8 citations · 17 across the 14 of their papers we have counts for
8 papers · 1 filter
Total Simulated Survey Error: Designing and Diagnosing Survey Responses from Large Language Models
Indira Sen, Georg Ahnert, Leah von der Heyde +3
Large Language models (LLMs), having been trained on vast amounts of human-generated data, may encode the attitudes and behaviors of these humans. As such, LLMs show promise in mim…
Missing the Margins: A Systematic Literature Review on the Demographic Representativeness of LLMs
Indira Sen, Marlene Lutz, Elisa Rogers +2
Many applications of Large Language Models (LLMs) require them to either simulate people or offer personalized functionality, making the demographic representativeness of LLMs cruc…
Only a Little to the Left: A Theory-grounded Measure of Political Bias in Large Language Models
Mats Faulborn, Indira Sen, Max Pellert +2
Prompt-based language models like GPT4 and LLaMa have been used for a wide variety of use cases such as simulating agents, searching for information, or for content analysis. For a…
Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness
Shayan Alipour, Indira Sen, Mattia Samory +1
Large language models (LLMs) are known to exhibit demographic biases, yet few studies systematically evaluate these biases across multiple datasets or account for confounding facto…
Total Error Sheets for Datasets (TES-D) -- A Critical Guide to Documenting Online Platform Datasets
Leon Fröhling, Indira Sen, Felix Soldner +3
This paper proposes a template for documenting datasets that have been collected from online platforms for research purposes. The template should help to critically reflect on data…
How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs?
Indira Sen, Mattia Samory, Fabian Floeck +2
As NLP models are increasingly deployed in socially situated settings such as online abusive content detection, it is crucial to ensure that these models are robust. One way of imp…
"Call me sexist, but...": Revisiting Sexism Detection Using Psychological Scales and Adversarial Samples
Mattia Samory, Indira Sen, Julian Kohne +2
Research has focused on automated methods to effectively detect sexism online. Although overt sexism seems easy to spot, its subtle forms and manifold expressions are not. In this…
TED-On: A Total Error Framework for Digital Traces of Human Behavior on Online Platforms
Indira Sen, Fabian Floeck, Katrin Weller +2
Peoples' activities and opinions recorded as digital traces online, especially on social media and other web-based platforms, offer increasingly informative pictures of the public.…