In recent years, contrastive language-image models such as CLIP have established themselves as a default choice for learning vision representations, particularly in multimodal applications like Visual ...

By scaling model size and training data, we show that vision-only models can match and even surpass language-supervised methods like CLIP, challenging the prevailing assumption that language ...

Note: *_sem_* representations are based on the classification level (probability distribution) of respective models.

Additionally, our AVE feature enhancement scheme develops intermodal correspondences through audio-visual interaction fusion, aligning the feature representations of AVEs temporally. To further ...

Abstract: Self-supervised visual pre-training models have achieved significant success without employing expensive annotations. Nevertheless, most of these models focus on iconic single-instance ...

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews. This fMRI study shows that two regions of the visual cortex ...

The masks of visual areas used in the study. The masks of Brodmann areas 17 (primary visual cortex, red), 18 (secondary visual cortex, green), and 19 (associative visual cortex, blue) are presented on ...

This is undoubtedly one of the best visual representations of how large language models (LLMs) truly function. ⬇️ Let’s break it down: Tokenization & Embeddings: The input text is divided ...

India has rejected the attempts to introduce new parameters, including religion and faith as the basis for representation in a reformed UN Security Council (UNSC). New Delhi asserted that the ...