AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces a novel PLM for political discourse language called RooseBERT, trained on large political debate and speech corpora in English, and fine-tuned it on multiple downstream tasks related to political debate analysis, highlighting how domain-specific pre-training enhances performance in political debate...
Extensive evaluations show that stereotype-conditioned prompting substantially outperforms generic baselines across all three languages, obtaining significant gains in factuality, specificity, cogency, and effectiveness for both explicit and implicit implied stereotypes.
The CRITICS project addresses science accessibility and literacy by converging advanced Machine Translation based on Large Language Models (LLMs) with educational technology and explores the design and evaluation of innovative science teaching-learning proposals grounded in curriculum-aligned teaching-learning.
Measuring political bias in large language models (LLMs) remains challenging as it can manifest through subtle differences in framing, argumentation, and legal reasoning that are difficult to capture with a single metric. In this work, we introduce Poli-Bias, a counterfactual framework for measuring whether LLMs treat...
This work introduces a guided retrieval-augmented methodology for fallacy detection and classification that leverages argumentative relations of support and attack to dynamically steer the extraction of relevant documents when retrieval is argumentatively guided.
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