---
title: "Who cites Wei Peng"
description: "92 papers of the Elamur Research library cite the works of Wei Peng, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/wei-peng/cited-by/"
---
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# Who cites Wei Peng

92 citations of their works from 92 papers of our library (of the 140,884 whose bibliographies we read) · 13 with a page here, the most cited first · [← Wei Peng](https://md.research.elamur.ai/free/en/authors/wei-peng/)

1. [**Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data**Emily M. Bender, Alexander Koller*2020 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/bender-2020-climbing-nlu-meaning-form-understanding/)
2. [**oLMpics — On what Language Model Pre-training Captures**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 432 citations*](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/)
3. [**Negated and Misprimed Probes for Pretrained Language Models: Birds Can Talk, But Cannot Fly**Nora Kassner, Hinrich Schütze*2020 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2020-negated-misprimed-probes-pretrained-language/)
4. [**Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little**Koustuv Sinha, Robin Jia, Dieuwke Hupkes, et al.*2021 · 292 citations*](https://md.research.elamur.ai/free/en/papers/sinha-2021-masked-language-modeling-distributional-hypothesis/)
5. [**Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 279 citations*](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/)
6. [**How Context Affects Language Models' Factual Predictions**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/)
7. [**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/)
8. [**Probing Natural Language Inference Models through Semantic Fragments**Kyle Richardson, Hai Hu, Lawrence S. Moss, et al.*2019 · 102 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/)
9. [**Harnessing the linguistic signal to predict scalar inferences**Sebastian Schuster, Yuxing Chen, Judith Degen*2020 · 54 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/)
10. [**BLiMP: The Benchmark of Linguistic Minimal Pairs for English**Alex Warstadt, Alicia Parrish, Haokun Liu, et al.*2020 · 19 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2020-blimp-benchmark-linguistic-minimal-pairs/)
11. [**Modelling the Morphology of Verbal Paradigms: A Case Study in the Tokenization of Turkish and Hebrew**Giuseppe Samo, Paola Merlo*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/samo-2026-modelling-morphology-verbal-paradigms-case/)
12. [**Datasets for Verb Alternations across Languages: BLM Templates and Data Augmentation Strategies**Giuseppe Samo, Paola Merlo*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/samo-2026-datasets-verb-alternations-across-languages/)
13. [**Open-access Dataset on Acceptability Ratings of Korean Clausal Constructions by Humans and GPT Models**Gyu-Ho Shin, Soo-Hwan Lee, Chanyoung Lee*2026*](https://md.research.elamur.ai/free/en/papers/shin-2026-open-access-dataset-acceptability-ratings/)

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

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