34 citations · 103 across the 67 of their papers we have counts for
9 papers · 1 filter
Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods
Adnan Al Ali, Jindřich Libovický, Anne Lauscher
Audio-enabled large language models (AuLLMs) allow users to interact with them simply by talking to them, without the need for an intermediate transcription. This expands the model…
Making a Name for Myself: On Academic Naming Policies and their Impact
A Pranav, Vagrant Gautam, Martin Mundt +6
In academic publishing, names connect scholars to their work. When scholars change their names, including for marriage, academic recognition, or gender transition, they may lose cr…
PsychoSafe: Eliciting Psychologically-Informed Refusals in Large Language Models
Gianluca Barmina, Federico Torrielli, Sven Harms +7
Large language models (LLMs) routinely face requests that should be refused, creating a trade-off between helpfulness and harm prevention. However, refusals themselves can be helpf…
Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails
Marco Antonio Stranisci, A Pranav, Rossana Damiano +2
Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesirable outputs during deployme…
GRUFF: LLM Pronoun Fidelity, Reasoning, and Biases in German
Fabian Mewes, Anne Lauscher, Vagrant Gautam
Third-person singular pronouns have long been used to study stereotypical biases in language models and to test their abilities to reason about reference. More recently, the interp…
Greater accessibility can amplify discrimination in generative AI
Carolin Holtermann, Minh Duc Bui, Kaitlyn Zhou +3
Hundreds of millions of people rely on large language models (LLMs) for education, work, and even healthcare. Yet these models are known to reproduce and amplify social biases pres…
Reviewing the Reviewer: LLM-Assisted Reviewer Feedback Generation for Guideline Compliance
Sukannya Purkayastha, Qile Wan, Anne Lauscher +2
Peer review is central to scientific quality, yet reliance on simple heuristics, namely lazy thinking and non-specific critiques, has threatened review quality. Prior work frames l…
SoS: Analysis of Surface over Semantics in Multilingual Text-To-Image Generation
Carolin Holtermann, Florian Schneider, Anne Lauscher
Text-to-image (T2I) models are increasingly employed by users worldwide. However, prior research has pointed to the high sensitivity of T2I towards particular input languages - whe…
TempViz: On the Evaluation of Temporal Knowledge in Text-to-Image Models
Carolin Holtermann, Nina Krebs, Anne Lauscher
Time alters the visual appearance of entities in our world, like objects, places, and animals. Thus, for accurately generating contextually-relevant images, knowledge and reasoning…