NLP comparison of lobby papers and MEP speeches discovers influence links validated indirectly via retweets and meetings, achieving AUC 0.77 and ideological alignment in aggregate analysis.
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DECOR learns decomposed contextual token representations by combining pretrained semantics with collaborative signals to fix objective misalignment in two-stage generative recommendation systems.
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Studying Lobby Influence in the European Parliament
NLP comparison of lobby papers and MEP speeches discovers influence links validated indirectly via retweets and meetings, achieving AUC 0.77 and ideological alignment in aggregate analysis.
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Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation
DECOR learns decomposed contextual token representations by combining pretrained semantics with collaborative signals to fix objective misalignment in two-stage generative recommendation systems.
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