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Integrating Supervised Extractive and Generative Language Models for Suicide Risk Evidence Summarization
We propose a method that integrates supervised extractive and generative language models for providing supporting evidence of suicide risk in the CLPsych 2024 shared task.
Personalized human mobility prediction for HuMob challenge
We adopted a personalized model to predict the individual's movement trajectory from their data, instead of predicting from the overall movement, based on the hypothesis that human movement is unique to each person.
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