--- title: "Who cites Lawrence S. Moss — 172 papers of our library" description: "172 papers of the Elamur Research library cite the works of Lawrence S. Moss, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/lawrence-s-moss/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/lawrence-s-moss/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Lawrence S. Moss](https://md.research.elamur.ai/free/en/authors/lawrence-s-moss/) / cited by # Who cites Lawrence S. Moss 186 citations of their works from 172 papers of our library (of the 141,840 whose bibliographies we read) · 33 with a page here, the most cited first · [← Lawrence S. Moss](https://md.research.elamur.ai/free/en/authors/lawrence-s-moss/) 1. [**Qwen Technical Report arXiv:2309.16609**Jinze Bai, Shuai Bai, Yunfei Chu, et al.*2023 · 1,645 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-technical-report/) **[Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) [IEEE/ACM Transactions on Audio Speech and Language Processing](https://md.research.elamur.ai/free/en/venues/ieee-acm-transactions-on-audio-speech-and-language-processing/)**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,490 citations* **[PPT: Pre-trained Prompt Tuning for Few-shot Learning](https://md.research.elamur.ai/free/en/papers/gu-2022-ppt-pre-trained-prompt-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxian Gu, Xu Han, Zhiyuan Liu, et al.*2022 · 469 citations* **[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* **[Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations* [**CLUE: A Chinese Language Understanding Evaluation Benchmark arXiv:2004.05986**Liang Xu, Hai Hu, Xuanwei Zhang, et al.*2020 · 243 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-clue-chinese-language-understanding/) [**How Context Affects Language Models' Factual Predictions arXiv:2005.04611**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 231 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/) [**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/) **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 149 citations* [**OCNLI: Original Chinese Natural Language Inference arXiv:2010.05444**Hai Hu, Kyle Richardson, Liang Xu, et al.*2020 · 147 citations*](https://md.research.elamur.ai/free/en/papers/hu-2020-ocnli-original-chinese-natural/) **[UnNatural Language Inference](https://md.research.elamur.ai/free/en/papers/sinha-2021-unnatural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.*2021 · 132 citations* [**Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation**Atticus Geiger, Kyle Richardson, Christopher Potts*2020 · 112 citations*](https://md.research.elamur.ai/free/en/papers/geiger-2020-neural-natural-language-inference-models/) **[Probing Natural Language Inference Models through Semantic Fragments](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Kyle Richardson, Hai Hu, Lawrence S. Moss, et al.*2019 · 102 citations* **[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* **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 85 citations* **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations* **[Are Pretrained Language Models Symbolic Reasoners over Knowledge?](https://md.research.elamur.ai/free/en/papers/kassner-2020-are-pretrained-language-models-symbolic/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nora Kassner, Benno Krojer, Hinrich Schütze*2020 · 79 citations* **[Figurative Language in Recognizing Textual Entailment](https://md.research.elamur.ai/free/en/papers/chakrabarty-2021-figurative-language-recognizing-textual-entailment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tuhin Chakrabarty, Debanjan Ghosh, Adam Poliak, et al.*2021 · 63 citations* **[Culturally Aware Natural Language Inference](https://md.research.elamur.ai/free/en/papers/huang-2023-culturally-aware-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Huang, Diyi Yang*2023 · 61 citations* **[ConjNLI: Natural Language Inference Over Conjunctive Sentences](https://md.research.elamur.ai/free/en/papers/saha-2020-conjnli-natural-language-inference-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Swarnadeep Saha, Yixin Nie, Mohit Bansal*2020 · 50 citations* **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations* **[CxGBERT: BERT meets Construction Grammar](https://md.research.elamur.ai/free/en/papers/madabushi-2020-cxgbert-bert-meets-construction-grammar/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Harish Tayyar Madabushi, Laurence Romain, Dagmar Divjak, et al.*2020 · 46 citations* **[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* [**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/) **[When Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs)](https://md.research.elamur.ai/free/en/papers/gubelmann-2023-when-truth-matters-addressing-pragmatic/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Reto Gubelmann, Aikaterini-lida Kalouli, Christina Niklaus, et al.*2023 · 15 citations* [**ArNLI: Arabic Natural Language Inference for Entailment and Contradiction Detection arXiv:2209.13953 · (2023) Computer Science, 24(2)**Khloud Al Jallad, Nada Ghneim*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/jallad-2022-arnli-arabic-natural-language-inference/) **[Decomposing Natural Logic Inferences for Neural NLI](https://md.research.elamur.ai/free/en/papers/rozanova-2022-decomposing-natural-logic-inferences-neural/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.*2022 · 8 citations* **[Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences](https://md.research.elamur.ai/free/en/papers/luo-2022-simple-but-challenging-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Luo, Wei Liu, Jieyu Lin, et al.*2022 · 7 citations* **[Annotation Difficulties in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/kalouli-2021-annotation-difficulties-natural-language-inference/) [Brazilian Symposium in Information and Human Language Technology](https://md.research.elamur.ai/free/en/venues/stil/)**Aikaterini-Lida Kalouli, Livy Real, Annebeth Buis, et al.*2021 · 5 citations* **[Supporting Context Monotonicity Abstractions in Neural NLI Models](https://md.research.elamur.ai/free/en/papers/rozanova-2021-supporting-context-monotonicity-abstractions-neural/) [Workshops on Natural Logic Meets Machine Learning (NALOMA)](https://md.research.elamur.ai/free/en/venues/naloma/)**Julia Rozanova, Deborah Ferreira, Mokanarangan Thayaparan, et al.*2021 · 5 citations* [**Probing the Natural Language Inference Task with Automated Reasoning Tools arXiv:2005.02573**Zaid Marji, Animesh Nighojkar, John Licato*2020 · 3 citations*](https://md.research.elamur.ai/free/en/papers/marji-2020-probing-natural-language-inference-task/) [**Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns arXiv:2201.07614**Reto Gubelmann, Siegfried Handschuh*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gubelmann-2022-uncovering-more-shallow-heuristics-probing/) **[Large Language Models Put to the Test on Chinese Noun Compounds: Experiments on Natural Language Inference and Compound Semantics](https://md.research.elamur.ai/free/en/papers/qiu-2026-large-language-models-put-test/) [Workshop on Multiword Expressions (MWE)](https://md.research.elamur.ai/free/en/venues/mwe/)**Le Qiu, Emmanuele Chersoni, He Zhou, et al.*2026* 139 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/lawrence-s-moss/) — Lawrence S. Moss