4 papers
Enoki: Efficient Multi-Level Hallucination Detection
Elisei Rykov, Timur Ionov, Nikolay Ivanov +5
Ensuring factuality remains a critical challenge for deploying LLMs in high-stakes settings. Existing hallucination detectors usually operate at a single level: claim-level methods…
OCC-RAG: Optimal Cognitive Core for Faithful Question Answering
Maksim Savkin, Mikhail Goncharov, Alexander Gambashidze +7
Recent progress in the development of language models has been defined by scale, with each generation absorbing more of the world's knowledge into its weights. However, many practi…
When Models Lie, We Learn: Multilingual Span-Level Hallucination Detection with PsiloQA
Elisei Rykov, Kseniia Petrushina, Maksim Savkin +6
Hallucination detection remains a fundamental challenge for the safe and reliable deployment of large language models (LLMs), especially in applications requiring factual accuracy.…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…