Gleb Kuzmin

Towards Computationally Feasible Deep Active Learning

2022 · Findings of the Association for Computational Linguistics: NAACL 2022

Active learning (AL) is a prominent technique for reducing the annotation effort required for training machine learning models. Deep learning offers a solution for several essential obstacles to deploying AL in practice but introduces many …

Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification

2024 · arXiv (Cornell University)

Large language models (LLMs) are notorious for hallucinating, i.e., producing erroneous claims in their output. Such hallucinations can be dangerous, as occasional factual inaccuracies in the generated text might be obscured by the rest of …