---
title: "Who cites Infini-gram: Scaling Unbounded — 61 citing papers"
description: "61 papers of the Elamur Research library cite «Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens», found in their…"
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---
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# Who cites «Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens»

61 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens»](https://md.research.elamur.ai/free/en/papers/liu-2024-infini-gram-scaling-unbounded-n/)

1. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
2. **[Constructions are Revealed in Word Distributions](https://md.research.elamur.ai/free/en/papers/rozner-2025-constructions-are-revealed-word-distributions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Rozner, Leonie Weissweiler, Kyle Mahowald, et al.*2025 · 9 citations*
3. **[Rethinking Creativity Evaluation: A Critical Analysis of Existing Creativity Evaluations](https://md.research.elamur.ai/free/en/papers/lu-2026-rethinking-creativity-evaluation-critical-analysis/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Li-Chun Lu, Miri Liu, Pin Chun Lu, et al.*2026 · 3 citations*
4. **[QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/min-2026-quco-rag-quantifying-uncertainty-pre/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dehai Min, Kailin Zhang, Tongtong Wu, et al.*2026 · 2 citations*
5. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*
6. **[Investigating Memorization in Language Models Trained via Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/macking-2026-investigating-memorization-language-models-trained/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maarten Mäcking, Michaela Regneri*2026*
7. **[Lexical Popularity: Quantifying the Impact of Pre-training for LLM Performance](https://md.research.elamur.ai/free/en/papers/ruzzetti-2026-lexical-popularity-quantifying-impact-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Elena Sofia Ruzzetti, Fabio Massimo Zanzotto, Tommaso Caselli*2026*
8. **[Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning](https://md.research.elamur.ai/free/en/papers/mi-2026-rethinking-idiomaticity-decomposability-hypothesis-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maggie Mi, Golzar Atefi, Atsuki Yamaguchi, et al.*2026*

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

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