---
title: "Who cites Ryan Aponte — 35 papers of our library"
description: "35 papers of the Elamur Research library cite the works of Ryan Aponte, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/ryan-aponte/cited-by/"
---
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# Who cites Ryan Aponte

35 citations of their works from 35 papers of our library (of the 149,439 whose bibliographies we read) · 9 with a page here, the most cited first · [← Ryan Aponte](https://md.research.elamur.ai/free/en/authors/ryan-aponte/)

1. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
2. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
3. **[Reassessing Active Learning Adoption in Contemporary NLP: A Community Survey](https://md.research.elamur.ai/free/en/papers/romberg-2026-reassessing-active-learning-adoption-contemporary/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Julia Romberg, Christopher Schröder, Julius Gonsior, et al.*2026 · 1 citation*
4. **[VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-vocabtailor-dynamic-vocabulary-selection-downstream/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanling Zhang, Yayu Zhou, Tongcheng Fang, et al.*2026 · 1 citation*
5. **[Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasing](https://md.research.elamur.ai/free/en/papers/trhlik-2026-bias-dynamics-babylms-compute-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Filip Trhlík, Andrew Caines, Paula Buttery*2026*
6. **[Counterspeech Generation using Small Language Models](https://md.research.elamur.ai/free/en/papers/muhammad-2026-counterspeech-generation-small-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abubakar Sadiq Muhammad, Simona Frenda, Gavin Abercrombie*2026*
7. **[GALA: Geometric Data Selection with Strategic Prospecting for Large Language Model Self-training](https://md.research.elamur.ai/free/en/papers/xie-2026-gala-geometric-data-selection-strategic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongwei Xie, Ruihao Liao, Zimo Wang, et al.*2026*
8. **[Perplexity-Aware Data Scaling Law: Perplexity Landscapes Predict Performance for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/liu-2026-perplexity-aware-data-scaling-law/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Liu, Hao Zhu, Xiaoyan Yang, et al.*2026*
9. **[Specialization without Sparsity: Efficient and Expressive Split-Path Experts for LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-specialization-without-sparsity-efficient-expressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ganghao Liu, Qin Zhou, Zhe Wang, et al.*2026*

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

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