7.4k citations · 11.1k across the 11 of their papers we have counts for
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cs.LG2014★ 1.3k cited
Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models
Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel
Inspired by recent advances in multimodal learning and machine translation, we introduce an encoder-decoder pipeline that learns (a): a multimodal joint embedding space with images…
cs.LG2014★ 38 cited
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations
Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov
In this paper we propose a general framework for learning distributed representations of attributes: characteristics of text whose representations can be jointly learned with word…