--- title: "Who cites Jiahao Wang — 97 papers of our library" description: "97 papers of the Elamur Research library cite the works of Jiahao Wang, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/jiahao-wang/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jiahao-wang/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Jiahao Wang](https://md.research.elamur.ai/free/en/authors/jiahao-wang/) / cited by # Who cites Jiahao Wang 97 citations of their works from 97 papers of our library (of the 149,439 whose bibliographies we read) · 19 with a page here, the most cited first · [← Jiahao Wang](https://md.research.elamur.ai/free/en/authors/jiahao-wang/) 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. **[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* 5. [**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/) 6. [**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/) 7. **[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* 8. **[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* 9. [**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/) 10. **[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* 11. [**AutoSOTA: An End-to-End Automated Research System for State-of-the-Art AI Model Discovery arXiv:2604.05550**Yu Li, Chenyang Shao, Xinyang Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/li-2026-autosota-end-end-automated-research/) 12. **[Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models](https://md.research.elamur.ai/free/en/papers/xiao-2026-exploring-layer-wise-information-effectiveness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**He Xiao, Qingyao Yang, Dirui Xie, et al.*2026 · 5 citations* 13. [**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/) 14. **[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* 15. **[Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-bit-bit-progressive-qat-strategy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binxing Xu, Hao Gu, Lujun Li, et al.*2026 · 3 citations* 16. **[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* 17. **[ACBQ: Adaptive Cross-Block Quantization of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-acbq-adaptive-cross-block-quantization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hailing Wang, Jianglin Lu, Yitian Zhang, et al.*2026* 18. **[LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation](https://md.research.elamur.ai/free/en/papers/song-2026-lbllm-lightweight-binarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siqing Song, Chuang Wang, Yong Lang, et al.*2026* 19. **[pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-pquant-effective-low-bit-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenzheng Zhang, Bingzheng Liu*2026* 78 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/jiahao-wang/) — Jiahao Wang