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cs.CL2024
MIMDE: Exploring the Use of Synthetic vs Human Data for Evaluating Multi-Insight Multi-Document Extraction Tasks
John Francis, Saba Esnaashari, Anton Poletaev +3
Large language models (LLMs) have demonstrated remarkable capabilities in text analysis tasks, yet their evaluation on complex, real-world applications remains challenging. We defi…
cs.CL2024★ 3 cited
Evidence of a log scaling law for political persuasion with large language models
Kobi Hackenburg, Ben M. Tappin, Paul Röttger +3
Large language models can now generate political messages as persuasive as those written by humans, raising concerns about how far this persuasiveness may continue to increase with…