Abdullah Almaatouq, Mohammad Amin Rahimian, Ulrike Hahn
CogSci4
2020 A New Approach to Testimonial Conditionals
Stephan Hartmann 0001, Ulrike Hahn
CogSci2
2020 '...that P is relevant for Q': Indicative conditionals and learning from testimony
Karolina Krzyzanowska, Peter Collins, Ulrike Hahn
CogSci3
2020 On the Malleability and Stability of Ignoring Group-Level Effects
Momme von Sydow, Niels Braus, Ulrike Hahn
CogSci3
2020 Human-Generated Explanations of Inferences in Bayesian Networks: A Case Study
Marko Tesic, Ulrike Hahn
CogSci2
2019 How Real is Moral Contagion in Online Social Networks?
Jason W. Burton, Nicole Cruz, Ulrike Hahn
CogSci3
2019 Failing to see what you are a part of: Wisdom among crowd members
Ulrike Hahn, Toby D. Pilditch, Nicole Cruz
CogSci1
2019 Reasoning about dissent: Expert disagreement and shared backgrounds
Jens Koed Madsen, Ulrike Hahn, Toby D. Pilditch
CogSci2
2019 Shared Evidence: It all depends
Toby D. Pilditch, Ulrike Hahn, David A. Lagnado
CogSci2
2019 Thinking Locally or Globally? - Trying to Overcome the Tragedy of Personnel Evaluation with Stories or Selective Information Presentation
Momme von Sydow, Niels Braus, Ulrike Hahn
CogSci3
2019 The Temporal Dynamics of Belief-based Updating of Epistemic Trust: Light at the End of the Tunnel?
Momme von Sydow, Christoph Merdes, Ulrike Hahn
CogSci3
2019 Sequential diagnostic reasoning with independent causes
Marko Tesic, Ulrike Hahn
CogSci2
2018 How Communication Can Make Voters Choose Less Well
Ulrike Hahn, Momme von Sydow, Christoph Merdes
CogSci1
2018 Partial source dependence and reliability revision: the impact of shared backgrounds
Jens Koed Madsen, Ulrike Hahn, Toby D. Pilditch
CogSci2
2018 Evaluating testimony from multiple witnesses: single cue satisficing or integration?
Kirsty Phillips, Ulrike Hahn, Toby D. Pilditch
CogSci2
2018 Integrating dependent evidence: naïve reasoning in the face of complexity
Toby D. Pilditch, Ulrike Hahn, David A. Lagnado
CogSci2
2017 The Puzzle of Conditionals with True Clauses: Against the Gricean Account
Karolina Krzyzanowska, Peter Collins, Ulrike Hahn
CogSci3
2017 The dilution effect: Conversational basis and witness reliability
Jens Koed Madsen, Ulrike Hahn, Marion Vorms
CogSci2
2017 Conditionals, Individual Variation, and the Scorekeeping Task
Niels Skovgaard-Olsen, David Kellen, Ulrike Hahn, Karl Christoph Klauer
CogSci3
2017 Overcoming the Tragedy of Personnel Evaluation?
Momme von Sydow, Niels Braus, Ulrike Hahn
CogSci3
2017 Rank Aggregation and Belief Revision Dynamics
Igor Volzhanin, Ulrike Hahn, Dell Zhang, Stephan Hartmann 0001
CogSci2
2015 The Bi-directional Relationship Between Source Characteristics and Message Content
Peter Collins, Ulrike Hahn, Yvlva von Gerber, Erik J. Olsson
CogSci2
2015 Individual Belief Revision Dynamics in a Group Context
Igor Volzhanin, Ulrike Hahn, Martin Jonsson, Erik J. Olsson
CogSci2
2014 Assessing the "bias" in human randomness perception
Umberto Gostoli, George Farmer, Mark Boyle, Wael El-Deredy, Andrew Howes 0001, Ulrike Hahn
CogSci7
2013 Autism, optimism and positive events: Evidence against a general optimistic bias
Adam J. L. Harris, Punit Shah, Caroline Catmur, Geoffrey Bird, Ulrike Hahn
CogSci5
2013 Infant contributions to joint attention predict vocabulary development
Katherine Scott, Elena Sakkalou, Kate Ellis-Davies, Elma E. Hilbrink, Ulrike Hahn, Merideth Gattis
CogSci5
1996 Cross-Serial Dependencies Are Not Hard to Process
Carl Vogel, Ulrike Hahn, Holly P. Branigan
COLING2