🧑‍🔬 Who cites Daniil Vasilev

104 citations of their works from 88 papers of our library (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · ← Daniil Vasilev

1. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty QuantificationFindings of the Association for Computational LinguisticsEkaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.2024 · 96 citations
2. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
3. LUQ: Long-text Uncertainty Quantification for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.2024 · 42 citations
4. AbstentionBench: Reasoning LLMs Fail on Unanswerable QuestionsConference on Neural Information Processing Systems (NeurIPS)Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri, et al.2025 · 35 citations
5. Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back HomeAnnual Meeting of the Association for Computational Linguistics (ACL)Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.2025 · 21 citations
6. LoGU: Long-form Generation with Uncertainty ExpressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Ruihan Yang, Caiqi Zhang, Zhisong Zhang, et al.2025 · 13 citations
7. Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Artem Vazhentsev, Lyudmila Rvanova, Ivan Lazichny, et al.2025 · 13 citations
8. A Probabilistic Framework for LLM Hallucination Detection via Belief Tree PropagationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bairu Hou, Yang Zhang, Jacob Andreas, et al.2025 · 12 citations
9. Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
10. Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing, et al.2025 · 10 citations
11. Knowing When to Abstain: Medical LLMs Under Clinical UncertaintyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sravanthi Machcha, Sushrita Yerra, Sahil Gupta, et al.2026 · 9 citations
12. Thinking Out Loud: Do Reasoning Models Know When They're Right?Conference on Empirical Methods in Natural Language Processing (EMNLP)Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.2025 · 9 citations
13. Revisiting Epistemic Markers in Confidence Estimation: Can Markers Accurately Reflect Large Language Models' Uncertainty?Annual Meeting of the Association for Computational Linguistics (ACL)Jiayu Liu, Qing Zong, Weiqi Wang, et al.2025 · 8 citations
14. MetaFaith: Faithful Natural Language Uncertainty Expression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.2025 · 6 citations
15. Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias ResultsAnnual Meeting of the Association for Computational Linguistics (ACL)Andrea Santilli, Adam Golinski, Michael Kirchhof, et al.2025 · 6 citations
16. Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is MissingTransactions of the Association for Computational Linguistics (TACL)Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.2026 · 4 citations
17. Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and OpportunitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Changdae Oh, Seongheon Park, To Eun Kim, et al.2026 · 4 citations
18. Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model UncertaintyAnnual Meeting of the Association for Computational Linguistics (ACL)Jingyi Ren, Ante Wang, Yunghwei Lai, et al.2026 · 3 citations
19. Chain-of-Thought as a Lens: Evaluating Structured Reasoning Alignment between Human Preferences and Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Boxuan Wang, Zhuoyun Li, Xinmiao Huang, et al.2026 · 1 citation
20. Efficient Self-Evaluation for Diffusion Language Models via Sequence RegenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Linhao Zhong, Linyu Wu, Wen Wang, et al.2026 · 1 citation
21. From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language ModelsFindings of the Association for Computational LinguisticsJiaxin Zhang, Wendi Cui, Zhuohang Li, et al.2026 · 1 citation
22. Reference Games as a Testbed for the Alignment of Model Uncertainty and Clarification RequestsWorkshop on Generation, Evaluation and Metrics (GEM)Manar Ali, Judith Sieker, Sina Zarrieß, et al.2026 · 1 citation
23. ReProbe: Efficient Test-Time Scaling of Multi-Step Reasoning by Probing Internal States of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jingwei Ni, Ekaterina Fadeeva, Tianyi Wu, et al.2026 · 1 citation
24. Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention MapsFindings of the Association for Computational LinguisticsJonas Waldendorf, Bashar Awwad Shiekh Hasan, Evgenii Tsymbalov2026
25. DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy InputsAnnual Meeting of the Association for Computational Linguistics (ACL)Bo Zhang, Jiawei Zhang, Cong Gao, et al.2026
26. Evaluation Pitfalls and Sparsity Limitations in LLM-based Confidence Estimates for ClassificationFindings of the Association for Computational LinguisticsElena Merdjanovska, Omar Zaidan, Andreas Rücklé2026
27. Evolutionary Search for Automated Design of Uncertainty Quantification MethodsAnnual Meeting of the Association for Computational Linguistics (ACL)Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.2026
28. From Standard Transformers to Modern LLMs: Bringing Dialogue Models, RAG, and Agents to the ClassroomWorkshop on Teaching Natural Language ProcessingMaria Tikhonova, Viktoriia A. Chekalina, Artem Chervyakov, et al.2026
29. LAFaCT: Attribution-based Localization and Focused Sequential Analysis of Fact-Critical Tokens for Hallucination DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Wang, Jiahao Li, Licheng Zhang, et al.2026
30. Learning Uncertainty from Sequential Internal Dispersion in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.2026
31. The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic TruthfulnessAnnual Meeting of the Association for Computational Linguistics (ACL)Yueheng Mao, Min Yu, Gengwang Li, et al.2026
32. ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.2026

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