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reading correctly credits Hien Thanh Doan, Yeji Lim and Hongseok Kim as the authors. Performance figures are kept as author reports ('the authors report'), not presented as established fact.","excerpt":"Authors:Hien Thanh Doan, Yeji Lim, Hongseok Kim"},{"dimension":"summary","status":"pass","explanation":"The summary leads with the actor and the proposal. It gives a plain-language gloss of NCUC and states the core argument: earlier learning methods still need a solver to repair predictions, which limits speed, while FALCON-UC avoids this at inference. The numbers, the comparison and the scope limits are faithful. 'Mixed-integer program', 'bus' and 'inference' are not explained in the text and are candidates for term-library tooltips, but the central idea is still understandable. The question follows directly from the stated scope.","excerpt":"usually still rely on an optimization solver to repair or complete their predictions, which limits the speedup they can deliver"},{"dimension":"date","status":"pass","explanation":"The originalPublished value, 2026-11-08, matches the arXiv v1 submission date. The feed date of 2026-11-10 is correctly not used.","excerpt":"[Submitted on 8 Nov 2026]"},{"dimension":"support","status":"pass","explanation":"All four claims match the quoted abstract text. The closing inference, that the results 'suggest a way to reduce solver use in these evaluations', is scoped to the tested systems. The reading explicitly does not extend the results to real-world performance. No benefits or costs are invented.","excerpt":"MTLR R-SCUC-FL is slightly more accurate but still needs an optimization solver to complete each schedule, which takes $262.2$ s per instance"},{"dimension":"media","status":"pass","explanation":"The selected media is the verified arXiv abstract page for this paper. It is the direct original source.","excerpt":null}],"createdAt":"2026-11-12T11:02:29.747Z","model":"anthropic/claude-opus-5.5"}],"correctionUrl":"https://escapemeridian.com/corrections/"}