16 citations · 21 across the 4 of their papers we have counts for
6 papers
A Computational Approach to Measuring Semantic Change in Sanskrit Literature
Tanay Agrawal
Diachronic word embeddings have become the modern standard for tracking semantic change, yet they have been largely validated on modern, high-resource, and well-segmented languages…
CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets
Tanay Agrawal, Mohammed Guermal, Michal Balazia +1
Challenges in cross-learning involve inhomogeneous or even inadequate amount of training data and lack of resources for retraining large pretrained models. Inspired by transfer lea…
AM Flow: Adapters for Temporal Processing in Action Recognition
Tanay Agrawal, Abid Ali, Antitza Dantcheva +1
Deep learning models, in particular \textit{image} models, have recently gained generalisability and robustness. %are becoming more general and robust by the day. In this work, we…
Multimodal Vision Transformers with Forced Attention for Behavior Analysis
Tanay Agrawal, Michal Balazia, Philipp Müller +1
Human behavior understanding requires looking at minute details in the large context of a scene containing multiple input modalities. It is necessary as it allows the design of mor…
Multimodal Personality Recognition using Cross-Attention Transformer and Behaviour Encoding
Tanay Agrawal, Dhruv Agarwal, Michal Balazia +2
Personality computing and affective computing have gained recent interest in many research areas. The datasets for the task generally have multiple modalities like video, audio, la…
From Multimodal to Unimodal Attention in Transformers using Knowledge Distillation
Dhruv Agarwal, Tanay Agrawal, Laura M. Ferrari +1
Multimodal Deep Learning has garnered much interest, and transformers have triggered novel approaches, thanks to the cross-attention mechanism. Here we propose an approach to deal…