{"arxiv_id":"2306.11167","incoming":{"papers":4,"sentences":6,"groups":[{"kind":"supports_this_paper","label":"Cites it as support","papers":1,"sentences":1,"quotes":[{"arxiv_id":"2405.01453","title":"Creative Problem Solving in Large Language and Vision Models -- What Would it Take?","url":"/paper/2405.01453","section":"Introduction","sentence":"Similar observations have been made in follow up work showing that state-of-the-art LLMs inherently possess poor creative problem solving capabilities compared to humans [ref] .","intent_p":1.0,"contests_p":null}]}],"unlabelled_sentences":5},"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/2306.11167"}}