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Found 4 papers, 3 papers with code
Improving Sequential Recommendations with LLMs
We conduct extensive experiments on three datasets and explore a large variety of configurations, including different language models and baseline recommendation models, to obtain a comprehensive picture of the performance of each approach.
Leveraging Large Language Models for Sequential Recommendation
Sequential recommendation problems have received increasing attention in research during the past few years, leading to the inception of a large variety of algorithmic approaches.
A Greek Parliament Proceedings Dataset for Computational Linguistics and Political Analysis
Large, diachronic datasets of political discourse are hard to come across, especially for resource-lean languages such as Greek.
Search Engine Similarity Analysis: A Combined Content and Rankings Approach
We evaluated the characteristics of the metric against other metrics and approaches that have been proposed in the literature, and used it to (1) investigate the similarities of search engine results, (2) the evolution of their affinity over time, (3) what aspects of the results influence similarity, and (4) how the metric differs over different kinds of search services.
