---
title: "Who cites Fabio Massimo Zanzotto — 243 papers of our library"
description: "243 papers of the Elamur Research library cite the works of Fabio Massimo Zanzotto, found in their bibliographies; the most cited first."
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---
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# Who cites Fabio Massimo Zanzotto

251 citations of their works from 243 papers of our library (of the 141,840 whose bibliographies we read) · 38 with a page here, the most cited first · [← Fabio Massimo Zanzotto](https://md.research.elamur.ai/free/en/authors/fabio-massimo-zanzotto/)

1. [**Distributed Representations of Sentences and Documents arXiv:1405.4053**Quoc V. Le, Tomas Mikolov*2014 · 5,786 citations*](https://md.research.elamur.ai/free/en/papers/le-2014-distributed-representations-sentences-documents/)
2. [**Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference**R. Thomas McCoy, Ellie Pavlick, Tal Linzen*2019 · 1,635 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)
3. **[Semantic Compositionality through Recursive Matrix-Vector Spaces](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,571 citations*
4. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,552 citations*
5. [**A Convolutional Neural Network for Modelling Sentences arXiv:1404.2188**Nal Kalchbrenner, Edward Grefenstette, Phil Blunsom*2014 · 851 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2014-convolutional-neural-network-modelling-sentences/)
6. **[Semantic Parsing via Paraphrasing](https://md.research.elamur.ai/free/en/papers/berant-2014-semantic-parsing-paraphrasing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonathan Berant, Percy Liang*2014 · 682 citations*
7. [**Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences**Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, et al.*2018 · 671 citations*](https://md.research.elamur.ai/free/en/papers/khashabi-2018-looking-beyond-surface-challenge-set/)
8. [**Breaking NLI Systems with Sentences that Require Simple Lexical Inferences**Max Glockner, Vered Shwartz, Yoav Goldberg*2018 · 517 citations*](https://md.research.elamur.ai/free/en/papers/glockner-2018-breaking-nli-systems-sentences-that/)
9. **[Learning Natural Language Inference with LSTM](https://md.research.elamur.ai/free/en/papers/wang-2016-learning-natural-language-inference-lstm/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shuohang Wang, Jing Jiang*2016 · 495 citations*
10. **[From Paraphrase Database to Compositional Paraphrase Model and Back](https://md.research.elamur.ai/free/en/papers/wieting-2015-paraphrase-database-compositional-paraphrase-model/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2015 · 377 citations*
11. **[Transformers as Soft Reasoners over Language](https://md.research.elamur.ai/free/en/papers/clark-2020-transformers-soft-reasoners-over-language/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Peter Clark, Oyvind Tafjord, Kyle Richardson*2020 · 376 citations*
12. **[ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers](https://md.research.elamur.ai/free/en/papers/yao-2022-zeroquant-efficient-affordable-post-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.*2022 · 302 citations*
13. **[Reasoning Over Semantic-Level Graph for Fact Checking](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*
14. **[Explaining Answers with Entailment Trees](https://md.research.elamur.ai/free/en/papers/dalvi-2021-explaining-answers-entailment-trees/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, et al.*2021 · 207 citations*
15. **[Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation](https://md.research.elamur.ai/free/en/papers/poliak-2018-collecting-diverse-natural-language-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adam Poliak, Aparajita Haldar, Rachel Rudinger, et al.*2018 · 190 citations*
16. [**Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition**Paloma Jeretic, Alex Warstadt, Suvrat Bhooshan, et al.*2020 · 161 citations*](https://md.research.elamur.ai/free/en/papers/jeretic-2020-are-natural-language-inference-models/)
17. **[Specialising Word Vectors for Lexical Entailment](https://md.research.elamur.ai/free/en/papers/vulic-2018-specialising-word-vectors-lexical-entailment/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ivan Vulić, Nikola Mrkšić*2018 · 160 citations*
18. **[HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment](https://md.research.elamur.ai/free/en/papers/vulic-2017-hyperlex-large-scale-evaluation-graded/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ivan Vulić, Daniela Gerz, Douwe Kiela, et al.*2017 · 148 citations*
19. **[From Arguments to Key Points: Towards Automatic Argument Summarization](https://md.research.elamur.ai/free/en/papers/haim-2020-arguments-key-points-automatic-argument/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roy Bar-Haim, Lilach Eden, Roni Friedman, et al.*2020 · 144 citations*
20. **[Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition](https://md.research.elamur.ai/free/en/papers/shwartz-2019-still-pain-neck-evaluating-text/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vered Shwartz, Ido Dagan*2019 · 130 citations*
