---
title: "Who cites Francesca Toni — 259 papers of our library"
description: "259 papers of the Elamur Research library cite the works of Francesca Toni, found in their bibliographies; the most cited first."
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---
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# Who cites Francesca Toni

294 citations of their works from 259 papers of our library (of the 149,439 whose bibliographies we read) · 36 with a page here, the most cited first · [← Francesca Toni](https://md.research.elamur.ai/free/en/authors/francesca-toni/)

1. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
2. **[A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 647 citations*
3. **[Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al.*2022 · 295 citations*
4. **[A Survey of the State of Explainable AI for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/danilevsky-2020-survey-state-explainable-ai-natural/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Marina Danilevsky, Kun Qian, Ranit Aharonov, et al.*2020 · 294 citations*
5. **[A Diagnostic Study of Explainability Techniques for Text Classification](https://md.research.elamur.ai/free/en/papers/atanasova-2020-diagnostic-study-explainability-techniques-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 274 citations*
6. **[Learning to Faithfully Rationalize by Construction](https://md.research.elamur.ai/free/en/papers/jain-2020-learning-faithfully-rationalize-construction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sarthak Jain, Sarah Wiegreffe, Yuval Pinter, et al.*2020 · 225 citations*
7. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
8. **[Retrieval of the Best Counterargument without Prior Topic Knowledge](https://md.research.elamur.ai/free/en/papers/wachsmuth-2018-retrieval-best-counterargument-without-prior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Henning Wachsmuth, Shahbaz Syed, Benno Stein*2018 · 197 citations*
9. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
10. **[Explanations for CommonsenseQA: New Dataset and Models](https://md.research.elamur.ai/free/en/papers/aggarwal-2021-explanations-commonsenseqa-new-dataset-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shourya Aggarwal, Divyanshu Mandowara, Vishwajeet Agrawal, et al.*2021 · 164 citations*
11. **[Fact-Checking Complex Claims with Program-Guided Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 146 citations*
12. **[Evidence-based Fact-Checking of Health-related Claims](https://md.research.elamur.ai/free/en/papers/sarrouti-2021-evidence-based-fact-checking-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, et al.*2021 · 129 citations*
13. [**AVeriTeC: A Dataset for Real-world Claim Verification with Evidence from the Web arXiv:2305.13117**Michael Schlichtkrull, Zhijiang Guo, Andreas Vlachos*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/schlichtkrull-2023-averitec-dataset-real-world-claim/)
14. **[SciFact-Open: Towards open-domain scientific claim verification](https://md.research.elamur.ai/free/en/papers/wadden-2022-scifact-open-open-domain-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**David Wadden, Kyle Lo, Bailey Kuehl, et al.*2022 · 94 citations*
15. **[Medical Graph RAG: Evidence-based Medical Large Language Model via Graph Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wu-2025-medical-graph-rag-evidence-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junde Wu, Jiayuan Zhu, Yunli Qi, et al.*2025 · 91 citations*
16. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
17. **[Explanation-Based Human Debugging of NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/lertvittayakumjorn-2021-explanation-based-human-debugging-nlp/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Piyawat Lertvittayakumjorn, Francesca Toni*2021 · 77 citations*
18. [**Interpretable Unified Language Checking arXiv:2304.03728**Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-interpretable-unified-language-checking/)
19. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
20. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
21. **[Evaluating Large Language Models for Health-related Queries with Presuppositions](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*
