---
title: "Who cites Ngai Wong — 130 papers of our library"
description: "130 papers of the Elamur Research library cite the works of Ngai Wong, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/ngai-wong/cited-by/"
---
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# Who cites Ngai Wong

134 citations of their works from 130 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← Ngai Wong](https://md.research.elamur.ai/free/en/authors/ngai-wong/)

1. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
2. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
3. **[Dual-Space Knowledge Distillation for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-dual-space-knowledge-distillation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songming Zhang, Xue Zhang, Zengkui Sun, et al.*2024 · 39 citations*
4. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
5. [**Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance arXiv:2507.22448**Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-falcon-h1-family-hybrid-head/)
6. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
7. **[Find Your Optimal Teacher: Personalized Data Synthesis via Router-Guided Multi-Teacher Distillation](https://md.research.elamur.ai/free/en/papers/zhang-2026-find-your-optimal-teacher-personalized/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengyuan Zhang, Shiping Yang, Xiao Liang, et al.*2026 · 13 citations*
8. **[ToDi: Token-wise Distillation via Fine-Grained Divergence Control](https://md.research.elamur.ai/free/en/papers/jung-2025-todi-token-wise-distillation-fine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Seongryong Jung, Suwan Yoon, DongGeon Kim, et al.*2025 · 12 citations*
9. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
10. [**RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models arXiv:2406.01983**Bichen Wang, Yuzhe Zi, Yixin Sun, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rkld-reverse-kl-divergence-based/)
11. **[Beyond Math: Stories as a Testbed for Memorization-Constrained Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/jiang-2026-beyond-math-stories-as-testbed/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxuan Jiang, Francis Ferraro*2026 · 10 citations*
12. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
13. **[Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal Uncertainty](https://md.research.elamur.ai/free/en/papers/xue-2026-reason-only-when-needed-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 8 citations*
14. **[Beyond Logits: Aligning Feature Dynamics for Effective Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/gong-2025-beyond-logits-aligning-feature-dynamics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guoqiang Gong, Jiaxing Wang, Jin Xu, et al.*2025 · 7 citations*
15. **[Why Supervised Fine-Tuning Fails to Learn: A Systematic Study of Incomplete Learning in Large Language Models](https://md.research.elamur.ai/free/en/papers/xue-2026-why-supervised-fine-tuning-fails/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chao Xue, Yao Wang, Mengqiao Liu, et al.*2026 · 6 citations*
16. **[Enhancing Knowledge Distillation of Large Language Models through Efficient Multi-Modal Distribution Alignment](https://md.research.elamur.ai/free/en/papers/peng-2025-enhancing-knowledge-distillation-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianyu Peng, Jiajun Zhang*2025 · 6 citations*
17. [**LLM-Oriented Token-Adaptive Knowledge Distillation arXiv:2510.11615**Xurong Xie, Zhucun Xue, Jiafu Wu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/xie-2025-llm-oriented-token-adaptive-knowledge/)
18. **[Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs](https://md.research.elamur.ai/free/en/papers/anshumann-2025-sparse-logit-sampling-accelerating-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anshumann, Mohd Abbas Zaidi, Akhil Kedia, et al.*2025 · 6 citations*
19. **[Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework](https://md.research.elamur.ai/free/en/papers/dycke-2026-automatic-reviewers-fail-detect-faulty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nils Dycke, Iryna Gurevych*2026 · 5 citations*
20. **[Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/rao-2026-dynamic-sampling-that-adapts-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jun Rao, Xuebo Liu, Hexuan Deng, et al.*2026 · 4 citations*
21. **[NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment](https://md.research.elamur.ai/free/en/papers/wu-2026-novbench-evaluating-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenqing Wu, Yi Zhao, Yuzhuo Wang, et al.*2026 · 4 citations*
