15 citations · 15 across the 3 of their papers we have counts for
3 papers
ATGen: A Framework for Active Text Generation
Akim Tsvigun, Daniil Vasilev, Ivan Tsvigun +12
Active learning (AL) has demonstrated remarkable potential in reducing the annotation effort required for training machine learning models. However, despite the surging popularity…
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev +12
The rapid proliferation of large language models (LLMs) has stimulated researchers to seek effective and efficient approaches to deal with LLM hallucinations and low-quality output…
LM-Polygraph: Uncertainty Estimation for Language Models
Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun +9
Recent advancements in the capabilities of large language models (LLMs) have paved the way for a myriad of groundbreaking applications in various fields. However, a significant cha…