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Ivan Lazichny

Active Learning for Abstractive Text Summarization
2022 · Akim Tsvigun, Ivan Lysenko, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · 13
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ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts
2022 · Akim Tsvigun, Leonid Sanochkin, et al. · Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) · 6
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Active Learning for Abstractive Text Summarization
2023 · Tsvigun, Akim, Lysenko, Ivan, et al. · arXiv (Cornell University) · 3
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Geopolitical biases in LLMs: what are the "good" and the "bad" countries according to contemporary language models
2025 · Salnikov, Mikhail, Korzh, Dmitrii, et al. · arXiv (Cornell University) · 2
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Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
2025 · Artem Vazhentsev, Ekaterina Fadeeva, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2
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Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models
2025 · Artem Vazhentsev, Lyudmila Rvanova, et al. · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · 1
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Reranking Answers of Large Language Models with Knowledge Graphs
2026 · Salnikov, Mikhail, Le, Hai, et al. · arXiv (Cornell University)
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Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads
2025 · Vazhentsev, Artem, Rvanova, Lyudmila, et al. · arXiv (Cornell University)
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Works count: 9
Citation count: 27
H-index: 3
I10-index: 1
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