A pipeline derives continuous signed edges from LLM stance scores on text and links discourse signals such as toxicity and extreme claims to changes in structural polarization measured by spectral and frustration scores on Reddit Brexit data.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing , pages=
2 Pith papers cite this work. Polarity classification is still indexing.
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Authors develop a multi-dimensional neuron screening framework and adaptive masking method to causally validate and steer emotion and rhetoric neurons in LLMs, with experiments on five datasets.
citing papers explorer
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Linking Extreme Discourse to Structural Polarization in Signed Interaction Networks
A pipeline derives continuous signed edges from LLM stance scores on text and links discourse signals such as toxicity and extreme claims to changes in structural polarization measured by spectral and frustration scores on Reddit Brexit data.
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Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering
Authors develop a multi-dimensional neuron screening framework and adaptive masking method to causally validate and steer emotion and rhetoric neurons in LLMs, with experiments on five datasets.