---
title: "Who cites Alberto Testoni — 132 papers of our library"
description: "132 papers of the Elamur Research library cite the works of Alberto Testoni, found in their bibliographies; the most cited first."
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---
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# Who cites Alberto Testoni

133 citations of their works from 132 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← Alberto Testoni](https://md.research.elamur.ai/free/en/authors/alberto-testoni/)

1. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
2. **[The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs](https://md.research.elamur.ai/free/en/papers/calderon-2025-alternative-annotator-test-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitay Calderon, Roi Reichart, Rotem Dror*2025 · 52 citations*
3. **[CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists](https://md.research.elamur.ai/free/en/papers/lee-2025-checkeval-reliable-llm-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yukyung Lee, JoongHoon Kim, Jaehee Kim, et al.*2025 · 37 citations*
4. **[Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance](https://md.research.elamur.ai/free/en/papers/nahum-2025-are-llms-better-than-reported/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Omer Nahum, Nitay Calderon, Orgad Keller, et al.*2025 · 27 citations*
5. **[JuStRank: Benchmarking LLM Judges for System Ranking](https://md.research.elamur.ai/free/en/papers/gera-2025-justrank-benchmarking-llm-judges-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ariel Gera, Odellia Boni, Yotam Perlitz, et al.*2025 · 15 citations*
6. **[Value Profiles for Encoding Human Variation](https://md.research.elamur.ai/free/en/papers/sorensen-2025-value-profiles-encoding-human-variation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.*2025 · 15 citations*
7. [**From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks arXiv:2409.04168**Andreas Stephan, Dawei Zhu, Matthias Aßenmacher, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/stephan-2024-calculation-adjudication-examining-llm-judges/)
8. [**Advancing Dialectal Arabic to Modern Standard Arabic Machine Translation arXiv:2507.20301**Abdullah Alabdullah, Lifeng Han, Chenghua Lin*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/alabdullah-2025-advancing-dialectal-arabic-modern-standard/)
9. **[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*
10. **[Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation](https://md.research.elamur.ai/free/en/papers/moon-2026-don-t-judge-code-its/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiwon Moon, Yerin Hwang, Dongryeol Lee, et al.*2026 · 5 citations*
11. **[Do Large Language Models Reflect Demographic Pluralism in Safety?](https://md.research.elamur.ai/free/en/papers/naseem-2026-do-large-language-models-reflect/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Usman Naseem, Gautam Siddharth Kashyap, Sushant Kumar Ray, et al.*2026 · 3 citations*
12. **[Native Design Bias: Studying the Impact of English Nativeness on Language Model Performance](https://md.research.elamur.ai/free/en/papers/reusens-2025-native-design-bias-studying-impact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Manon Reusens, Philipp Borchert, Jochen De Weerdt, et al.*2025 · 3 citations*
13. **[Garbage In, Reasoning Out? Why Benchmark Scores are Unreliable and What to Do About It](https://md.research.elamur.ai/free/en/papers/mousavi-2026-garbage-reasoning-out-why-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seyed Mahed Mousavi, Edoardo Cecchinato, Lucia Horníková, et al.*2026 · 2 citations*
14. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation*
15. **[Automated Creativity Evaluation of Language Models Across Open-Ended Tasks](https://md.research.elamur.ai/free/en/papers/sen-2026-automated-creativity-evaluation-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tan Min Sen, Zachary Choy Kit Chun, Syed Ali Redha Alsagoff, et al.*2026 · 1 citation*
16. **[BitBypass: A New Direction in Jailbreaking Aligned Large Language Models with Bitstream Camouflage](https://md.research.elamur.ai/free/en/papers/nakka-2026-bitbypass-new-direction-jailbreaking-aligned/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kalyan Nakka, Nitesh Saxena*2026 · 1 citation*
17. [**Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles arXiv:2604.21152**Irti Haq, Belen Saldias*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/haq-2026-dialect-vs-demographics-quantifying-llm/)
18. **[MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues](https://md.research.elamur.ai/free/en/papers/liu-2026-mtmcs-bench-evaluating-contextual-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Liu, Dongwhi Kim, Yixin Wan, et al.*2026 · 1 citation*
19. **[Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation Task](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*2026 · 1 citation*
20. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*
21. **[Actionable Interpretability for Churn Classification: A Text Bottleneck Model Case Study at a Major Telecom Provider](https://md.research.elamur.ai/free/en/papers/sauter-2026-actionable-interpretability-churn-classification-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Adrian Sauter, Vera Neplenbroek, Georgios Vlassopoulos, et al.*2026*
