
Aishwarya Agrawal
@aagrawalAA
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Assistant Professor @UMontrealDIRO and @Mila_Quebec Research Scientist @DeepMind
Montreal, Canada
Joined July 2013
We will present this work in the afternoon poster session today at #CVPR2025, poster #322, Exhibition Hall D, 4-6pm. Do stop by if you are interested in learning how to extract visual features for *specific* concepts specified by language queries!.
Check out our latest work (published at CVPR 2025) on learning language-controllable visual representations.
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Check out our latest work on how to do data efficient instruction tuning of multimodal large language models. The key idea is to let the model tell us what training data points it would most benefit learning from at a given stage of training.
Excited to share our paper "Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selection"with an amazing co-lead Shivam Chandhok @ShivamChandhok2!ย We introduce PROGRESS, a data&compute-efficient framework for training VLMs!
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RT @QianYangMila: Excited to share our paper "Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selectioโฆ.
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@QianYangMila presenting our #CVPR25 highlight poster on Assessing and Learning Alignment of Unimodal Vision and Language Models. We propose an approach to learn more language compatible visual representations with minimal training resources: single GPU and just 5 hours of
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Sara Hooker speaking about Aya: Optimization under Severe Constraints @vlms4all workshop in room 104 E now!. We also have swag: mugs, buttons and stickers! So stop-by!
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