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pro vyhledávání: '"Aponte, Ryan"'
Autor:
Aponte, Ryan, Rossi, Ryan A., Guo, Shunan, Dernoncourt, Franck, Yu, Tong, Chen, Xiang, Mitra, Subrata, Lipka, Nedim
Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) followin
Externí odkaz:
http://arxiv.org/abs/2408.02861
Autor:
Aponte, Ryan, Rossi, Ryan A., Guo, Shunan, Hoffswell, Jane, Lipka, Nedim, Xiao, Chang, Chan, Gromit, Koh, Eunyee, Ahmed, Nesreen
In this work, we introduce a hypergraph representation learning framework called Hypergraph Neural Networks (HNN) that jointly learns hyperedge embeddings along with a set of hyperedge-dependent embeddings for each node in the hypergraph. HNN derives
Externí odkaz:
http://arxiv.org/abs/2212.14077