Toloka Research
Our mission
Our team strives to enhance the capabilities and safety of frontier models with valuable data, advanced training and evaluation methods
New data collection methods
for SFT and RLHF that leverage synthetic data, AI feedback, and expert human-generated data.
Improved approaches to model training and alignment
that enhance model capabilities in long-horizon reasoning and autonomous behavior.
High-quality evaluation metrics & benchmarks to measure performance in coding, math, reasoning, multilingualism, multimodality, and other complex tasks.
Red-teaming methods for identifying model vulnerabilities and developing safety metrics such as harmfulness, security and CBRN risks, social bias, and more.
Our projects
Publications
Conferences and events
We regularly hold tutorials and lead workshops at some of the biggest AI conferences around the globe.
Blog
Applied ML at Toloka
We use ML technologies to enhance data production for better data quality, faster data collection, and lower costs.
AI copilots
In-task tools help experts focus on quality: accurate fact checks, grammar checks, suggestions and more
Antifraud algorithms
Fraud prevention built into every data pipeline from start to finish to guarantee authentic human effort and expertise
Matching algorithms
Task distribution system matches tasks to the best qualified annotators and experts
Automated metrics
Our data quality metrics correlate with model performance gains for confidence in training data