22. [**Kuwain 1.5B: An Arabic SLM via Language Injection arXiv:2504.15120**Khalil Hennara, Sara Chrouf, Mohamed Motaism Hamed, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-kuwain-1-5b-arabic-slm/)
23. [**Less is More: Selective Reflection for Compatible and Efficient Knowledge Distillation in Large Language Models arXiv:2508.06135**Lingyuan Liu, Mengxiang Zhang*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-less-more-selective-reflection-compatible/)
24. **[Tokenisation is NP-Complete](https://md.research.elamur.ai/free/en/papers/whittington-2025-tokenisation-is-np-complete/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Philip Whittington, Gregor Bachmann, Tiago Pimentel*2025 · 4 citations*
25. **[Behavior Knowledge Merge in Reinforced Agentic Models](https://md.research.elamur.ai/free/en/papers/yuan-2026-behavior-knowledge-merge-reinforced-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchi Yuan, Dachuan Shi, Chunhui Zhang, et al.*2026 · 3 citations*
26. **[FLEXITOKENS: Flexible Tokenization for Evolving Language Models](https://md.research.elamur.ai/free/en/papers/owodunni-2026-flexitokens-flexible-tokenization-evolving-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abraham Toluwase Owodunni, Orevaoghene Ahia, Sachin Kumar*2026 · 3 citations*
27. **[MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis](https://md.research.elamur.ai/free/en/papers/yu-2026-mathagent-adversarial-evolution-constraint-graphs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixiong Yu, Jun Rao, Guhan Chen, et al.*2026 · 3 citations*
28. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
29. **[Speculative Decoding with a Speculative Vocabulary](https://md.research.elamur.ai/free/en/papers/williams-2026-speculative-decoding-speculative-vocabulary/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Miles Williams, Young D. Kwon, Rui Li, et al.*2026 · 2 citations*
30. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
31. **[From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization](https://md.research.elamur.ai/free/en/papers/zhou-2026-signal-degradation-computation-collapse-uncovering/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenxi Zhou, Pengfei Cao, Jiang Li, et al.*2026 · 1 citation*
32. **[Resource-Limited Joint Multimodal Sentiment Reasoning and Classification via Chain-of-Thought Enhancement and Distillation](https://md.research.elamur.ai/free/en/papers/shangguan-2026-resource-limited-joint-multimodal-sentiment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haonan Shangguan, Xiaocui Yang, Shi Feng, et al.*2026 · 1 citation*
33. **[SupraTok: Cross-Boundary Tokenization for Enhanced Language Model Performance](https://md.research.elamur.ai/free/en/papers/tanase-2026-supratok-cross-boundary-tokenization-enhanced/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Andrei-Valentin Tănase, Elena Pelican*2026 · 1 citation*
34. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
35. **[Why Steering Works: Toward a Unified View of Language Model Parameter Dynamics](https://md.research.elamur.ai/free/en/papers/xu-2026-why-steering-works-unified-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Chenyan WU, Hengyu Sun, et al.*2026 · 1 citation*
36. **[From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation](https://md.research.elamur.ai/free/en/papers/zheng-2026-isolated-scoring-collaborative-ranking-comparison/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.*2026*
37. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Kewei Xu, Haoming Xu, et al.*2026*
38. **[Investigating Gender Stereotypes in Large Language Models via Social Determinants of Health](https://md.research.elamur.ai/free/en/papers/ngo-2026-investigating-gender-stereotypes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Trung Hieu Ngo, Adrien Bazoge, Solen Quiniou, et al.*2026*
39. **[Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data](https://md.research.elamur.ai/free/en/papers/yang-2026-quantifying-improving-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shiping Yang, Jie Wu, Wenbiao Ding, et al.*2026*
40. **[Vocabulary Shapes Cross-Lingual Variation of Word-Order Learnability in Language Models](https://md.research.elamur.ai/free/en/papers/martins-2026-vocabulary-shapes-cross-lingual-variation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonas Mayer Martins, Jaap Jumelet, Viola Priesemann, et al.*2026*

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

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