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Found 2 papers, 1 papers with code
ISQA: Informative Factuality Feedback for Scientific Summarization
We propose Iterative Facuality Refining on Informative Scientific Question-Answering (ISQA) feedback\footnote{Code is available at \url{https://github. com/lizekai-richard/isqa}}, a method following human learning theories that employs model-generated feedback consisting of both positive and negative information.
FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations
In edge computing, users' service profiles are migrated due to user mobility.
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