---
title: "Who cites Adam: A Method — page 12 — 10,909 citing papers"
description: "10,909 papers of the Elamur Research library cite «Adam: A Method for Stochastic Optimization», found in their bibliographies · page 12 of…"
canonical: "https://research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/12/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/12/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Adam: A Method for Stochastic Optimization](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/) / [cited by](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) / page 12

# Who cites «Adam: A Method for Stochastic Optimization»

10,909 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1123 with a page here, the most cited first · page 12 of 12 · 1101–1123 · [← back to «Adam: A Method for Stochastic Optimization»](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)

[← prev](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) [1](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) … [10](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) **12**

1101. **[Small Neural Networks as Models of Cross-Linguistic Speech Perception](https://md.research.elamur.ai/free/en/papers/shankwitz-2026-small-neural-networks-as-models/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Annika Shankwitz*2026*
1102. **[Soft Head Selection for Injecting ICL-Derived Task Embeddings](https://md.research.elamur.ai/free/en/papers/park-2026-soft-head-selection-injecting-icl/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungwon Park, Jimyeong Kim, Changin Choi, et al.*2026*
1103. **[Task Assignment meets Annotator Modeling: Human-LLM Collaborative Annotation with Constraints](https://md.research.elamur.ai/free/en/papers/moriyama-2026-task-assignment-meets-annotator-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kei Moriyama, Kouta Nakayama, Yukino Baba*2026*
1104. **[The Development of Spectral and Temporal Encodings in Speech Sounds](https://md.research.elamur.ai/free/en/papers/tan-2026-development-spectral-temporal-encodings-speech/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Frank Lihui Tan, Youngah Do*2026*
1105. **[ThinkStruct: RST-Aware Attention for Logical Reasoning in Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/tran-2026-thinkstruct-rst-aware-attention-logical/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nhi Thao Tran, Tien Le, Toan Pham, et al.*2026*
1106. **[Tracing Mathematical Proficiency Through Problem-Solving Processes](https://md.research.elamur.ai/free/en/papers/park-2026-tracing-mathematical-proficiency-through-problem/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jungyang Park, Suho Kang, Jaewoo Park, et al.*2026*
1107. **[Tracing Relational Knowledge Recall in Large Language Models](https://md.research.elamur.ai/free/en/papers/popovic-2026-tracing-relational-knowledge-recall-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nicholas Popovič, Michael Färber*2026*
1108. **[Understanding Conflicts in Multi-Objective Alignment through Reward Consistency](https://md.research.elamur.ai/free/en/papers/xu-2026-understanding-conflicts-multi-objective-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhihao Xu, Yongqi Tong, Xin Zhang, et al.*2026*
1109. **[Universally Empowering Zeroth-Order Optimization via Adaptive Layer-wise Sampling](https://md.research.elamur.ai/free/en/papers/wang-2026-universally-empowering-zeroth-order-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fei Wang, Li Shen, Liang Ding, et al.*2026*
1110. **[What Do Prosody and Text Convey? Characterizing How Meaningful Information is Distributed Across Multiple Channels](https://md.research.elamur.ai/free/en/papers/yadavalli-2026-what-do-prosody-text-convey/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aditya Yadavalli, Tiago Pimentel, Tamar I Regev, et al.*2026*
1111. **[What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance](https://md.research.elamur.ai/free/en/papers/watson-2026-what-makes-good-query-measuring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Watson, Nicole Cho, Sumitra Ganesh, et al.*2026*
1112. **[Who You Are, What You Say: Intra- and Inter- Context Personality for Emotion Recognition in Conversation](https://md.research.elamur.ai/free/en/papers/rakib-2026-who-you-are-what-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tazeek Bin Abdur Rakib, Lay-Ki Soon, Wern Han Lim*2026*
1113. **[A MISMATCHED Benchmark for Scientific Natural Language Inference](https://md.research.elamur.ai/free/en/papers/shaik-2025-mismatched-benchmark-scientific-natural-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Firoz Shaik, Mobashir Sadat, Nikita Gautam, et al.*2025*
1114. **[Robustness Evaluation of ChatGPT Against Chinese Adversarial Attacks (中文对抗攻击下的ChatGPT鲁棒性评估)](https://md.research.elamur.ai/free/en/papers/zhang-2025-robustness-evaluation-chatgpt/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yunting Zhang (张云婷), Lin Ye (叶麟), Baisong Li (李柏松), et al.*2025*
1115. **[DILAB at #SMM4H 2024: RoBERTa Ensemble for Identifying Children's Medical Disorders in English Tweets](https://md.research.elamur.ai/free/en/papers/wasi-2024-dilab-smm4h-2024-roberta-ensemble/) [Social Media Mining for Health Research and Applications Workshop and Shared Tasks](https://md.research.elamur.ai/free/en/venues/smm4h/)**Azmine Toushik Wasi, Sheikh Rahman*2024*
1116. [**Evaluating the Effectiveness of the Foundational Models for Q&A Classification in Mental Health care arXiv:2406.15966**Hassan Alhuzali, Ashwag Alasmari*2024*](https://md.research.elamur.ai/free/en/papers/alhuzali-2024-evaluating-effectiveness-foundational-models-q/)
1117. [**On the importance of Data Scale in Pretraining Arabic Language Models arXiv:2401.07760**Abbas Ghaddar, Philippe Langlais, Mehdi Rezagholizadeh, et al.*2024*](https://md.research.elamur.ai/free/en/papers/ghaddar-2024-importance-data-scale-pretraining-arabic/)
1118. **[Barch: an English Dataset of Bar Chart Summaries](https://md.research.elamur.ai/free/en/papers/skrjanec-2022-barch-english-dataset-bar-chart/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Iza Škrjanec, Muhammad Salman Edhi, Vera Demberg*2022*
1119. [**BERT-based Multi-Task Model for Country and Province Level Modern Standard Arabic and Dialectal Arabic Identification arXiv:2106.12495**Abdellah El Mekki, Abdelkader El Mahdaouy, Kabil Essefar, et al.*2021*](https://md.research.elamur.ai/free/en/papers/mekki-2021-bert-based-multi-task-model-country/)
1120. [**A Simple Global Neural Discourse Parser arXiv:2009.01312**Yichu Zhou, Omri Koshorek, Vivek Srikumar, et al.*2020*](https://md.research.elamur.ai/free/en/papers/zhou-2020-simple-global-neural-discourse-parser/)
1121. [**Recursive LSTM Tree Representation for Arc-Standard Transition-Based Dependency Parsing**Mohab Elkaref, Bernd Bohnet*2019*](https://md.research.elamur.ai/free/en/papers/elkaref-2019-recursive-lstm-tree-representation-arc/)
1122. **[Algorithmes à base d'échantillonage pour l'entraînement de modèles de langue neuronaux (Here the title in English)](https://md.research.elamur.ai/free/en/papers/labeau-2018-algorithmes-base-d-echantillonage-pour/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Matthieu Labeau, Alexandre Allauzen*2018*
1123. **[ECNU at SemEval-2018 Task 3: Exploration on Irony Detection from Tweets via Machine Learning and Deep Learning Methods](https://md.research.elamur.ai/free/en/papers/yin-2018-ecnu-semeval-2018-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Zhenghang Yin, Feixiang Wang, Man Lan, et al.*2018*

[← prev](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) [1](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) … [10](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) **12**

9,786 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/) — Adam: A Method for Stochastic Optimization