33 citations · 37 across the 3 of their papers we have counts for
3 papers
Why context matters in VQA and Reasoning: Semantic interventions for VLM input modalities
Kenza Amara, Lukas Klein, Carsten Lüth +3
The various limitations of Generative AI, such as hallucinations and model failures, have made it crucial to understand the role of different modalities in Visual Language Model (V…
Understanding Large Language Model Behaviors through Interactive Counterfactual Generation and Analysis
Furui Cheng, Vilém Zouhar, Robin Shing Moon Chan +3
Understanding the behavior of large language models (LLMs) is crucial for ensuring their safe and reliable use. However, existing explainable AI (XAI) methods for LLMs primarily re…
RELIC: Investigating Large Language Model Responses using Self-Consistency
Furui Cheng, Vilém Zouhar, Simran Arora +3
Large Language Models (LLMs) are notorious for blending fact with fiction and generating non-factual content, known as hallucinations. To address this challenge, we propose an inte…