22. **[Tailoring Self-Rationalizers with Multi-Reward Distillation](https://md.research.elamur.ai/free/en/papers/ramnath-2023-tailoring-self-rationalizers-multi-reward/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Sahana Ramnath, Brihi Joshi, Skyler Hallinan, et al.*2023 · 14 citations*
23. **[Can LLMs Automate Fact-Checking Article Writing?](https://md.research.elamur.ai/free/en/papers/sahnan-2026-can-llms-automate-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dhruv Sahnan, David Corney, Irene Larraz, et al.*2026 · 5 citations*
24. **[Exploiting Dialogue Acts and Context to Identify Argumentative Relations in Online Debates](https://md.research.elamur.ai/free/en/papers/mezza-2024-exploiting-dialogue-acts-context-identify/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Stefano Mezza, Wayne Wobcke, Alan Blair*2024 · 4 citations*
25. **[Explaining Sources of Uncertainty in Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/sun-2026-explaining-sources-uncertainty-automated-fact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Sun, Greta Warren, Irina Shklovski, et al.*2026 · 3 citations*
26. **[KG-CRAFT: Knowledge Graph-based Contrastive Reasoning with LLMs for Enhancing Automated Fact-checking](https://md.research.elamur.ai/free/en/papers/lourenco-2026-kg-craft-knowledge-graph-based/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Vítor Lourenço, Aline Paes, Tillman Weyde, et al.*2026 · 2 citations*
27. **[NSF-SciFy: Mining the NSF Awards Database for Scientific Claims](https://md.research.elamur.ai/free/en/papers/rao-2026-nsf-scify-mining-nsf-awards/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Delip Rao, Weiqiu You, Eric Wong, et al.*2026 · 2 citations*
28. **[Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/schreieder-2026-attribution-citation-quotation-survey-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tobias Schreieder, Tim Schopf, Michael Färber*2026 · 1 citation*
29. **[Constructing a Japanese Claim Decomposition Dataset for Fact-Checking of LLM-Generated Texts](https://md.research.elamur.ai/free/en/papers/masano-2026-constructing-japanese-claim-decomposition-dataset/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Miwa Masano, Ribeka Keyaki, Atsushi Keyaki, et al.*2026 · 1 citation*
30. **[MEVER: Multi-Modal and Explainable Claim Verification with Graph-based Evidence Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2026-mever-multi-modal-explainable-claim/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Delvin Ce Zhang, Suhan Cui, Zhelin Chu, et al.*2026 · 1 citation*
31. [**ARAFA: An LLM-Generated Arabic Fact-Checking Dataset arXiv:2609.25833**Christophe Khalil, Shady Elbassuoni, Rida Assaf*2026*](https://md.research.elamur.ai/free/en/papers/khalil-2026-arafa-llm-generated-arabic-fact/)
32. **[Constructing a Japanese Verdict Prediction Dataset for Fact-Checking of LLM-Generated Texts](https://md.research.elamur.ai/free/en/papers/masano-2026-constructing-japanese-verdict-prediction-dataset/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miwa Masano, Hirokazu Kiyomaru, Atsushi Keyaki, et al.*2026*
33. **[Deconstruct, Diagnose, and Deliberate: A Protocol-Adaptive Role-Specific Multi-Agent Framework for Fake News Detection](https://md.research.elamur.ai/free/en/papers/zhang-2026-deconstruct-diagnose-deliberate-protocol-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhigan Zhang, Jie Sui*2026*
34. **[Pushing the Frontiers of Scientific Fact-Checking: The SCINLP Dataset](https://md.research.elamur.ai/free/en/papers/maab-2026-pushing-frontiers-scientific-fact-checking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Iffat Maab, Junichi Yamagishi*2026*
35. **[Tailoring Rumor Debunking to You: Diversifying Chinese Rumor-Debunking Passages with an LLM-Driven Simulated Feedback-Enhanced Framework](https://md.research.elamur.ai/free/en/papers/pang-2026-tailoring-rumor-debunking-you-diversifying/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Xinle Pang, Danding Wang, Qiang Sheng, et al.*2026*
36. [**DeformAr: Rethinking NER Evaluation through Component Analysis and Visual Analytics arXiv:2512.00938**Ahmed Mustafa Younes*2025*](https://md.research.elamur.ai/free/en/papers/younes-2025-deformar-rethinking-ner-evaluation-through/)

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

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