Yulia Grishina — accepted AI-conference papers

2024

Efficient Performance Tracking: Leveraging Large Language Models for Automated Construction of Scientific Leaderboards

Furkan Şahinuç, Thy Thy Tran, Yulia Grishina, Yufang Hou, Bei Chen, Iryna Gurevych

EMNLP 2024main

Scientific leaderboards are standardized ranking systems that facilitate evaluating and comparing competitive methods. Typically, a leaderboard is defined by a task, dataset, and evaluation metric (TDM) triple, allowing objective performance assessment and fostering innovation through benchmarking.…

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2022

Local-to-global learning for iterative training of production SLU models on new features

Yulia Grishina, Daniil Sorokin

NAACL 2022industry

In production SLU systems, new training data becomes available with time so that ML models need to be updated on a regular basis. Specifically, releasing new features adds new classes of data while the old data remains constant. However, retraining the full model each time from scratch is computatio…

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