--- title: "Who cites Lyudmila Rvanova — 54 papers of our library" description: "54 papers of the Elamur Research library cite the works of Lyudmila Rvanova, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/lyudmila-rvanova/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/lyudmila-rvanova/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Lyudmila Rvanova](https://md.research.elamur.ai/free/en/authors/lyudmila-rvanova/) / cited by # Who cites Lyudmila Rvanova 61 citations of their works from 54 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← Lyudmila Rvanova](https://md.research.elamur.ai/free/en/authors/lyudmila-rvanova/) 1. **[Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-token-level-density-based-uncertainty/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.*2025 · 13 citations* 2. **[Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.*2025 · 11 citations* 3. **[Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models](https://md.research.elamur.ai/free/en/papers/vazhentsev-2025-unconditional-truthfulness-learning-unconditional-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.*2025 · 10 citations* 4. **[Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty](https://md.research.elamur.ai/free/en/papers/machcha-2026-knowing-when-abstain-medical-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sravanthi Machcha, Sushrita Yerra, Sahil Gupta, et al.*2026 · 9 citations* 5. **[Thinking Out Loud: Do Reasoning Models Know When They're Right?](https://md.research.elamur.ai/free/en/papers/zeng-2025-thinking-out-loud-do-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.*2025 · 9 citations* 6. **[Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?](https://md.research.elamur.ai/free/en/papers/liu-2025-revisiting-epistemic-markers-confidence-estimation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayu Liu, Qing Zong, Weiqi Wang, et al.*2025 · 8 citations* 7. **[Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results](https://md.research.elamur.ai/free/en/papers/santilli-2025-revisiting-uncertainty-quantification-evaluation-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.*2025 · 6 citations* 8. **[Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://md.research.elamur.ai/free/en/papers/ulmer-2026-anthropomimetic-uncertainty-what-verbalized-uncertainty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.*2026 · 4 citations* 9. **[Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty](https://md.research.elamur.ai/free/en/papers/ren-2026-beyond-i-don-t-know/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Ren, Ante Wang, Yunghwei Lai, et al.*2026 · 3 citations* 10. **[Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-chain-thought-as-lens-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boxuan Wang, Zhuoyun Li, Xinmiao Huang, et al.*2026 · 1 citation* 11. **[Efficient Self-Evaluation for Diffusion Language Models via Sequence Regeneration](https://md.research.elamur.ai/free/en/papers/zhong-2026-efficient-self-evaluation-diffusion-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linhao Zhong, Linyu Wu, Wen Wang, et al.*2026 · 1 citation* 12. **[From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-passive-metric-active-signal-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaxin Zhang, Wendi Cui, Zhuohang Li, et al.*2026 · 1 citation* 13. **[Reference Games as a Testbed for the Alignment of Model Uncertainty and Clarification Requests](https://md.research.elamur.ai/free/en/papers/ali-2026-reference-games-as-testbed-alignment/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Manar Ali, Judith Sieker, Sina Zarrieß, et al.*2026 · 1 citation* 14. **[ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language Models](https://md.research.elamur.ai/free/en/papers/ni-2026-reprobe-efficient-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.*2026 · 1 citation* 15. **[Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps](https://md.research.elamur.ai/free/en/papers/waldendorf-2026-detecting-hallucinations-speechllms-inference-time/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jonas Waldendorf, Bashar Awwad Shiekh Hasan, Evgenii Tsymbalov*2026* 16. **[Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for Classification](https://md.research.elamur.ai/free/en/papers/merdjanovska-2026-evaluation-pitfalls-sparsity-limitations-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Elena Merdjanovska, Omar Zaidan, Andreas Rücklé*2026* 17. **[Evolutionary Search for Automated Design of Uncertainty Quantification Methods](https://md.research.elamur.ai/free/en/papers/seleznyov-2026-evolutionary-search-automated-design-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.*2026* 18. **[From Standard Transformers to Modern LLMs: Bringing Dialogue Models, RAG, and Agents to the Classroom](https://md.research.elamur.ai/free/en/papers/tikhonova-2026-standard-transformers-modern-llms-bringing/) [Workshop on Teaching Natural Language Processing](https://md.research.elamur.ai/free/en/venues/teachingnlp/)**Maria Tikhonova, Viktoriia A. Chekalina, Artem Chervyakov, et al.*2026* 19. **[LAFaCT: Attribution-based Localization and Focused Sequential Analysis of Fact-Critical Tokens for Hallucination Detection](https://md.research.elamur.ai/free/en/papers/wang-2026-lafact-attribution-based-localization-focused/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Wang, Jiahao Li, Licheng Zhang, et al.*2026* 20. **[Learning Uncertainty from Sequential Internal Dispersion in Large Language Models](https://md.research.elamur.ai/free/en/papers/srey-2026-learning-uncertainty-sequential-internal-dispersion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.*2026* 21. **[ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning](https://md.research.elamur.ai/free/en/papers/smirnov-2026-thinkbooster-unified-framework-seamless-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.*2026* 33 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/lyudmila-rvanova/) — Lyudmila Rvanova