2 papers
cs.CL2026
GRACE-DS: a Guarded Reward-guided Agent Correction Environment in Data Science
Aleksandr Tsymbalov, Danis Zaripov, Artem Epifanov +1
We introduce GRACE-DS, a Guarded Reward-guided Agent Correction Environment in Data Science for pre-deployment evaluation of LLM-powered AutoML agents. GRACE-DS is a set of evaluat…
cs.CL2025
Large Language Models in the Task of Automatic Validation of Text Classifier Predictions
Aleksandr Tsymbalov, Mikhail Khovrichev
Machine learning models for text classification are trained to predict a class for a given text. To do this, training and validation samples must be prepared: a set of texts is col…