21. **[TwoWingOS: A Two-Wing Optimization Strategy for Evidential Claim Verification](https://md.research.elamur.ai/free/en/papers/yin-2018-twowingos-two-wing-optimization-strategy/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenpeng Yin, Dan Roth*2018 · 114 citations*
22. [**Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework**Aaron Steven White, Pushpendre Rastogi, Kevin Duh, et al.*2017 · 110 citations*](https://md.research.elamur.ai/free/en/papers/white-2017-inference-is-everything-recasting-semantic/)
23. **[PRover: Proof Generation for Interpretable Reasoning over Rules](https://md.research.elamur.ai/free/en/papers/saha-2020-prover-proof-generation-interpretable-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swarnadeep Saha, Sayan Ghosh, Shashank Srivastava, et al.*2020 · 101 citations*
24. **[LAMBADA: Backward Chaining for Automated Reasoning in Natural Language](https://md.research.elamur.ai/free/en/papers/kazemi-2023-lambada-backward-chaining-automated-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.*2023 · 89 citations*
25. **[Semeval-2022 Task 1: CODWOE – Comparing Dictionaries and Word Embeddings](https://md.research.elamur.ai/free/en/papers/mickus-2022-codwoe-dictionaries-embeddings/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Timothee Mickus, Kees Van Deemter, Mathieu Constant, et al.*2022 · 59 citations*
26. **[On-demand Injection of Lexical Knowledge for Recognising Textual Entailment](https://md.research.elamur.ai/free/en/papers/gomez-2017-demand-injection-lexical-knowledge-recognising/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Pascual Martínez-Gómez, Koji Mineshima, Yusuke Miyao, et al.*2017 · 52 citations*
27. **[An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-empirical-study-model-agnostic-debiasing/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Tianyu Liu, Xin Zheng, Xiaoan Ding, et al.*2020 · 36 citations*
28. [**SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference**Martin Schmitt, Hinrich Schütze*2019 · 28 citations*](https://md.research.elamur.ai/free/en/papers/schmitt-2019-sherliic-typed-event-focused-lexical/)
29. **[Exploring Transitivity in Neural NLI Models through Veridicality](https://md.research.elamur.ai/free/en/papers/yanaka-2021-exploring-transitivity-neural-nli-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hitomi Yanaka, Koji Mineshima, Kentaro Inui*2021 · 27 citations*
30. **[HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/liu-2020-hyponli-exploring-artificial-patterns-hypothesis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tianyu Liu, Xin Zheng, Baobao Chang, et al.*2020 · 27 citations*
31. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/)
32. **[Multi-Level Alignments As An Extensible Representation Basis for Textual Entailment Algorithms](https://md.research.elamur.ai/free/en/papers/noh-2015-multi-level-alignments-as-extensible/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Tae-Gil Noh, Sebastian Padó, Vered Shwartz, et al.*2015 · 17 citations*
33. [**The First Shared Task on Discourse Representation Structure Parsing**Lasha Abzianidze, Rik van Noord, Hessel Haagsma, et al.*2019 · 16 citations*](https://md.research.elamur.ai/free/en/papers/abzianidze-2019-first-shared-task-discourse-representation/)
34. **[Towards the Necessity for Debiasing Natural Language Inference Datasets](https://md.research.elamur.ai/free/en/papers/panenghat-2020-necessity-debiasing-natural-language-inference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mithun Paul Panenghat, Sandeep Suntwal, Faiz Rafique, et al.*2020 · 13 citations*
35. [**SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives**Rashid Nizamani, Sebastian Schuster, Vera Demberg*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/nizamani-2024-siga-naturalistic-nli-dataset-english/)
36. **[Corpora for Learning the Mutual Relationship between Semantic Relatedness and Textual Entailment](https://md.research.elamur.ai/free/en/papers/vo-2016-corpora-learning-mutual-relationship-between/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ngoc Phuoc An Vo, Octavian Popescu*2016 · 3 citations*
37. **[Semi-Automatic Construction of a Textual Entailment Dataset: Selecting Candidates with Vector Space Models](https://md.research.elamur.ai/free/en/papers/fonseca-2015-semi-automatic-construction-textual-entailment/) [Brazilian Symposium in Information and Human Language Technology](https://md.research.elamur.ai/free/en/venues/stil/)**Erick R. Fonseca, Sandra Maria Aluísio*2015 · 1 citation*
38. [**E-CONAN (Entailment, CONtradition And Neutral) Diagnostics Dataset Investigating Linguistic Phenomena in Arabic Natural Language Understanding arXiv:2609.33530**Khloud AL Jallad, Nada Ghneim, Ghaida Rebdawi*2026*](https://md.research.elamur.ai/free/en/papers/jallad-2026-e-conan-entailment-contradition-neutral/)

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

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