---
title: "Who cites Kuang-Huei Lee — page 2 — 515 papers of our library"
description: "515 papers of the Elamur Research library cite the works of Kuang-Huei Lee, found in their bibliographies · page 2 of 2 · 101–160; the most…"
canonical: "https://research.elamur.ai/free/en/authors/kuang-huei-lee/cited-by/page/2/"
---
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# Who cites Kuang-Huei Lee

526 citations of their works from 515 papers of our library (of the 149,439 whose bibliographies we read) · 160 with a page here, the most cited first · page 2 of 2 · 101–160 · [← Kuang-Huei Lee](https://md.research.elamur.ai/free/en/authors/kuang-huei-lee/)

[← prev](https://md.research.elamur.ai/free/en/authors/kuang-huei-lee/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/kuang-huei-lee/cited-by/) **2**

101. **[Learning to Reason and Memorize with Self-Notes](https://md.research.elamur.ai/free/en/papers/lanchantin-2023-learning-reason-memorize-self-notes/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jack Lanchantin, Shubham Toshniwal, Jason Weston, et al.*2023 · 21 citations*
102. [**The Vector Grounding Problem arXiv:2304.01481**Dimitri Coelho Mollo, Raphael Milliere*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/mollo-2023-vector-grounding-problem/)
103. [**Quality-Diversity through AI Feedback arXiv:2310.13032**Herbie Bradley, Andrew Dai, Hannah Teufel, et al.*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/bradley-2023-quality-diversity-through-ai-feedback/)
104. **[Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools](https://md.research.elamur.ai/free/en/papers/hao-2025-large-language-models-can-solve/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yilun Hao, Yongchao Chen, Yang Zhang, et al.*2025 · 18 citations*
105. [**Aviary: training language agents on challenging scientific tasks arXiv:2412.21154**Siddharth Narayanan, James D. Braza, Ryan-Rhys Griffiths, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/narayanan-2024-aviary-training-language-agents/)
106. [**Language Models, Agent Models, and World Models: The LAW for Machine Reasoning and Planning arXiv:2312.05230**Zhiting Hu, Tianmin Shu*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-language-models-agent-models-world/)
107. [**Large Language Model Programs arXiv:2305.05364**Imanol Schlag, Sainbayar Sukhbaatar, Asli Celikyilmaz, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/schlag-2023-large-language-model-programs/)
108. **[Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction](https://md.research.elamur.ai/free/en/papers/cai-2023-open-world-multi-task-control/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Shaofei Cai, Zihao Wang, Xiaojian Ma, et al.*2023 · 18 citations*
109. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mihir Parmar, Xin Liu, Palash Goyal, et al.*2025 · 16 citations*
110. [**Sparks of Science: Hypothesis Generation Using Structured Paper Data arXiv:2504.12976**Charles O'Neill, Tirthankar Ghosal, Roberta R\uaileanu, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/o-neill-2025-sparks-science-hypothesis-generation-using/)
111. **[Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS](https://md.research.elamur.ai/free/en/papers/xu-2026-self-correcting-rag-enhancing-faithfulness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Zhou Wu, Xiaolong Jia, et al.*2026 · 15 citations*
112. [**Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search arXiv:2405.15383**Nicola Dainese, Matteo Merler, Minttu Alakuijala, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/dainese-2024-generating-code-world-models/)
113. [**Open-Endedness is Essential for Artificial Superhuman Intelligence arXiv:2406.04268**Edward Hughes, Michael Dennis, Jack Parker-Holder, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hughes-2024-open-endedness-essential-artificial-superhuman/)
114. **[Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2026-meta-reasoner-dynamic-guidance-optimized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Sui, Yufei He, Tri Cao, et al.*2026 · 13 citations*
115. [**Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency arXiv:2309.17382**Zhihan Liu, Hao Hu, Shenao Zhang, et al.*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-reason-future-act-now-principled/)
116. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning arXiv:2504.01005**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
117. **[Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic Puzzles](https://md.research.elamur.ai/free/en/papers/shah-2024-causal-language-modeling-elicit-search/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Kulin Shah, Nishanth Dikkala, Xin Wang, et al.*2024 · 12 citations*
118. **[Scaffolding Coordinates to Promote Vision-Language Coordination in Large Multi-Modal Models](https://md.research.elamur.ai/free/en/papers/lei-2025-scaffolding-coordinates-promote-vision-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Xuanyu Lei, Zonghan Yang, Xinrui Chen, et al.*2025 · 11 citations*
119. [**Augmenting Autotelic Agents with Large Language Models arXiv:2305.12487**Cedric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/colas-2023-augmenting-autotelic-agents-large-language/)
