Tag
This paper benchmarks masked language models (XLM-RoBERTa, DeBERTa V3) and causal LLMs (OpenAI, Google, Mistral, Anthropic, Meta) on propaganda technique detection using the SemEval-2020 Task 11 dataset, reporting state-of-the-art F1 scores of 63.18 and 63.62 respectively.
This paper analyzes the global distributional behavior induced by iterative masked-token resampling in masked language models using Glauber dynamics. It introduces a rectangle test for incompatibility, establishes mixing time bounds, and empirically demonstrates phase transitions and metastable semantic basins.