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cs.CL2025
GenderBench: Evaluation Suite for Gender Biases in LLMs
Matúš Pikuliak
We present GenderBench -- a comprehensive evaluation suite designed to measure gender biases in LLMs. GenderBench includes 14 probes that quantify 19 gender-related harmful behavio…
cs.CL2025
Large Language Models for Multilingual Previously Fact-Checked Claim Detection
Ivan Vykopal, Matúš Pikuliak, Simon Ostermann +3
In our era of widespread false information, human fact-checkers often face the challenge of duplicating efforts when verifying claims that may have already been addressed in other…
cs.CL2023
Disinformation Capabilities of Large Language Models
Ivan Vykopal, Matúš Pikuliak, Ivan Srba +3
Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with d…