LLM Planning

LLM: Large Language Model

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12 papers in the last four weeks, up 300% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28

Latest papers 92

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CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs
Jul 6, 2026Qiuyi Qi, Jinjian Zhang, Mutian Bao +9RL for Language Models LLM Planning
Zhejiang University · Ant Group · City University of Hong Kong
URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment
Jul 6, 2026Bogdan Zagribelnyy, Ivan Ilin, Nikita Bondarev +7LLM Evaluation LLM Planning
Insilico Medicine AI Limited, Masdar City, Abu Dhabi, UAE · Independent researcher · Insilico Medicine Canada Inc., Montreal, Quebec, Canada +1
Toward Secure and Reliable PDDL Formalization of Large Language Models with Planner-in-the-Loop Feedback
Jun 29, 2026Jiamei Jiang, Jiajing Zhang, Feifei Mo +2LLM Planning LLM Reliability
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · School of Industry-education Integration, University of Chinese Academy of Sciences, Beijing, China
Towards Reliable and Robust LLM Planning: Symbolic Feedback-Driven Iterative Self-Refinement Framework
Jun 26, 2026Jiajing Zhang, Jiamei Jiang, Chenyang Zhang +3LLM Self-Refinement LLM Planning
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China · School of Industry-education Integration, University of Chinese Academy of Sciences, Beijing, China
When to Plan, When to Polish: Noise Level as a Granularity Axis for Diffusion Language Models
Jun 19, 2026Peihong Li, Yuanjie Shi, Yan YanLLM Planning Diffusion Language Model Decoding
Washington State University
Training the Orchestrator: A Supervised Approach to End-to-End PDDL Planning with LLM Agents
Jun 19, 2026Rajesh Mangannavar, Zachary Coalson, Pranay Dugar +1LLM Planning Symbolic Planning
Oregon State University
OmniV2X: A Generative Foundation Planner for Efficient End-to-End Cooperative Driving
Jun 19, 2026Juntong Peng, Juanwu Lu, Yupeng Zhou +3End-to-End Autonomous Driving LLM Planning
College of Engineering, Purdue University, West Lafayette, IN 47907, USA
Compositional Skill Routing for LLM Agents: Decompose, Retrieve, and Compose
Jun 16, 2026Xueping GaoTool-Augmented Language Model Agents LLM Planning
Alibaba Cloud Hangzhou, China
When in Doubt, Plan It Out: Committed Small Language Model Deliberation for Reactive Reinforcement Learning
Jun 15, 2026Nathan Gavenski, Juarez Monteiro, Francisco Galuppo +2LLM Planning LLM-Guided RL
Department of Informatics, King’s College London, London, United Kingdom · Kunumi Institute, Belo Horizonte, Brazil
SIMMER: Benchmarking Latent Failures in LLM Executable Planning with a World Model
Jun 12, 2026Xiaoxin Lu, Ranran Haoran Zhang, Rui ZhangLarge Language Model-Based Robot Planning LLM Planning
The Pennsylvania State University, State College, PA, USA
A complementary study on PlanGPT: Evaluation with defined Performance Metrics and comparison with a planner
Jun 9, 2026Youssef Abdelkader, Humbert Fiorino, Damien PellierLLM Planning
Univ. Grenoble Alpes - LIG Grenoble, France
SafeRun: Enabling Determinism in LLM Planning for Running
Jun 8, 2026Meilin Chen, Zepeng Zhai, Jiaxuan Zhao +1LLM Planning LLM Safety Evaluation
Xiaohongshu Inc. · Institute of Information Engineering, Chinese Academy of Sciences
Beyond Vector Similarity: A Structural Analysis of Graph-Augmented Retrieval for Industrial Knowledge Graphs
Jun 4, 2026Grama ChethanLLM Reasoning with Graphs LLM Planning
Siemens Digital Industries Software
DiG-Plan: Mitigating Early Commitment for Tool-Graph Planning via Diffusion Guidance
Jun 4, 2026Yansi Li, Zhuosheng ZhangDiffusion-Based Planning LLM Planning
School of Computer Science, Shanghai Jiao Tong University
AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints
Jun 4, 2026Jiayu Liu, Cheng Qian, Zhenhailong Wang +10LLM Planning LLM Agent Evaluation
University of Illinois Urbana-Champaign
Plan, Watch, Recover: A Benchmark and Architectures for Proactive Procedural Assistance
Jun 3, 2026Kaustav Kundu, Ritvik Shrivastava, Maxim Arap +13LLM Planning Egocentric Video Understanding
1Meta Reality Labs · 2Meta Superintelligence Labs
A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners
Jun 2, 2026Patrick Emami, Nan Qiang, Peter GrafSupervised Fine-Tuning LLM Planning
National Laboratory of the Rockies · Epic Systems
SagaQA: A Multi-hop Reasoning Benchmark for Long-form Narrative Understanding in TV Series
Jun 2, 2026Galann Pennec, Zhengyuan Liu, Nicholas Asher +2LLM Planning Multimodal QA
IRIT, University of Toulouse, France · Agency for Science, Technology and Research (A*STAR), Singapore · CNRS, IRIT, France
Robust Asynchronous Planning via Auto-Formalization
May 31, 2026Jiayi Zhang, Jianing Yin, Ben Zhou +1LLM Planning Symbolic Planning
Drexel University · Arizona State University
A Machine-to-Machine Knowledge-Guided LLM Agent for Generalizable Radiotherapy Treatment Planning
May 30, 2026Md Mainul Abrar, Xun Jia, Yujie ChiLLM Planning
Department of Physics, The University of Texas at Arlington, Arlington, 76019, TX · Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD
Efficient Test-time Inference for Generative Planning Models with OCL Search
May 30, 2026Robert Gieselmann, Mihai Samson, Federico Pecora +1Inference-Time Search Efficient Inference
1Amazon · 2Work done while at Amazon.
Planner-Centric Reinforcement Learning for Deep Research with Structure-Aware Reward
May 29, 2026Mustafa Anis Hussain, Xinle Wu, Yao LuDeep Research Agents LLM Planning
National University of Singapore
Knowing What to Solve Before How: Preplan Empowered LLM Mathematical Reasoning
May 28, 2026Shaojie Wang, Liang ZhangLLM Planning Structured Reasoning
Hong Kong University of Science and Technology (Guangzhou)
Self-Improving Language Models with Bidirectional Evolutionary Search
May 27, 2026Guowei Xu, Zhenting Qi, Huangyuan Su +4Evolutionary Optimization LLM Planning
1Harvard University · 2MIT
An LLM-Based Assistance System for Intuitive and Flexible Capability-Based Planning
May 27, 2026Luis Miguel Vieira da Silva, Nicolas König, Felix GehlhoffLLM Planning Symbolic Planning
Institute of Automation Technology, Helmut Schmidt University
Managing Uncertainty in LLM-Generated Procedural Knowledge for Virtual Laboratory Planning
May 25, 2026Polychronis Karpodinis, Dimitris KallesLLM Planning Decision-Making under Uncertainty
School of Science and Technology, Hellenic Open University, Patras 26335, Greece
GroupTravelBench: Benchmarking LLM Agents on Multi-Person Travel Planning
May 24, 2026Xiang Cheng, Yulan Hu, Lulu Zheng +4AI-Assisted Decision Making LLM Planning
Gaoling School of Artificial Intelligence, Renmin University of China · AMAP, Alibaba Group
Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning
May 21, 2026Anjie Qiu, Hans D. SchottenLLM Planning Autonomous Driving Planning
Institute for Wireless Communication and Navigation, RPTU University Kaiserslautern-Landau, Kaiserslautern, Germany · Intelligent Networks Research Group (IN), German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
Efficient Agentic Reasoning Through Self-Regulated Simulative Planning
May 21, 2026Mingkai Deng, Jinyu Hou, Lara Sá Neves +4LLM Planning World Model-Based Planning
Carnegie Mellon University · Institute of Foundation Models (IFM)
Planning in the LLM Era: Building for Reliability and Efficiency
May 21, 2026Michael Katz, Harsha Kokel, Kavitha Srinivas +1LLM Inference Efficiency LLM Planning
IBM Research