22. **[Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns](https://md.research.elamur.ai/free/en/papers/pauli-2026-analysing-differences-persuasive-language-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amalie Brogaard Pauli, Maria Barrett, Max Müller-Eberstein, et al.*2026*
23. **[Argument-Based Comparative Question Answering Evaluation Benchmark](https://md.research.elamur.ai/free/en/papers/nikishina-2026-argument-based-comparative-question-answering/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Irina Nikishina, Saba Anwar, Nikolay Dolgov, et al.*2026*
24. **[Automatic Paper Analysis and Categorisation for Systematic Reviews with Combined Reasoning-Augmented SFT and DAPO RL](https://md.research.elamur.ai/free/en/papers/lorandi-2026-automatic-paper-analysis-categorisation-systematic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michela Lorandi, Anya Belz, Simon Mille, et al.*2026*
25. **[Calibrated? Not for Everyone: How Sexual Orientation and Religious Markers Distort LLM Accuracy and Confidence in Medical QA](https://md.research.elamur.ai/free/en/papers/testoni-2026-calibrated-not-everyone-how-sexual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alberto Testoni, Iacer Calixto*2026*
26. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
27. **[Combining Distantly Supervised Models with In Context Learning for Monolingual and Cross-Lingual Relation Extraction](https://md.research.elamur.ai/free/en/papers/rathore-2026-combining-distantly-supervised-models-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vipul Kumar Rathore, Malik Hammad Faisal, Parag Singla, et al.*2026*
28. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
29. **[DialogGuard: Multi-Agent Psychosocial Safety Evaluation Interface of Sensitive LLM Responses](https://md.research.elamur.ai/free/en/papers/luo-2026-dialogguard-multi-agent-psychosocial-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Luo, Guy Laban*2026*
30. **[Evaluation of Document-Level Text Simplification in Japanese](https://md.research.elamur.ai/free/en/papers/yamashita-2026-evaluation-document-level-text-simplification/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iori Yamashita, Hikari Tanaka, Hajime Kiyama, et al.*2026*
31. **[GlossMATE: Multi-Agent Translator Explanations for Glosses](https://md.research.elamur.ai/free/en/papers/yang-2026-glossmate-multi-agent-translator-explanations/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Changbing Yang, Patrick Littell, Gabriel Bernier-Colborne, et al.*2026*
32. **[HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop Questions](https://md.research.elamur.ai/free/en/papers/shen-2026-hopweaver-cross-document-synthesis-high/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Shen, Jiyuan Liu, Yunhe Pang, et al.*2026*
33. **[How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-how-much-would-clinician-edit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Joseph Gatto, Sarah E. Greer, et al.*2026*
34. **[Judging Instruction Responses in a Low-Resource Language: A Case Study on Basque](https://md.research.elamur.ai/free/en/papers/ponce-2026-judging-instruction-responses-low-resource/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**David Ponce, Harritxu Gete, Thierry Etchegoyhen, et al.*2026*
35. **[LLMs as annotators of credibility assessment in Danish asylum decisions: evaluating classification performance and errors beyond aggregated metrics](https://md.research.elamur.ai/free/en/papers/renaux-2026-llms-as-annotators-credibility-assessment/) [Linguistic Annotation Workshop (LAW)](https://md.research.elamur.ai/free/en/venues/law/)**Galadrielle Humblot-Renaux, Mohammad N. S. Jahromi, Rohat Bakuri-Jørgensen, et al.*2026*
36. **[Never Truly Out of Fashion: A Retrospective Look at Evaluation in NLG](https://md.research.elamur.ai/free/en/papers/schmidtova-2026-never-truly-out-fashion-retrospective/) [Symposium on Natural Language Generation Evaluations](https://md.research.elamur.ai/free/en/venues/retroeval/)**Patrícia Schmidtová, Saad Mahamood, Ondřej Dušek*2026*
37. **[Rethinking Evaluation in Retrieval-Augmented Personalized Dialogue: A Cognitive and Linguistic Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2026-rethinking-evaluation-retrieval-augmented-personalized/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tianyi Zhang, David Traum*2026*
38. **[Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/schaffelder-2026-synthetic-eggs-many-baskets-impact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Max Schaffelder, Albert Gatt*2026*
39. **[TextMineX: Data, Evaluation Framework and Ontology-guided LLM Pipeline for Humanitarian Mine Action](https://md.research.elamur.ai/free/en/papers/zhou-2026-textminex-data-evaluation-framework-ontology/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenyue Zhou, Gürkan Solmaz, Flavio Cirillo, et al.*2026*
40. [**LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade arXiv:2509.07274**Aida Kostikova, Ole Putz, Steffen Eger, et al.*2025*](https://md.research.elamur.ai/free/en/papers/kostikova-2025-llm-analysis-150-years-german/)

92 more citing papers of our library have no page here yet.

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