{"arxiv_id":"2207.10915","incoming":{"papers":0,"sentences":0,"groups":[],"unlabelled_sentences":0},"outgoing":{"papers":2,"sentences":2,"groups":[{"kind":"method_or_tool","label":"Uses the method or tool of","papers":1,"sentences":1,"quotes":[{"arxiv_id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","url":"/paper/1609.02907","section":"Graph-based Armband Modeling Network for recognition","sentence":"Based on the generic graph modeling of special-shaped FMG armband considering both FMG signals $𝒳$ the connectivity $𝒜$, as is shown in Fig. [ref], we further leverage graph convolutional network (GCN) [ref] to build our classifier for FMG armbands, namely Graph-based Armband Modeling Network (GAM-Net), for arm movement recognition.","intent_p":0.99,"contests_p":null}]},{"kind":"background","label":"Cites as background","papers":1,"sentences":1,"quotes":[{"arxiv_id":"2110.05352","title":"All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda","url":"/paper/2110.05352","section":"INTRODUCTION","sentence":"To approach such a lofty goal of human-machine symbiosis, a growing effort has been devoted to designing more powerful wearable sensing devices and smarter algorithms to recognize human movement or intention [ref] , especially in the field of human-machine interaction [ref] [ref] , augmented reality [ref] , and Metaverse [ref] .","intent_p":0.97,"contests_p":null}]}],"unlabelled_sentences":0},"claims":[],"thresholds":{"intent_p":0.8,"supports_p":0.95,"contests_p":0.7},"method":"Citing sentences come from each paper's LaTeX source; every \\cite marks the sentence and the works it cites. Pith's classifier typed each sentence. A label is shown at intent probability 0.8 or more (0.95 for support), a contest at 0.7 or more. Measured accuracy against two blind model families is at https://pith.science/accuracy. The quoted sentences are the citing authors' own.","held_up":null,"_links":{"html":"https://pith.science/paper/2207.10915"}}