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CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs

Qiuyi Qi, Jinjian Zhang, Mutian Bao, Tian Liang+8

Zhejiang University · Ant Group · City University of Hong Kong

RL for Language Models LLM Planning Constrained RL

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Despite their strong reasoning capabilities and extensive world knowledge, Large Language Models (LLMs) frequently generate plans that violate task constraints, undermining their reliability in real-world applications. This deficiency arises from a lack of systematic mechanisms to incorporate constraint information during the generation process. While existing approaches attempt to mitigate this by relying on external tools or task decomposition, they fail to enhance the model's intrinsic constraint awareness. To address this, we propose Constraint-Aware Reinforcement Learning (CARL), a novel RL framework designed to strengthen LLMs' intrinsic focus on constraints. CARL introduces a constraint-aware reward by comparing the model's output distributions under constrained and unconstrained inputs, encouraging constraint focus and penalizing neglect. Compatible with various RL frameworks and requiring no external solvers or top models, CARL enables scalable, end-to-end constraint-aware planning. Extensive experiments on BlocksWorld, TravelPlanner, and T-Eval demonstrate that CARL significantly outperforms standard Reinforcement Fine-Tuning (RFT) baselines and state-of-the-art reasoning models, exhibiting a markedly increased focus on constraints.

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Latest papers 92