---
title: "Who cites Subbarao Kambhampati — 337 papers of our library"
description: "337 papers of the Elamur Research library cite the works of Subbarao Kambhampati, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/subbarao-kambhampati/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/subbarao-kambhampati/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Subbarao Kambhampati](https://md.research.elamur.ai/free/en/authors/subbarao-kambhampati/) / cited by

# Who cites Subbarao Kambhampati

452 citations of their works from 337 papers of our library (of the 149,439 whose bibliographies we read) · 82 with a page here, the most cited first · [← Subbarao Kambhampati](https://md.research.elamur.ai/free/en/authors/subbarao-kambhampati/)

1. **[Explanation in Artificial Intelligence: Insights from the Social Sciences](https://md.research.elamur.ai/free/en/papers/miller-2017-explanation-artificial-intelligence-insights-social/) [Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/artificial-intelligence/)**Tim Miller*2017 · 5,372 citations*
2. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
3. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arXiv:2403.05530**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
4. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
5. **[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*
6. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/)
7. **[Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.*2023 · 690 citations*
8. **[Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives](https://md.research.elamur.ai/free/en/papers/gao-2023-large-language-models-empowered-agent/) [Humanities and Social Sciences Communications](https://md.research.elamur.ai/free/en/venues/humanities-and-social-sciences-communications/)**Chen Gao, Xiaochong Lan, Nian Li, et al.*2023 · 344 citations*
9. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models arXiv:2410.05229**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
10. [**Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought arXiv:2210.01240**Abulhair Saparov, He He*2022 · 244 citations*](https://md.research.elamur.ai/free/en/papers/saparov-2022-language-models-greedy-reasoners-systematic/)
11. **[PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change](https://md.research.elamur.ai/free/en/papers/valmeekam-2022-planbench-extensible-benchmark-evaluating-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.*2022 · 222 citations*
12. [**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/)
13. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking arXiv:2501.04519**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
14. **[Many-Shot In-Context Learning](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 142 citations*
15. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
16. [**Understanding the planning of LLM agents: A survey arXiv:2402.02716**Xu Huang, Weiwen Liu, Xiaolong Chen, et al.*2024 · 128 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-understanding-planning-llm-agents-survey/)
17. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
18. [**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/)
19. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
20. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
21. **[Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning](https://md.research.elamur.ai/free/en/papers/guan-2023-leveraging-pre-trained-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lin Guan, Karthik Valmeekam, Sarath Sreedharan, et al.*2023 · 115 citations*
22. **[Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language Models](https://md.research.elamur.ai/free/en/papers/arora-2023-have-llms-advanced-enough-challenging/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daman Arora, Himanshu Singh, Mausam*2023 · 107 citations*
23. **[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*
24. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations*
25. [**LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks arXiv:2402.01817 · Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024**Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/kambhampati-2024-llms-t-plan-but-help/)
26. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
27. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations*
28. **[TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks](https://md.research.elamur.ai/free/en/papers/xu-2024-theagentcompany-benchmarking-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Frank F. Xu, Yufan Song, Boxuan Li, et al.*2024 · 68 citations*
29. **[SatLM: Satisfiability-Aided Language Models Using Declarative Prompting](https://md.research.elamur.ai/free/en/papers/ye-2023-satlm-satisfiability-aided-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Qiaochu Chen, Isil Dillig, et al.*2023 · 62 citations*
30. [**Tree Search for Language Model Agents arXiv:2407.01476**Jing Yu Koh, Stephen McAleer, Daniel Fried, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-tree-search-language-model-agents/)
31. **[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*
32. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/)
33. [**Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning arXiv:2406.14283**Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-q-improving-multi-step-reasoning/)
34. **[NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes](https://md.research.elamur.ai/free/en/papers/fan-2024-nphardeval-dynamic-benchmark-reasoning-ability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lizhou Fan, Wenyue Hua, Lingyao Li, et al.*2024 · 47 citations*
35. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations*
36. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/)
37. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
38. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations*
39. **[When is Tree Search Useful for LLM Planning? It Depends on the Discriminator](https://md.research.elamur.ai/free/en/papers/chen-2024-when-is-tree-search-useful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziru Chen, Michael White, Ray Mooney, et al.*2024 · 28 citations*
40. **[LLM Agents Making Agent Tools](https://md.research.elamur.ai/free/en/papers/wolflein-2025-llm-agents-making-agent-tools/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Georg Wölflein, Dyke Ferber, Daniel Truhn, et al.*2025 · 27 citations*
41. [**Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language Models arXiv:2310.00836**Man Luo, Shrinidhi Kumbhar, Ming shen, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-towards-logiglue-brief-survey-benchmark/)
42. [**PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning arXiv:2305.19472**Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/brahman-2023-plasma-making-small-language-models/)
43. **[SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/valentino-2026-semeval-2026-task-11-disentangling/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Marco Valentino, Leonardo Ranaldi, Giulia Pucci, et al.*2026 · 22 citations*
44. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
45. **[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*
46. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations*
47. [**Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation arXiv:2407.08940**Biqing Qi, Kaiyan Zhang, Kai Tian, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-large-language-models-biomedical-hypothesis/)
48. **[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*
49. **[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*
50. [**Data-driven Discovery with Large Generative Models arXiv:2402.13610**Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2024-data-driven-discovery-large-generative/)
51. [**101 Billion Arabic Words Dataset arXiv:2405.01590**Manel Aloui, Hasna Chouikhi, Ghaith Chaabane, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/aloui-2024-101-billion-arabic-words-dataset/)
52. [**Mixed Distillation Helps Smaller Language Model Better Reasoning arXiv:2312.10730**Chenglin Li, Qianglong Chen, Liangyue Li, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-mixed-distillation-helps-smaller-language/)
53. **[Planning with Multi-Constraints via Collaborative Language Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-planning-multi-constraints-collaborative-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Cong Zhang, Xin Deik Goh, Dexun Li, et al.*2025 · 10 citations*
54. [**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/)
55. **[MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/li-2026-mtr-bench-comprehensive-benchmark-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Li, Keqin Bao, Yubo Ma, et al.*2026 · 9 citations*
56. **[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*
57. **[Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2025-marco-o1-v2-widening/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huifeng Yin, Yu Zhao, Minghao Wu, et al.*2025 · 8 citations*
58. **[SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding](https://md.research.elamur.ai/free/en/papers/wang-2025-seed-accelerating-reasoning-tree-construction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhenglin Wang, Jialong Wu, Yilong Lai, et al.*2025 · 8 citations*
59. **[DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints](https://md.research.elamur.ai/free/en/papers/zhang-2026-deepplanning-benchmarking-long-horizon-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinger Zhang, Shutong Jiang, Renhao Li, et al.*2026 · 5 citations*
60. **[Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?](https://md.research.elamur.ai/free/en/papers/lim-2025-analysing-chain-thought-dynamics-active/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao, et al.*2025 · 5 citations*
61. **[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*
62. **[DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-deeppresenter-environment-grounded-reflection-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zheng, Guozhao Mo, Xinru Yan, et al.*2026 · 3 citations*
63. **[AOT*: Efficient Synthesis Planning via LLM-Empowered AND-OR Tree Search](https://md.research.elamur.ai/free/en/papers/song-2026-aot-efficient-synthesis-planning-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaozhuang Song, Xuanhao Pan, Xinjian Zhao, et al.*2026 · 2 citations*
64. **[Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math](https://md.research.elamur.ai/free/en/papers/pandit-2026-hard2verify-step-level-verification-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.*2026 · 2 citations*
65. **[InferenceDynamics: Adaptive LLM Routing through Structured Capability and Knowledge Profiling](https://md.research.elamur.ai/free/en/papers/shi-2026-inferencedynamics-adaptive-llm-routing-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Shi, Tianshi Zheng, Weiqi Wang, et al.*2026 · 1 citation*
66. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation*
67. **[Verification-Aware Planning for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/xu-2026-verification-aware-planning-multi-agent/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianyang Xu, Dan Zhang, Kushan Mitra, et al.*2026 · 1 citation*
68. **[Construction Grammar Evidence for How LLMs Use Context-Directed Extrapolation to Solve Tasks](https://md.research.elamur.ai/free/en/papers/madabushi-2025-construction-grammar-evidence-how-llms/) [International Workshop on Construction Grammars and NLP](https://md.research.elamur.ai/free/en/venues/cxgsnlp/)**Harish Tayyar Madabushi, Claire Bonial*2025 · 1 citation*
69. [**Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering**Polina Tsvilodub, Robert D. Hawkins, Michael Franke*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2025-integrating-neural-symbolic-components-model/)
70. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
71. **[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*
72. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
73. **[DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents](https://md.research.elamur.ai/free/en/papers/shi-2026-damo-data-mixing-optimizer-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Shi, Jun Yang, Ni Yang, et al.*2026*
74. **[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*
75. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
76. **[Knowledge Vector of Logical Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-knowledge-vector-logical-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zixuan Wang, Yuanyuan Lei*2026*
77. **[Multi-Constraint State Tracking with Negation: A Diagnostic Benchmark for LLM World Modeling](https://md.research.elamur.ai/free/en/papers/sar-2026-multi-constraint-state-tracking-negation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ayan Sar, Pranav Singh Puri, Sumit Aich, et al.*2026*
78. **[NaturalGAIA: A Verifiable Benchmark and Hierarchical Framework for Long-Horizon GUI Tasks](https://md.research.elamur.ai/free/en/papers/zheng-2026-naturalgaia-verifiable-benchmark-hierarchical-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Zheng, Tianle Cui, Taoran Wang, et al.*2026*
79. **[Navigating the Infinite Dynamic Web Space: Effective In-Context Exploration via Cognitive Multi-Agent Collaboration](https://md.research.elamur.ai/free/en/papers/mo-2026-navigating-infinite-dynamic-web-space/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Guozhao Mo, Yanjiang Liu, Yafei Shi, et al.*2026*
80. **[To Skip, to Swap or to Not Swap? Identifying Step Transition Types in Instructional Manuals](https://md.research.elamur.ai/free/en/papers/yang-2026-skip-swap-or-not-swap/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hsiu-Yu Yang, Michael Roth, Andreas Bulling, et al.*2026*
81. **[Tool-Aware Planning for Contact-Center Analytics: Evaluating LLMs through Lineage-Guided Query Decomposition](https://md.research.elamur.ai/free/en/papers/nathan-2026-tool-aware-planning-contact-center/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Varun Nathan, Shreyas Guha, Ayush Kumar*2026*
82. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/subbarao-kambhampati/) — Subbarao Kambhampati