The question of how meaning might be acquired by young children and represented by adult speakers of a language is one of the most debated topics in cognitive science. Existing semantic representation models are primarily amodal based on information provided by the linguistic input despite ample evidence indicating that the cognitive system is also sensitive to perceptual information. In this w...

Recently, computer vision foundation models such as CLIP and ALI-GN, have shown impressive generalization capabilities on various downstream tasks. But their abilities to deal with the long-tailed data still remain be proved. In this work, we present a novel framework based pre-trained visual-linguistic for recognition (LTR), termed VL-LTR, conduct empirical studies benefits of introducing text...

Knowledge can be expressed in two forms: declarative and procedural. Declarative knowledge describes a set of definitions about the world, while procedural knowledge describes the temporal, spatial and constraint aspects applied within these definitions. Expressing declarative knowledge textually is in some ways difficult to follow, whereas it is virtually impossible to capture all aspects of p...

In [6], we have introduced Complexity Distortion Theory, a mathematical framework characterizing the design of programmable communication systems. In this paper, we show how Complexity Distortion Theory ts in the MPEG-4 context and more generally in any system allowing programmability, by formalizing the concept of programmable decoders. We also show how it can be used to design intelligent enc...

The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerica...