---
title: "Who cites Akim Tsvigun — 179 papers of our library"
description: "179 papers of the Elamur Research library cite the works of Akim Tsvigun, found in their bibliographies; the most cited first."
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---
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# Who cites Akim Tsvigun

195 citations of their works from 179 papers of our library (of the 149,439 whose bibliographies we read) · 52 with a page here, the most cited first · [← Akim Tsvigun](https://md.research.elamur.ai/free/en/authors/akim-tsvigun/)

1. [**Can AI-Generated Text be Reliably Detected? arXiv:2303.11156**Vinu Sankar Sadasivan, Aounon Kumar, Sriram Balasubramanian, et al.*2023 · 306 citations*](https://md.research.elamur.ai/free/en/papers/sadasivan-2023-ai-generated-text-reliably-detected/)
2. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
3. [**Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text arXiv:2401.12070**Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/hans-2024-spotting-llms-binoculars-zero-shot/)
4. **[RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors](https://md.research.elamur.ai/free/en/papers/dugan-2024-raid-shared-benchmark-robust-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.*2024 · 110 citations*
5. **[Fact-Checking the Output of Large Language Models via Token-Level Uncertainty Quantification](https://md.research.elamur.ai/free/en/papers/fadeeva-2024-fact-checking-output-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.*2024 · 96 citations*
6. **[Do-Not-Answer: Evaluating Safeguards in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-do-not-answer-evaluating-safeguards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Haonan Li, Xudong Han, et al.*2024 · 93 citations*
7. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
8. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
9. **[LUQ: Long-text Uncertainty Quantification for LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2024-luq-long-text-uncertainty-quantification/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.*2024 · 42 citations*
10. **[SemEval-2026 Task 13: Detecting Machine-Generated Code with Multiple Programming Languages, Generators, and Application Scenarios](https://md.research.elamur.ai/free/en/papers/orel-2026-semeval-2026-task-13-detecting/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 41 citations*
11. **[The AraGenEval Shared Task on Arabic Authorship Style Transfer and AI Generated Text Detection](https://md.research.elamur.ai/free/en/papers/abudalfa-2025-arageneval-shared-task-arabic-authorship/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Shadi Abudalfa, Saad Ezzini, Ahmed Abdelali, et al.*2025 · 36 citations*
12. **[People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://md.research.elamur.ai/free/en/papers/russell-2025-people-who-frequently-use-chatgpt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Mohit Iyyer*2025 · 33 citations*
13. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
14. **[Adaptive Retrieval Without Self-Knowledge? Bringing Uncertainty Back Home](https://md.research.elamur.ai/free/en/papers/moskvoretskii-2025-adaptive-retrieval-without-self-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viktor Moskvoretskii, Maria Marina, Mikhail Salnikov, et al.*2025 · 21 citations*
15. **[LoGU: Long-form Generation with Uncertainty Expressions](https://md.research.elamur.ai/free/en/papers/yang-2025-logu-long-form-generation-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruihan Yang, Caiqi Zhang, Zhisong Zhang, et al.*2025 · 13 citations*
16. **[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*
17. **[A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation](https://md.research.elamur.ai/free/en/papers/hou-2025-probabilistic-framework-llm-hallucination-detection/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bairu Hou, Yang Zhang, Jacob Andreas, et al.*2025 · 12 citations*
18. **[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*
19. **[AbjadGenEval: Abjad AI Generated Text Detection Shared Task for Languages Using Arabic Script at AbjadNLP 2026](https://md.research.elamur.ai/free/en/papers/ezzini-2026-abjadgeneval-abjad-ai-generated-text/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Saad Ezzini, Irfan Ahmad, Salmane Chafik, et al.*2026 · 10 citations*
20. **[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*
21. **[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*
22. **[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*
23. **[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*
24. **[MetaFaith: Faithful Natural Language Uncertainty Expression in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-metafaith-faithful-natural-language-uncertainty/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gabrielle Kaili-May Liu, Gal Yona, Avi Caciularu, et al.*2025 · 6 citations*
25. **[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*
26. **[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*
27. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
28. **[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*
29. **[FAID: Fine-grained AI-generated Text Detection using Multi-task Auxiliary and Multi-level Contrastive Learning](https://md.research.elamur.ai/free/en/papers/ta-2026-faid-fine-grained-ai-generated/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minh Ngoc Ta, Dong Cao Van, Duc-Anh Hoang, et al.*2026 · 3 citations*
30. **[Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis](https://md.research.elamur.ai/free/en/papers/xia-2026-explaining-generalization-ai-generated-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxi Xia, Kinga Stańczak, Benjamin Roth*2026 · 2 citations*
31. **[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*
32. **[DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution](https://md.research.elamur.ai/free/en/papers/teja-2026-damasha-detecting-ai-mixed-adversarial/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan, et al.*2026 · 1 citation*
33. **[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*
34. **[Frankentext: Stitching random text fragments into long-form narratives](https://md.research.elamur.ai/free/en/papers/pham-2026-frankentext-stitching-random-text-fragments/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chau Minh Pham, Jenna Russell, Dzung Pham, et al.*2026 · 1 citation*
35. **[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*
36. **[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*
37. **[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*
38. **[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*
39. **[DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection](https://md.research.elamur.ai/free/en/papers/wu-2026-detectrl-x-reliable-multilingual-real/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junchao Wu, Yefeng Liu, Chenyu Zhu, et al.*2026*
40. **[DisCal: Distribution-Aware Calibration for Mathematical Reasoning Under Character-Level Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-discal-distribution-aware-calibration-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Zhang, Jiawei Zhang, Cong Gao, et al.*2026*
41. **[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*
42. **[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*
43. **[Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI](https://md.research.elamur.ai/free/en/papers/man-2026-explainable-disentangled-representation-learning-generalizable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hieu Man, Van-Cuong Pham, Nghia Trung Ngo, et al.*2026*
44. **[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*
45. **[GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*
46. **[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*
47. **[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*
48. **[Reasoning-Aware AIGC Detection via Alignment and Reinforcement](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoning-aware-aigc-detection-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhao Wang, Max Xiong, Jianxun Lian, et al.*2026*
49. **[SearchLLM: Detecting LLM Paraphrased Text by Measuring the Similarity with Regeneration of the Candidate Source via Search Engine](https://md.research.elamur.ai/free/en/papers/son-2026-searchllm-detecting-llm-paraphrased-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hoang-Quoc Nguyen-Son, Minh-Son Dao, Koji Zettsu*2026*
50. **[The Digital Dunning-Kruger Effect: Decoupling Hallucinations via Geometric Hidden-state Observation for Semantic Truthfulness](https://md.research.elamur.ai/free/en/papers/mao-2026-digital-dunning-kruger-effect-decoupling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueheng Mao, Min Yu, Gengwang Li, et al.*2026*
51. **[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*
52. **[What Are LLMs Doing to Scientific Communication? Measuring Changes in Writing Practices and Reading Experience](https://md.research.elamur.ai/free/en/papers/miletic-2026-what-are-llms-doing-scientific/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Filip Miletić, Neele Falk*2026*

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