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What is Topic Evolution in Information Retrieval about?
The document explores topic evolution in the field of information retrieval through an analysis of 20,000 papers, utilizing LDA to extract global and local topics over time. It also introduces the Scito2M dataset for a 30-year scientometric analysis, revealing trends in academic terminology and citation patterns. Additionally, it discusses advancements in graph representation learning with the Graphormer model and evaluates temporal reasoning in large language models using the ChronoSense benchmark.
- Author
- ai23mtech02007
- Language
- EN