120. [**Learning and Leveraging Verifiers to Improve Planning Capabilities of Pre-trained Language Models arXiv:2305.17077**Daman Arora, Subbarao Kambhampati*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/arora-2023-learning-leveraging-verifiers-improve-planning/)
121. **[Language Modeling by Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2025-language-modeling-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junyan Cheng, Peter Clark, Kyle Richardson*2025 · 9 citations*
122. **[Problem Solving Through Human–AI Preference-based Cooperation](https://md.research.elamur.ai/free/en/papers/dutta-2025-problem-solving-through-human-ai/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.*2025 · 9 citations*
123. [**Distilling Internet-Scale Vision-Language Models into Embodied Agents arXiv:2301.12507**Theodore Sumers, Kenneth Marino, Arun Ahuja, et al.*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/sumers-2023-distilling-internet-scale-vision-language/)
124. **[H-MEM: Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents](https://md.research.elamur.ai/free/en/papers/sun-2026-h-mem-hierarchical-memory-high/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Haoran Sun, Shaoning Zeng, Bob Zhang*2026 · 8 citations*
125. **[Lightweight LLM Agent Memory with Small Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-lightweight-llm-agent-memory-small/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaquan Zhang, Chaoning Zhang, Shuxu Chen, et al.*2026 · 6 citations*
126. **[ChartAgent: A Multimodal Agent for Visually Grounded Reasoning in Complex Chart Question Answering](https://md.research.elamur.ai/free/en/papers/kaur-2026-chartagent-multimodal-agent-visually-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rachneet Kaur, Nishan Srishankar, Zhen Zeng, et al.*2026 · 5 citations*
127. **[Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2026-embodied-reasoner-synergizing-visual-search/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Mengna Wang, Gangao Liu, et al.*2026 · 5 citations*
128. **[GAM: Hierarchical Graph-based Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/wu-2026-gam-hierarchical-graph-based-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaofen Wu, Hanrong Zhang, Fulin Lin, et al.*2026 · 5 citations*
129. **[Growing Through Experience: Scaling Episodic Grounding in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-growing-through-experience-scaling-episodic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chunhui Zhang, Sirui Wang, Zhongyu Ouyang, et al.*2025 · 5 citations*
130. **[Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?](https://md.research.elamur.ai/free/en/papers/yan-2025-recitation-over-reasoning-how-cutting/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kai Yan, Yufei Xu, Zhengyin Du, et al.*2025 · 5 citations*
131. **[Preference-Aware Memory Update for Long-Term LLM Agents](https://md.research.elamur.ai/free/en/papers/sun-2026-preference-aware-memory-update-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Sun, Zekun Zhang, Shaoning Zeng*2026 · 4 citations*
132. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
133. **[From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms](https://md.research.elamur.ai/free/en/papers/luo-2026-storage-experience-survey-evolution-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghao Luo, Yuchen Tian, Chuxue Cao, et al.*2026 · 3 citations*
134. **[Tailoring Memory Granularity for Multi-Hop Reasoning over Long Contexts](https://md.research.elamur.ai/free/en/papers/qing-2026-tailoring-memory-granularity-multi-hop/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peijun Qing, Xingjian Diao, Chiyu Ma, et al.*2026 · 3 citations*
135. **[HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/zhu-2026-hela-mem-hebbian-learning-associative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinchang Zhu, Jindong Li, Cheng Zhang, et al.*2026 · 2 citations*
136. **[Strong Reasoning Isn't Enough: Evaluating Evidence Elicitation in Interactive Diagnosis](https://md.research.elamur.ai/free/en/papers/long-2026-strong-reasoning-isn-t-enough/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohan Long, Zhongyu Wei*2026 · 1 citation*
137. [**Language Models are Bounded Pragmatic Speakers: Understanding RLHF from a Bayesian Cognitive Modeling Perspective arXiv:2305.17760**Khanh Nguyen*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-language-models-bounded-pragmatic-speakers/)
138. **[A Dual-Phase Self-Evolution Framework for Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-dual-phase-self-evolution-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Sun, Zekun Zhang, Shaoning Zeng*2026*
139. **[AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-alphacontext-evolutionary-tree-based-psychometric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Wang, Yue Huang, Hong Qian, et al.*2026*
140. **[Amory: Building Coherent Narrative-Driven Agent Memory through Agentic Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2026-amory-building-coherent-narrative-driven/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yue Zhou, Xiaobo Guo, Belhassen Bayar, et al.*2026*
141. **[Are My Optimized Prompts Compromised? Exploring Vulnerabilities of LLM-based Optimizers](https://md.research.elamur.ai/free/en/papers/zhao-2026-are-my-optimized-prompts-compromised/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Andrew Zhao, Reshmi Ghosh, Vitor R. Carvalho, et al.*2026*
