---
title: "Who cites Ee-Peng Lim — page 2 — 573 papers of our library"
description: "573 papers of the Elamur Research library cite the works of Ee-Peng Lim, found in their bibliographies · page 2 of 2 · 101–130; the most cited first."
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---
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# Who cites Ee-Peng Lim

614 citations of their works from 573 papers of our library (of the 149,439 whose bibliographies we read) · 130 with a page here, the most cited first · page 2 of 2 · 101–130 · [← Ee-Peng Lim](https://md.research.elamur.ai/free/en/authors/ee-peng-lim/)

[← prev](https://md.research.elamur.ai/free/en/authors/ee-peng-lim/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/ee-peng-lim/cited-by/) **2**

101. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
102. **[Action Boundary Blindness: When LLM Agents Cannot Tell Where One Action Ends and Another Begins](https://md.research.elamur.ai/free/en/papers/wang-2026-action-boundary-blindness-when-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangyi Wang, Bingnan Yu, Jiexiang Xu, et al.*2026*
103. **[Can Spectral-Clipping Enable Better Learning While Forgetting Less for Low-Rank Adaptation?](https://md.research.elamur.ai/free/en/papers/wi-2026-can-spectral-clipping-enable-better/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hyowon Wi, Noseong Park*2026*
104. **[CAP: Controllable Alignment Prompting for Unlearning in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-cap-controllable-alignment-prompting-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaokun Wang, Jinyu Guo, Jingwen Pu, et al.*2026*
105. **[CAR: Empowering Agents with Dynamic Tool Synthesis and Global Trajectory Rectification](https://md.research.elamur.ai/free/en/papers/wang-2026-car-empowering-agents-dynamic-tool/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Wang, Xu Wang, Zhiyuan Fu, et al.*2026*
106. **[C³D: Enhancing LLM Reasoning via Confidence-Guided Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-c-3-d-enhancing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Zhang, Xuepeng Wang, Lingxiang Wu, et al.*2026*
107. **[FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation](https://md.research.elamur.ai/free/en/papers/siddika-2026-fedreft-federated-representation-fine-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fatema Siddika, Md Anwar Hossen, Juan Pablo Munoz, et al.*2026*
108. **[From Coarse to Fine: Self-Adaptive Hierarchical Planning for LLM Agents](https://md.research.elamur.ai/free/en/papers/tan-2026-coarse-fine-self-adaptive-hierarchical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Tan, Zeyu Zhang, Chen Ma, et al.*2026*
109. **[G-LoRA: Global-Local Decoupled Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/xiong-2026-g-lora-global-local-decoupled/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiahao Xiong, Yihong Huang, Yihe Liu, et al.*2026*
110. **[GAST: Gradient-aligned Sparse Tuning of Large Language Models with Data-layer Selection](https://md.research.elamur.ai/free/en/papers/yao-2026-gast-gradient-aligned-sparse-tuning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kai Yao, Zhenghan Song, Kaixin Wu, et al.*2026*
111. **[GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning](https://md.research.elamur.ai/free/en/papers/tian-2026-grass-gradient-based-adaptive-layer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiyuan Tian, Linbo Qiao, Yu Tang, et al.*2026*
112. **[How to Train a Real-World Silicon Concierge? Internalizing Complex Business Workflow to Only OneModel](https://md.research.elamur.ai/free/en/papers/tong-2026-how-train-real-world-silicon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongqi Tong, Xiaoyun Feng, Lyuxin Xue, et al.*2026*
113. **[IMRNNs: An Efficient Method for Interpretable Dense Retrieval via Embedding Modulation](https://md.research.elamur.ai/free/en/papers/saxena-2026-imrnns-efficient-method-interpretable-dense/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yash Saxena, Ankur Padia, Kalpa Gunaratna, et al.*2026*
114. **[KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/saha-2026-kismath-do-llms-have-knowledge/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Soumadeep Saha, Akshay Chaturvedi, Saptarshi Saha, et al.*2026*
115. **[LeLoRA: Learnable Low-Rank Adaptation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lelora-learnable-low-rank-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoling Zhou, Mingjie Zhang, Zhemg Lee, et al.*2026*
116. **[Localized Low-Rank Adaptation within Clustered Parameter Subspaces](https://md.research.elamur.ai/free/en/papers/xiong-2026-localized-low-rank-adaptation-within/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiahao Xiong, Yihe Liu, Xianming Hu, et al.*2026*
117. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Xingle Xu, Ercong Nie, et al.*2026*
118. **[On LLM Prompting Techniques for Arabic Language Arithmetic Reasoning](https://md.research.elamur.ai/free/en/papers/alenezi-2026-llm-prompting-techniques-arabic-language/) [Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/)**Reem Alenezi, Ayed Atallah Salman*2026*
119. **[On the Representation Geometry of LoRA Model Merging](https://md.research.elamur.ai/free/en/papers/lu-2026-representation-geometry-lora-model-merging/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenyang Lu, Jiaru Li, Jinman Zhao, et al.*2026*
120. **[ParaCook: On Time-Efficient Planning for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-paracook-time-efficient-planning-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiqi Zhang, Xinbei Ma, Yunqing Xu, et al.*2026*
121. **[Policy-Guided Stepwise Action Planning for Controllable LLM Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2026-policy-guided-stepwise-action-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianpeng Zhou, Qisheng Hu, Jiahai Wang, et al.*2026*
122. **[QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/qu-2026-quantumqa-enhancing-scientific-reasoning-physics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Songxin Qu, Tai-Ping Sun, Yun-Jie Wang, et al.*2026*
123. **[RanLoRA: Residual-aware Nonlinear Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/luo-2026-ranlora-residual-aware-nonlinear-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Luo, Yongbin Liu, Chunping Ouyang, et al.*2026*
124. **[Self-EmoQ: Plutchik-Guided Value-based Planning to Drive Streaming Emotional TTS](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-emoq-plutchik-guided-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yue Zhao, Hongyan Li, Yong Chen, et al.*2026*
125. **[SR-RAG: Verifiable Multi-Hop Reasoning via On-the-fly Symbolic Graph Construction](https://md.research.elamur.ai/free/en/papers/wang-2026-sr-rag-verifiable-multi-hop/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zehua Wang, Zhaojin Zhang, Boyu Qiu, et al.*2026*
126. **[STCOR: A Trilevel Syllogism-Driven Reasoning Framework](https://md.research.elamur.ai/free/en/papers/yang-2026-stcor-trilevel-syllogism-driven-reasoning/) [Workshop on Argument Mining](https://md.research.elamur.ai/free/en/venues/argmining/)**Keying Yang, Hao Wang, Chengtao Jian, et al.*2026*
127. **[TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models](https://md.research.elamur.ai/free/en/papers/wang-2026-tare-lightweight-token-aware-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Siyu Zhao*2026*
128. **[TeleAI at SemEval-2026 Task 6: A Confidence-Aware Multi-Stage Reasoning Framework with Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/shi-2026-teleai-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Lingling Shi, Haoyu Jin, Shiquan Wang, et al.*2026*
129. **[Weakly-supervised Argument Mining with Boundary Refinement and Relation Denoising](https://md.research.elamur.ai/free/en/papers/sun-2026-weakly-supervised-argument-mining-boundary/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Wei Sun, Mingxiao Li, Jesse Davis, et al.*2026*
130. **[ZIP: Quantifying Which Words Matter in Zero-Shot Instructional Prompts](https://md.research.elamur.ai/free/en/papers/sadr-2026-zip-quantifying-which-words-matter/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Nikta Gohari Sadr, Sangmitra Madhusudan, Arash Asgari, et al.*2026*

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