---
title: "Who cites Yingyu Liang"
description: "153 papers of the Elamur Research library cite the works of Yingyu Liang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yingyu-liang/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yingyu-liang/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Yingyu Liang](https://md.research.elamur.ai/free/en/authors/yingyu-liang/) / cited by

# Who cites Yingyu Liang

160 citations of their works from 153 papers of our library (of the 140,884 whose bibliographies we read) · 12 with a page here, the most cited first · [← Yingyu Liang](https://md.research.elamur.ai/free/en/authors/yingyu-liang/)

1. [**On the Opportunities and Risks of Foundation Models**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,044 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
2. [**Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features**Matteo Pagliardini, Prakhar Gupta, Martin Jaggi*2018 · 840 citations*](https://md.research.elamur.ai/free/en/papers/pagliardini-2018-unsupervised-learning-sentence-embeddings-compositional/)
3. [**Learning Gender-Neutral Word Embeddings**Jieyu Zhao, Yichao Zhou, Zeyu Li, et al.*2018 · 512 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2018-learning-gender-neutral-word-embeddings/)
4. [**A Latent Variable Model Approach to PMI-based Word Embeddings**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2016 · 365 citations*](https://md.research.elamur.ai/free/en/papers/arora-2016-latent-variable-model-approach-pmi/)
5. [**Linear Algebraic Structure of Word Senses, with Applications to Polysemy**Sanjeev Arora, Yuanzhi Li, Yingyu Liang, et al.*2018 · 247 citations*](https://md.research.elamur.ai/free/en/papers/arora-2018-linear-algebraic-structure-word-senses/)
6. [**LESS: Selecting Influential Data for Targeted Instruction Tuning**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
7. [**The Linear Representation Hypothesis and the Geometry of Large Language Models**Kiho Park, Yo Joong Choe, Victor Veitch*2023 · 157 citations*](https://md.research.elamur.ai/free/en/papers/park-2023-linear-representation-hypothesis-geometry-large/)
8. [**Improving Event Coreference Resolution by Modeling Correlations between Event Coreference Chains and Document Topic Structures**Prafulla Kumar Choubey, Ruihong Huang*2018 · 43 citations*](https://md.research.elamur.ai/free/en/papers/choubey-2018-improving-event-coreference-resolution-modeling/)
9. [**Ontology-Aware Token Embeddings for Prepositional Phrase Attachment**Pradeep Dasigi, Waleed Ammar, Chris Dyer, et al.*2017 · 35 citations*](https://md.research.elamur.ai/free/en/papers/dasigi-2017-ontology-aware-token-embeddings-prepositional/)
10. [**Current Trends and Approaches in Synonyms Extraction: Potential Adaptation to Arabic**Eman Naser-Karajah, Nabil Arman, Mustafa Jarrar*2021 · 14 citations*](https://md.research.elamur.ai/free/en/papers/naser-karajah-2022-current-trends-approaches-synonyms-extraction/)
11. [**Word-Embeddings Distinguish Denominal and Root-Derived Verbs in Semitic**Ido Benbaji, Omri Doron, Adele Henot-Mortier*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/benbaji-2022-word-embeddings-distinguish-denominal-root/)
12. [**“Oat Milk Vegan Chocolate Taste Great!”: Monitoring the Food Transition Debate in Reddit**Greta Zella, Jan Willem Bolderdijk, Saskia Peels, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zella-2026-oat-milk-vegan-chocolate-taste/)

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

- [← back to](https://md.research.elamur.ai/free/en/authors/yingyu-liang/) — Yingyu Liang