The test-time compute strategy, such as Chain-of-Thought (CoT), has significantly enhanced the ability of large language models to solve complex tasks like logical reasoning. However, empirical studies indicate that simply increasing the compute budget can sometimes lead to a collapse in test-time performance when employing typical task decomposition strategies such as CoT. This work hypothesizes that reasoning failures with larger compute budgets stem from static planning methods, which hardly perceive the intrinsic boundaries of LLM reasoning. We term it as the Limited Reasoning Space hypothesis and perform theoretical analysis through the lens of a non-autonomous stochastic dynamical system. This insight suggests that there is an optimal range for compute budgets; over-planning can lead to redundant feedback and may even impair reasoning capabilities. To exploit the compute-scaling benefits and suppress over-planning, this work proposes Halo, a model predictive control framework for LLM planning. Halo is designed for long-horizon tasks with reason-based planning and crafts an entropy-driven dual controller, which adopts a Measure-then-Plan strategy to achieve controllable reasoning. Experimental results demonstrate that Halo outperforms static baselines on complex long-horizon tasks by dynamically regulating planning at the reasoning boundary.
V-CAGE: Context-Aware Generation and Verification for Scalable Long-Horizon Embodied Tasks
Department of Computer Science and Technology, University of Cambridge, Cambridge, England.（计算机科学与技术系，剑桥大学，剑桥，英格兰）；Shanghai Jiao Tong University, Shanghai, China（上海交通大学，上海，中国）；Wuhan University, Wuhan, Hubei, China（武汉大学，武汉，湖北，中国）
HeroBench: A Benchmark for Long-Horizon Planning and Structured Reasoning in Virtual Worlds
Artyom Sorokin（AXXX）；Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学）；Higher School of Economics（高等经济学院）；Kurchatov Institute（库尔斯克研究所）；Independent Researcher（独立研究者）
ActiveMem: Distributed Active Memory for Long-Horizon LLM Reasoning
State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所人工智能安全国家重点实验室）；University of Chinese Academy of Sciences（中国科学院大学）
SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks
Southern University of Science and Technology（南方科技大学）；INFLY TECH；Beijing University of Posts and Telecommunications（北京邮电大学）；Microsoft Research Asia（微软亚洲研究院）；Shanghai University of Finance and Economics（上海财经大学）；Tsinghua University（清华大学）
HyMem: Hierarchical Context Management for Long-Horizon Agents via Information Isolation
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Nanjing Artificial Intelligence Research of IA（IA南京人工智能研究院）
From Perception to Planning: Evolving Ego-Centric Task-Oriented Spatiotemporal Reasoning via Curriculum Learning
Zhejiang University（浙江大学）；Tianjin University（天津大学）；Qingdao University（青岛大学）；Shanghai Jiao Tong University（上海交通大学）；National University of Singapore（新加坡国立大学）
QART: A Quantum-Classical Hybrid Architecture for Long-Horizon Reasoning -- Exploring a Conditional Path toward Quantum Scaling
QuantumMind（量子心智）；Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳市人工智能与机器人研究院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Institute of Data Economy（深圳数据经济研究院）；Nanyang Technological University（南洋理工大学）；The Hong Kong Polytechnic University（香港理工大学）
SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning
School of artificial intelligence, Wuhan University（武汉大学人工智能学院）；School of computer science, Shanghai Jiao Tong University（上海交通大学计算机科学与工程学院）；Institute of automation, Chinese Academy of Sciences（中国科学院自动化研究所）
Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents
University of Notre Dame（诺丁汉大学）；Stanford University（斯坦福大学）；Purdue University（普渡大学）；University of Edinburgh（爱丁堡大学）；University of Oxford（牛津大学）；Yale University（耶鲁大学）
Recurrent Reasoning with Vision-Language Models for Estimating Long-Horizon Embodied Task Progress
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学北京校区人工智能学院）；Beijing Key Laboratory of Research on Large Models and Intelligent Governance（北京大型模型与智能治理研究重点实验室）；Engineering Research Center of Next-Generation Intelligent Search and Recommendation, MOE（教育部下一代智能搜索与推荐工程研究中心）；Department of Computer Science and Technology, Tsinghua University（清华大学计算机科学与技术系）；Institute for AI Industry Research (AIR), Tsinghua University（清华大学人工智能产业研究院）
Towards Long-Horizon Vessel Trajectory and Destination Forecasting with Reasoning Large Language Models
Institute of High Performance Computing (IHPC), A*STAR, Singapore（新加坡科技研究局高性能计算研究所）；The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University（同济大学道路与交通工程教育部重点实验室）；Meituan Inc., Shenzhen, China（美团（深圳））；Centre for Frontier AI Research (CFAR), A*STAR, Singapore（新加坡科技研究局前沿人工智能研究中心）；Nankai University（南开大学）；School of Artificial Intelligence, Jilin University（吉林大学人工智能学院）
MedClaw: Heuristic Agent Harness for Long-Horizon Surgical Video Reasoning
School of Automation and Intelligence, Beijing Jiaotong University（北京交通大学自动化与智能学院）；University of Maryland（马里兰大学）；Suzhou Institute for Advanced Research, University of Science and Technology of China（中国科学技术大学苏州高等研究院）；University of British Columbia（不列颠哥伦比亚大学）；Beijing Tiantan Hospital, Capital Medical University（首都医科大学附属北京天坛医院）
LongSpace: Exploring Long-Horizon Spatial Memory from Perception to Recall in Video
Beijing University of Posts and Telecommunications（北京邮电大学）；Zhongguancun Academy（中关村学院）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；The Chinese University of Hong Kong（香港中文大学）；Xi’an Jiaotong University（西安交通大学）
