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Found 4 papers, 2 papers with code
Evaluating GPT's Programming Capability through CodeWars' Katas
In the burgeoning field of artificial intelligence (AI), understanding the capabilities and limitations of programming-oriented models is crucial.
Prompt Learning for News Recommendation
Some recent \textit{news recommendation} (NR) methods introduce a Pre-trained Language Model (PLM) to encode news representation by following the vanilla pre-train and fine-tune paradigm with carefully-designed recommendation-specific neural networks and objective functions.
VRKG4Rec: Virtual Relational Knowledge Graphs for Recommendation
Recent studies regard items as entities of a knowledge graph and leverage graph neural networks to assist item encoding, yet by considering each relation type individually.
Graph Spring Network and Informative Anchor Selection for Session-based Recommendation
In this paper, we propose a strategy that first selects some informative item anchors and then encode items' potential relations to such anchors.
