---
title: "Who cites Information-Theoretic Probing with Minimum…"
description: "169 papers of the Elamur Research library cite «Information-Theoretic Probing with Minimum Description Length», found in their bibliographies; the most…"
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---
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# Who cites «Information-Theoretic Probing with Minimum Description Length»

169 papers of our library cite it (of the 140,884 whose bibliographies we read) · 11 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/voita-2020-information-theoretic-probing-minimum-description/)

1. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,879 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/)
2. [**Probing Classifiers: Promises, Shortcomings, and Advances**Yonatan Belinkov*2022 · 513 citations*](https://md.research.elamur.ai/free/en/papers/belinkov-2022-probing-classifiers-promises-shortcomings-advances/)
3. [**Factual Probing Is MASK: Learning vs. Learning to Recall**Zexuan Zhong, Dan Friedman, Danqi Chen*2021 · 411 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2021-factual-probing-is-mask-learning/)
4. [**True Few-Shot Learning with Language Models**Ethan Perez, Douwe Kiela, Kyunghyun Cho*2021 · 403 citations*](https://md.research.elamur.ai/free/en/papers/perez-2021-true-few-shot-learning-language/)
5. [**Probing Pretrained Language Models for Lexical Semantics**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/)
6. [**Information-Theoretic Probing for Linguistic Structure**Tiago Pimentel, Josef Valvoda, Rowan Hall Maudslay, et al.*2020 · 293 citations*](https://md.research.elamur.ai/free/en/papers/pimentel-2020-information-theoretic-probing-linguistic-structure/)
7. [**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/)
8. [**What Happens To BERT Embeddings During Fine-tuning?**Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.*2020 · 219 citations*](https://md.research.elamur.ai/free/en/papers/merchant-2020-what-happens-bert-embeddings-during/)
9. [**What Artificial Neural Networks Can Tell Us About Human Language Acquisition**Alex Warstadt, Samuel R. Bowman*2022 · 72 citations*](https://md.research.elamur.ai/free/en/papers/warstadt-2022-artificial-neural-networks-tell-us/)
10. [**When Alignment Hurts: Decoupling Representational Spaces in Multilingual Models**Ahmed Elshabrawy, Hour Kaing, Haiyue Song, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elshabrawy-2025-alignment-hurts-decoupling-representational-spaces/)
11. [**Compositional Meaning Representations in LLMs: a Critical Review of Probing Studies**Rémy Marro*2026*](https://md.research.elamur.ai/free/en/papers/marro-2026-compositional-meaning-representations-llms-critical/)

158 more papers of our library cite it; they have no page here yet.

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