# Like a bilingual baby: The advantage of visually grounding a bilingual language model Source: [Like a bilingual baby: The advantage of visually grounding a bilingual language model]() Collection index: [llms.txt]() Data updated: 2026-07-29T05:00:09.748Z Authors: Khai-Nguyen Nguyen, Zixin Tang, Ankur Mali, Mary ALexandria Kelly Published: 2022-10-11T14:43:26.000Z ## Abstract Unlike most neural language models, humans learn language in a rich, multi-sensory and, often, multi-lingual environment. Current language models typically fail to fully capture the complexities of multilingual language use. We train an LSTM language model on images and captions in English and Spanish from MS-COCO-ES. We find that the visual grounding improves the model's understanding of semantic similarity both within and across languages and improves perplexity. However, we find no significant advantage of visual grounding for abstract words. Our results provide additional evidence of the advantages of visually grounded language models and point to the need for more naturalistic language data from multilingual speakers and multilingual datasets with perceptual grounding. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. ## Original sources and implementation [Original paper]() [PDF]()