4 papers
Hybrid Fact-Checking that Integrates Knowledge Graphs, Large Language Models, and Search-Based Retrieval Agents Improves Interpretable Claim Verification
Shaghayegh Kolli, Richard Rosenbaum, Timo Cavelius +3
Large language models (LLMs) excel in generating fluent utterances but can lack reliable grounding in verified information. At the same time, knowledge-graph-based fact-checkers de…
StylisticBias: A Few Human Visual Cues Drive Most Social Biases in MLLMs
Shaghayegh Kolli, Timo Cavelius, Nafiseh Nikeghbal +2
Multimodal large language models (MLLMs) are increasingly deployed in personally and societally consequential settings, yet the visual cues that shape how these models judge people…
Who Flips? Self- and Cross-Model Counterarguments Reveal Answer Instability in LLMs
Nafiseh Nikeghbal, Amir Hossein Kargaran, Shaghayegh Kolli +1
Standard accuracy benchmarks are designed to test how closely large language models (LLMs) approach correct answers, but are not suitable for testing whether LLMs stick with a corr…
Crafting Tomorrow's Headlines: Neural News Generation and Detection in English, Turkish, Hungarian, and Persian
Cem Ãyük, Danica Rovó, Shaghayegh Kolli +3
In the era dominated by information overload and its facilitation with Large Language Models (LLMs), the prevalence of misinformation poses a significant threat to public discourse…