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This paper describes an approach used to generate new translations using rawbilingual dictionaries as part of the 4th Task Inference Across Dictionaries(TIAD 2021) shared task. We propose Augmented Cycle Density (ACD) as aframework that combines insights from two state of the art methods that requireno sense information and parallel corpora: Cycle Density (CD) and One TimeInverse Consultation (OTIC). The task results show that across 3 unseenlanguage pairs, ACD's predictions, has more than double (74%) the coverage ofOTIC at almost the same precision (76%). ACD combines CD's scalability -leveraging rich multilingual graphs for better predictions, and OTIC's dataefficiency - producing good results with the minimum possible resource of onepivot language.

From Pivots to Graphs: Augmented CycleDensity as a Generalization to One Time InverseConsultation