3 accepted papers
Recent progress in natural language processing has popularized causal language models, but their internal behavior remains poorly understood due to the high cost and reliance on large-scale benchmarks in existing analysis methods. To address these challenges, we introduce a graph-theoretical framewo
Evaluation of large language models (LLMs) in low-resource languages like Persian has received less attention than in high-resource languages like English. Existing evaluation approaches for Persian LLMs generally lack comprehensive frameworks, limiting their ability to assess models’ performance ov…
Automatic evaluation of machine-generated texts, such as answers in open-domain question answering (Open-Domain QA), presents a complex challenge involving cost efficiency, hardware constraints, and high accuracy. Although various metrics exist for comparing machine-generated answers with reference…