142. **[Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics](https://md.research.elamur.ai/free/en/papers/qiu-2026-can-vlms-predict-future-states/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifu Qiu, Yftah Ziser, Anna Korhonen, et al.*2026*
143. **[CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs](https://md.research.elamur.ai/free/en/papers/qi-2026-carl-constraint-aware-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiuyi Qi, Jinjian Zhang, Mutian Bao, et al.*2026*
144. **[Conflict-Aware Memory for Embodied Agents: Enhancing Vector Data Quality via Detection Rules](https://md.research.elamur.ai/free/en/papers/ma-2026-conflict-aware-memory-embodied-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kexin Ma, Haotian Wang, Shenglin Chen, et al.*2026*
145. **[Context-Aware Language Understanding in Human-Robot Dialogue with LLMs](https://md.research.elamur.ai/free/en/papers/stoyanchev-2026-context-aware-language-understanding-human/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Svetlana Stoyanchev, Youmna Farag, Simon Keizer, et al.*2026*
146. **[CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-cotevol-self-evolving-chain-thoughts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuo Wang, Zhuo Zhang, Yafu Li, et al.*2026*
147. **[Evolutionary Search for Automated Design of Uncertainty Quantification Methods](https://md.research.elamur.ai/free/en/papers/seleznyov-2026-evolutionary-search-automated-design-uncertainty/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mikhail Seleznyov, Daniil Korbut, Viktor Moskvoretskii, et al.*2026*
148. **[FalconCopilot: Empowering LLMs Towards Integrated Human-Machine Systems for Aviation Autonomy](https://md.research.elamur.ai/free/en/papers/yan-2026-falconcopilot-empowering-llms-integrated-human/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyuan Yan, Qingchen Liu, Qichao Ma, et al.*2026*
149. **[Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality](https://md.research.elamur.ai/free/en/papers/zhang-2026-follow-path-reasoning-over-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhang, Johannes Bjerva, Russa Biswas*2026*
150. **[Frame2KG: A Benchmark and Evaluation Toolkit for Interpretable Frame-to-Graph Generation](https://md.research.elamur.ai/free/en/papers/watson-2026-frame2kg-benchmark-evaluation-toolkit-interpretable/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lewis N. Watson, Carl Strathearn, Kenny Mitchell, et al.*2026*
151. **[LARA: LLM-based Agile Power Distribution Network Restoration from Disastrous Events](https://md.research.elamur.ai/free/en/papers/warrier-2026-lara-llm-based-agile-power/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jishnu Warrier, Heqing Huang, Yuzhang Lin, et al.*2026*
152. **[Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory](https://md.research.elamur.ai/free/en/papers/xu-2026-learning-how-what-memorize-cognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Derong Xu, Shuochen Liu, Pengfei Luo, et al.*2026*
153. **[MADRA: Multi-Agent Debate for Risk-Aware Embodied Planning](https://md.research.elamur.ai/free/en/papers/wang-2026-madra-multi-agent-debate-risk/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**JunJian Wang, Lidan Zhao, Xi Sheryl Zhang*2026*
154. **[MemWeaver: Weaving Hybrid Memories for Traceable Long-Horizon Agentic Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2026-memweaver-weaving-hybrid-memories-traceable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Juexiang Ye, Xue Li, Yang Xinyu, et al.*2026*
155. **[MIRTH: Mutual-Information Reasoning with Temporal Hubs for Vision-Language-Action Agents](https://md.research.elamur.ai/free/en/papers/sun-2026-mirth-mutual-information-reasoning-temporal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Sun, Yu Song, Teng Shiyu, et al.*2026*
156. **[Parallel Test-Time Scaling for Latent Reasoning Models](https://md.research.elamur.ai/free/en/papers/you-2026-parallel-test-time-scaling-latent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runyang You, Yongqi Li, Meng Liu, et al.*2026*
157. **[Self-Consistency from Only Two Samples: CoT–PoT Ensembling for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/saparkhan-2026-self-consistency-only-two-samples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raman Saparkhan, Majd Hawasly, Md Rizwan Parvez, et al.*2026*
158. **[Self-Guided Plan Extraction for Instruction-Following Tasks with Goal-Conditional Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/volovikova-2026-self-guided-plan-extraction-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zoya Volovikova, Nikita Sorokin, Dmitriy Lukashevskiy, et al.*2026*
159. [**Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述) Acta Automatica Sinica (自动化学报)**Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.*2025*](https://md.research.elamur.ai/free/en/papers/wang-2025-embodied-intelligence-systems/)
160. [**Survey of Tool Use in Large Language Models (大语言模型的工具使用综述) Acta Automatica Sinica (自动化学报)**Yining Zheng (郑逸宁), Zhen Yu (余镇), Bufan Li (李不凡), et al.*2025*](https://md.research.elamur.ai/free/en/papers/zheng-2025-tool-use-large/)

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