---
title: "Who cites Adhiguna Kuncoro — page 4 — 1,338 citing papers"
description: "1,338 papers of the Elamur Research library cite the works of Adhiguna Kuncoro, found in their bibliographies · page 4 of 4 · 301–353; the…"
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# Who cites Adhiguna Kuncoro

1,544 citations of their works from 1,338 papers of our library (of the 149,439 whose bibliographies we read) · 353 with a page here, the most cited first · page 4 of 4 · 301–353 · [← Adhiguna Kuncoro](https://md.research.elamur.ai/free/en/authors/adhiguna-kuncoro/)

[← prev](https://md.research.elamur.ai/free/en/authors/adhiguna-kuncoro/cited-by/page/3/) [1](https://md.research.elamur.ai/free/en/authors/adhiguna-kuncoro/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/adhiguna-kuncoro/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/authors/adhiguna-kuncoro/cited-by/page/3/) **4**

301. [**Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model arXiv:2404.04167**Xinrun Du; Zhouliang Yu; Songyang Gao; Ding Pan; Yuyang Cheng; Ziyang Ma; Ruibin Yuan; Xingwei Qu; Jiaheng Liu; Tianyu Zheng; Xinchen Luo; Guorui Zhou; Wenhu Chen;, Ge Zhang*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/)
302. [**InstructAlign: High-and-Low Resource Language Alignment via Continual Crosslingual Instruction Tuning arXiv:2305.13627**Samuel Cahyawijaya, Holy Lovenia, Tiezheng Yu, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/cahyawijaya-2023-instructalign-high-low-resource-language/)
303. **[AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-aramus-pushing-limits-data-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaad Alghamdi, Xinyu Duan, Wei Jiang, et al.*2023 · 21 citations*
304. [**DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules**Yanchen Liu, William Held, Diyi Yang*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-dada-dialect-adaptation-dynamic-aggregation/)
305. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
306. [**A Distributional and Orthographic Aggregation Model for English Derivational Morphology**Daniel Deutsch, John Hewitt, Dan Roth*2018 · 19 citations*](https://md.research.elamur.ai/free/en/papers/deutsch-2018-distributional-orthographic-aggregation-model-english/)
307. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
308. **[LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English](https://md.research.elamur.ai/free/en/papers/s-2024-lexsumm-lext5-benchmarking-modeling-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Santosh T.Y.S.S, Cornelius Weiss, Matthias Grabmair*2024 · 16 citations*
309. [**AMALGUM – A Free, Balanced, Multilayer English Web Corpus**Luke Gessler, Siyao Peng, Yang Liu, et al.*2020 · 16 citations*](https://md.research.elamur.ai/free/en/papers/gessler-2020-amalgum-free-balanced-multilayer-english/)
310. [**The First Shared Task on Discourse Representation Structure Parsing**Lasha Abzianidze, Rik van Noord, Hessel Haagsma, et al.*2019 · 16 citations*](https://md.research.elamur.ai/free/en/papers/abzianidze-2019-first-shared-task-discourse-representation/)
311. **[AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters](https://md.research.elamur.ai/free/en/papers/lucy-2024-aboutme-self-descriptions-webpages-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Lucy, Suchin Gururangan, Luca Soldaini, et al.*2024 · 15 citations*
312. [**Constituency Parsing using LLMs arXiv:2310.19462**Xuefeng Bai, Jialong Wu, Yulong Chen, et al.*2023 · 14 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-constituency-parsing-using-llms/)
313. [**Towards Ontology Construction with Language Models arXiv:2309.09898**Maurice Funk, Simon Hosemann, Jean Christoph Jung, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/funk-2023-towards-ontology-construction-language-models/)
314. **[A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021](https://md.research.elamur.ai/free/en/papers/anderson-2021-modest-pareto-optimisation-analysis-dependency/) [International Conference on Parsing Technologies and the IWPT Shared Task on Parsing into Enhanced Universal Dependencies](https://md.research.elamur.ai/free/en/venues/iwpt/)**Mark Anderson, Carlos Gómez-Rodríguez*2021 · 10 citations*
315. [**Improving a Strong Neural Parser with Conjunction-Specific Features**Jessica Ficler, Yoav Goldberg*2017 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ficler-2017-improving-strong-neural-parser-conjunction/)
316. [**TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression arXiv:2506.02678**Zhong-Zhi Li, Xiao Liang, Zihao Tang, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-tl-dr-too-long-re/)
317. [**Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization arXiv:2409.12903**Mohammad Samragh, Iman Mirzadeh, Keivan Alizadeh Vahid, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/samragh-2024-scaling-smart-accelerating-large-language/)
318. [**Integrating Graph-Based and Transition-Based Dependency Parsers in the Deep Contextualized Era**Agnieszka Falenska, Anders Björkelund, Jonas Kuhn*2020 · 8 citations*](https://md.research.elamur.ai/free/en/papers/falenska-2020-integrating-graph-based-transition-based/)
319. [**Head-First Linearization with Tree-Structured Representation**Xiang Yu, Agnieszka Falenska, Ngoc Thang Vu, et al.*2019 · 8 citations*](https://md.research.elamur.ai/free/en/papers/yu-2019-head-first-linearization-tree-structured/)
320. [**Fast and Accurate Non-Projective Dependency Tree Linearization**Xiang Yu, Simon Tannert, Ngoc Thang Vu, et al.*2020 · 7 citations*](https://md.research.elamur.ai/free/en/papers/yu-2020-fast-accurate-non-projective-dependency/)
321. **[How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP](https://md.research.elamur.ai/free/en/papers/tatariya-2026-how-good-is-your-wikipedia/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kushal Tatariya, Artur Kulmizev, Wessel Poelman, et al.*2026 · 6 citations*
322. [**Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic arXiv:2412.04277**Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-arabic-stable-lm-adapting-stable/)
