---
title: "Who cites Leslie Pack Kaelbling — 184 papers of our library"
description: "184 papers of the Elamur Research library cite the works of Leslie Pack Kaelbling, found in their bibliographies; the most cited first."
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---
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# Who cites Leslie Pack Kaelbling

185 citations of their works from 184 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← Leslie Pack Kaelbling](https://md.research.elamur.ai/free/en/authors/leslie-pack-kaelbling/)

1. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
2. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
3. [**LLM+P: Empowering Large Language Models with Optimal Planning Proficiency arXiv:2304.11477**Bo Liu, Yuqian Jiang, Xiaohan Zhang, et al.*2023 · 216 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-llm-p-empowering-large-language/)
4. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
5. **[Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models](https://md.research.elamur.ai/free/en/papers/zhao-2019-rethinking-action-spaces-reinforcement-learning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tiancheng Zhao, Kaige Xie, Maxine Eskenazi*2019 · 169 citations*
6. **[Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion](https://md.research.elamur.ai/free/en/papers/huang-2025-self-forcing-bridging-train-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xun Huang, Zhengqi Li, Guande He, et al.*2025 · 146 citations*
7. [**Efficient Processing of Deep Neural Networks: A Tutorial and Survey Proceedings of the IEEE 2017**Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, et al.*2017 · 146 citations*](https://md.research.elamur.ai/free/en/papers/sze-2017-efficient-processing-deep-neural-networks/)
8. [**Eureka: Human-Level Reward Design via Coding Large Language Models arXiv:2310.12931**Yecheng Jason Ma, William Liang, Guanzhi Wang, et al.*2023 · 142 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-eureka-human-level-reward-design/)
9. [**A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis arXiv:2307.12856**Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/gur-2023-real-world-webagent-planning-long/)
10. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
11. [**Qwen-Image Technical Report arXiv:2508.02324**Chenfei Wu, Jiahao Li, Jingren Zhou, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-qwen-image-technical-report/)
12. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
13. [**Seed-TTS: A Family of High-Quality Versatile Speech Generation Models arXiv:2406.02430**Philip Anastassiou, Jiawei Chen, Jitong Chen, et al.*2024 · 71 citations*](https://md.research.elamur.ai/free/en/papers/anastassiou-2024-seed-tts-family-high/)
14. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
15. [**Diffusion Models Are Real-Time Game Engines arXiv:2408.14837**Dani Valevski, Yaniv Leviathan, Moab Arar, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/valevski-2024-diffusion-models-real-time-game/)
16. **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 38 citations*
17. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
18. **[VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vrag-rl-empower-vision-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.*2025 · 23 citations*
19. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
20. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations*
21. [**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/)
22. [**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/)
23. [**Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive Search arXiv:2502.02508**Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-satori-reinforcement-learning-chain-action/)
24. [**EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models arXiv:2402.11430**Jun Gao, Huan Zhao, Wei Wang, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-eventrl-enhancing-event-extraction-outcome/)
25. **[R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhao-2026-r-search-empowering-llm-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingfei Zhao, Ruobing Wang, Dingling Xu, et al.*2026 · 7 citations*
26. [**Time Series Forecasting via Reasoning: A Slow-Thinking Approach with Reinforcement Fine-Tuned LLMs arXiv:2506.10630**Yitong Zhou, Yucong Luo, Mingyue Cheng, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-time-series-forecasting-reasoning-slow/)
27. **[ChatR1: Reinforcement Learning for Conversational Reasoning and Retrieval Augmented Question Answering](https://md.research.elamur.ai/free/en/papers/lupart-2026-chatr1-reinforcement-learning-conversational-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simon Lupart, Mohammad Aliannejadi, Evangelos Kanoulas*2026 · 5 citations*
28. **[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*
29. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
30. **[ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs](https://md.research.elamur.ai/free/en/papers/ding-2026-promed-shapley-information-gain-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongxin Ding, Baixiang Huang, Yue Fang, et al.*2026 · 4 citations*
31. **[Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/gong-2026-temp-r1-unified-autonomous-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoyan Gong, Zhiqiang Liu, Songze Li, et al.*2026 · 4 citations*
32. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation*
33. **[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*
34. **[GaLa: Hypergraph-Guided Visual Language Models for Procedural Planning](https://md.research.elamur.ai/free/en/papers/wang-2026-gala-hypergraph-guided-visual-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kun Wang, Li Yiming, Mingcheng Qu, et al.*2026*
35. **[GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy Inputs](https://md.research.elamur.ai/free/en/papers/zhang-2026-gsm-noise-exploring-enhancing-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengxin Zhang, Chengyu Huang, Xufu Liu, et al.*2026*
36. **[Learning to Control Summaries with Score Ranking](https://md.research.elamur.ai/free/en/papers/liu-2026-learning-control-summaries-score-ranking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongye Liu, Liang Ding, Ricardo Henao*2026*
37. **[Mitigating Context Interference for Reliable and Efficient Search Agents](https://md.research.elamur.ai/free/en/papers/xue-2026-mitigating-context-interference-reliable-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyang Xue, Bin Wu, Shuofei Qiao, et al.*2026*
38. **[PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plane-meta-planning-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Wang, Weiyan Zhang, Guangya Yu*2026*
39. [**Qwen-AgentWorld: Language World Models for General Agents arXiv:2606.24597**Yuxin Zuo, Zikai Xiao, Li Sheng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zuo-2026-qwen-agentworld-language-world/)
40. **[Methods for Constraint Solving Problems Based on Learn to Reason Model: A Review (基于学习-推理的约束求解方法研究进展)](https://md.research.elamur.ai/free/en/papers/zou-2023-methods-constraint-solving/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yue Zou (邹悦), Jiayang Lai (赖家洋), Yonggang Zhang (张永刚)*2023*

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

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