{"arxiv_id":"2607.13613","incoming":{"papers":0,"sentences":0,"groups":[],"unlabelled_sentences":0},"outgoing":{"papers":1,"sentences":1,"groups":[{"kind":"background","label":"Cites as background","papers":1,"sentences":1,"quotes":[{"arxiv_id":"2305.00001","title":"Feature Embedding Clustering using POCS-based Clustering Algorithm","url":"/paper/2305.00001","section":"Introduction","sentence":"Clustering remains a core task in unsupervised learning, with applications spanning pattern discovery, compression, anomaly detection, and post-processing [ref] .","intent_p":0.98,"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/2607.13613"}}