{"arxiv_id":"2208.10874","incoming":{"papers":2,"sentences":4,"groups":[{"kind":"background","label":"Cites it as background","papers":2,"sentences":2,"quotes":[{"arxiv_id":"2301.03496","title":"Time-Varying Graph Mode Decomposition","url":"/paper/2301.03496","section":"Introduction","sentence":"Recently, extensions of these methods for multivariate signals have also emerged, namely multivariate extensions of empirical mode decomposition (MEMD) [ref] , variational mode decomposition (MVMD) [ref] and iterative filtering [ref] ; a recent article provides an overview of both univariate and multivariate signal decomposition methods along with their comparative analysis [ref] .","intent_p":0.84,"contests_p":null},{"arxiv_id":"2505.17797","title":"Latent Mode Decomposition","url":"/paper/2505.17797","section":"Introduction","sentence":"A more comprehensive comparison of both univariate and multivariate approaches is presented in [ref] .","intent_p":0.86,"contests_p":null}]}],"unlabelled_sentences":2},"outgoing":{"papers":0,"sentences":0,"groups":[],"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/2208.10874"}}