Fractal

Toloka Education

We collaborate with universities and researchers to share expertise 
in human data labeling and promote Responsible AI.

Reach out

For researchers and educators

We have 10+ years of research and unique industry expertise to share.

  • Guest lecturesYou can invite our speaker to give a lecture for your course, or we can organize an independent event.Talk to us
  • Conference supportWe can help you organize workshops, tutorials or panel discussions. To propose collaboration on scientific projects, contact our Research team.Toloka Research

University partnerships

We run tutorials and workshops, provide grants and educational materials, and take part in scientific events all over the world. 
If you'd like to join us, reach out to discuss a long-term partnership.

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Sponsorship of student projects in crowdsourcing courses at TU Delft & PennState

Many educators need data sets and projects for their courses, and we believe in supporting educators and students with access to human data labeling. At the moment we are proud sponsors of the Crowd Computing Course at TUDelft and the Crowdsourcing & Crowd-AI Systems Course at Pennsylvania State University. Every course starts with a hands-on tutorial that demonstrates real use cases. Then participants use Toloka to collect and label data free of charge. At the end of the course we run a group project presentation with invited experts.

Sponsorship

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Saiph Savage, Director, Civic A.I. Lab Northeastern University & UNAM

We are creating technology that is empowering workers while also ensuring quality labor for the projects of academics and industry actors. Our collaborative research led us to be recognized by UNESCO as one of the 100 most impactful projects in AI. This collaboration has also helped us develop crowdsourcing mini-courses at Northeastern University and the Universidad Nacional Autonoma de Mexico (UNAM).

Guest lectures

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Materials used in the “Global UX” course at Northeastern University, USA

We provide educators with learning materials that can be easily included in a course or used independently. For example, our materials are used in the Global UX course at Northeastern University. When we share our materials and expertise with faculty members, we also teach them how to apply all of that in the most efficient way.

Educational resources

Toloka at top-tier conferences

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Past event
ICML '23
Reinforcement Learning from Human Feedback: A Tutorial.
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ECIR '23
Human-in-the-Loop learning for information retrieval.
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WSDM '23
CANDLE: Collaboration of Humans and Learning Algorithms for Data Labeling.
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Past event
NeurIPS '22
Toloka social at NeurIPS 2022. From old biases to new opportunities: Annotator empowerment and data excellence.
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Past event
RecSys '22
We shared more than six years of our crowdsourcing experience and bridge the gap between crowdsourcing and recommender systems communities.
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CHI '22
This сrowd science workshop explores how a reimagined perspective on crowdsourcing platforms could provide a more equitable, fair, and rewarding experience.
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VLDB '21
This crowd science workshop focuses on the best practices for efficient and trustworthy crowdsourcing.
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ICML '21
High-Quality Data Labeling at Scale with Toloka workshop aims to provide a comprehensive picture of how crowdsourcing can be applied to real life AI production.
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NAACL-HLT '21
We shared some of the unique insights we have gained from six years of industry experience in efficient natural language data.
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TheWebConf '21
In this tutorial, we presented a systematic view on using Human-in-the-Loop to obtain scalable offline evaluation processes and high-quality relevance judgements
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NeurIPS '20
At this сrowd science workshop we discussed key issues in preparing labeled data for machine learning, with a focus on remoteness, fairness, and mechanisms in the context of crowdsourcing for data collection and labeling.
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CVPR '20
We presented a data processing pipeline used for training self-driving cars. Participants gained practical experience launching an annotation project in Toloka.
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SIGMOD '20
We explored the practical aspects of how crowdsourcing can be applied to information retrieval. Participants learnt how to create a dataset with relevant products.
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WSDM '20
We explored the practice of efficient data collection via crowdsourcing: aggregation, incremental relabeling, and pricing.
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KDD '19
We introduced data labeling via public crowdsourcing marketplaces and presented the key components of efficient label collection.
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Where to learn more

Interested in collaboration?

Let's talk about how we can support your education initiatives
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