323. [**A Novel Challenge Set for Hebrew Morphological Disambiguation and Diacritics Restoration**Avi Shmidman, Joshua Guedalia, Shaltiel Shmidman, et al.*2020 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2020-novel-challenge-set-hebrew-morphological/)
324. **[VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2026-visaidmath-benchmarking-visual-aided-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingkun Ma, Runzhe Zhan, Yang Li, et al.*2026 · 5 citations*
325. [**WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset arXiv:2402.19282**Jiantao Qiu, Haijun Lv, Zhenjiang Jin, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2024-wanjuan-cc-safe-high-quality/)
326. [**Approximate Dynamic Oracle for Dependency Parsing with Reinforcement Learning**Xiang Yu, Ngoc Thang Vu, Jonas Kuhn*2018 · 5 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-approximate-dynamic-oracle-dependency-parsing/)
327. **[Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generation](https://md.research.elamur.ai/free/en/papers/burns-2026-aleph-alpha-germanweb-improving-german/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.*2026 · 4 citations*
328. [**The German Commons - 154 Billion Tokens of Openly Licensed Text for German Language Models arXiv:2510.13996**Lukas Gienapp, Christopher Schroder, Stefan Schweter, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gienapp-2025-german-commons-154-billion-tokens/)
329. **[Tree Transformer's Disambiguation Ability of Prepositional Phrase Attachment and Garden Path Effects](https://md.research.elamur.ai/free/en/papers/zhou-2024-tree-transformer-s-disambiguation-ability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingling Zhou, Suzan Verberne, Gijs Wijnholds*2024 · 2 citations*
330. [**Uncovering More Shallow Heuristics: Probing the Natural Language Inference Capacities of Transformer-Based Pre-Trained Language Models Using Syllogistic Patterns arXiv:2201.07614**Reto Gubelmann, Siegfried Handschuh*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/gubelmann-2022-uncovering-more-shallow-heuristics-probing/)
331. [**Comparing Neural Network Parsers for a Less-resourced and Morphologically-rich Language: Amharic Dependency Parser**Binyam Ephrem Seyoum, Yusuke Miyao, Baye Yimam Mekonnen*2020 · 2 citations*](https://md.research.elamur.ai/free/en/papers/seyoum-2020-comparing-neural-network-parsers-less/)
332. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
333. **[From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan](https://md.research.elamur.ai/free/en/papers/yang-2026-curated-data-scalable-models-continual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Yang, Leiyu Pan, Bojian Xiong, et al.*2026 · 1 citation*
334. **[ArabicWeb-Edu: Educational Quality Data for Arabic LLM Training](https://md.research.elamur.ai/free/en/papers/hawasly-2025-arabicweb-edu-educational-quality-data/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Majd Hawasly, Tasnim Mohiuddin, Hamdy Mubarak, et al.*2025 · 1 citation*
335. [**Mix, MinHash, and Match: Cross-Source Agreement for Multilingual Pretraining Datasets arXiv:2512.18834**Sultan Alrashed, Francesco Orabona*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alrashed-2025-mix-minhash-match-cross-source/)
336. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
337. **[BRAGD: Constrained Multi-Label POS Tagging for Faroese](https://md.research.elamur.ai/free/en/papers/simonsen-2026-bragd-constrained-multi-label-pos/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Annika Simonsen, Barbara Scalvini, Uni Johannesen, et al.*2026*
338. [**Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks**Claire Hobbs, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/hobbs-2026-collocational-bootstrapping-hypothesis-about-learning/)
339. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)
340. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
341. **[MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification](https://md.research.elamur.ai/free/en/papers/zheng-2026-masktab-scalable-masked-tabular-pretraining/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo Zheng, Yudong Chen, Zihua Xiong, et al.*2026*
342. **[Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*
343. **[MUTANT: A Recipe for Multilingual Tokenizer Design](https://md.research.elamur.ai/free/en/papers/rana-2026-mutant-recipe-multilingual-tokenizer-design/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.*2026*
344. **[MzansiText and MzansiLM: An Open Corpus and Decoder-Only Language Model for South African Languages](https://md.research.elamur.ai/free/en/papers/lombard-2026-mzansitext-mzansilm-open-corpus-decoder/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anri M. Lombard, Simbarashe Mawere, Temi Aina, et al.*2026*
345. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
346. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Tong, Weidong Zhang, Jiaang Li, et al.*2026*
347. **[SemiAdapt: Semi-Supervised and Efficient LoRA-Based Domain Adaptation for Low-Resource Irish Machine Translation with Transformers](https://md.research.elamur.ai/free/en/papers/mcgiff-2026-semiadapt-semi-supervised-efficient-lora/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Josh Mcgiff, Nikola S. Nikolov*2026*
348. [**The Validity of Coreference-based Evaluations of Natural Language Understanding arXiv:2602.16200**Ian Porada*2026*](https://md.research.elamur.ai/free/en/papers/porada-2026-validity-coreference-based-evaluations-natural/)
349. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026*
350. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*
351. [**Wasm: A Pipeline for Constructing Structured Arabic Interleaved Multimodal Corpora arXiv:2511.07080**Khalil Hennara; Ahmad Bastati; Muhammad Hreden; Mohamed Motasim Hamed; Zeina Aldallal; Sara Chrouf;, Safwan AlModhayan*2025*](https://md.research.elamur.ai/free/en/papers/hennara-2025-wasm-pipeline-constructing-structured-arabic/)
352. [**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/)
353. [**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/)

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