Time series is a pervasive data type across various application domains, rendering the reasonable solving of diverse time series tasks a long-standing goal. Recent advances in large language models (LLMs), especially their reasoning abilities unlocked through reinforcement learning (RL), have opened new opportunities for tackling tasks with long Chain-of-Thought (CoT) reasoning. However, leveraging LLM reasoning for time series remains in its infancy, hindered by the absence of carefully curated time series CoT data for training, limited data efficiency caused by underexplored data scheduling, and the lack of RL algorithms tailored for exploiting such time series CoT data. In this paper, we introduce VeriTime, a framework that tailors LLMs for time series reasoning through data synthesis, data scheduling, and RL training. First, we propose a data synthesis pipeline that constructs a TS-text multimodal dataset with process-verifiable annotations. Second, we design a data scheduling mechanism that arranges training samples according to a principled hierarchy of difficulty and task taxonomy. Third, we develop a two-stage reinforcement finetuning featuring fine-grained, multi-objective rewards that leverage verifiable process-level CoT data. Extensive experiments show that VeriTime substantially boosts LLM performance across diverse time series reasoning tasks. Notably, it enables compact 3B, 4B models to achieve reasoning capabilities on par with or exceeding those of larger proprietary LLMs.
PTFA: An LLM-based Agent that Facilitates Online Consensus Building through Parallel Thinking
Nagoya Institute of Technology（名古屋技术大学）；University of Southampton（南安普顿大学）；University of Amsterdam（阿姆斯特丹大学）；Japan Advanced Institute of Science and Technology（日本先进科学研究院）
Do Quantum AIs Dream in Paths? Path-Integral Slow Thinking through Grover Interference
Institute of Theoretical Physics, Chinese Academy of Sciences（中国科学院理论物理研究所）；Shenzhen International Quantum Academy（深圳国际量子研究院）；Hefei National Laboratory（合肥国家实验室）
Omni-Thinker: Scaling Multi-Task RL in LLMs with Hybrid Reward and Task Scheduling
Huawei Noah’s Ark Lab, Montréal, Canada（华为诺亚实验室，加拿大蒙特利尔）；McGill University and Mila - Québec AI Institute（麦吉尔大学和魁北克人工智能研究所）；Huawei Noah’s Ark Lab, Beijing, China（华为诺亚实验室，中国北京）
Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles
ByteDance Seed（字节跳动种子）；Fudan University（复旦大学）；Institute for AI Industry Research (AIR), Tsinghua University（人工智能产业研究院（AIR），清华大学）；Nanjing University（南京大学）；Shanghai Jiao Tong University（上海交通大学）；SIA-Lab of Tsinghua AIR and ByteDance Seed（清华大学AIR实验室和字节跳动种子）
Emergent Slow Thinking in LLMs as Inverse Tree Freezing
Hefei National Laboratory, University of Science and Technology of China（中国科学技术大学合肥微尺度物质科学国家实验室）；Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics, University of Science and Technology of China（中国科学技术大学合肥微尺度物质科学国家实验室和现代物理系）；Institute of Theoretical Physics, Chinese Academy of Sciences（中国科学院理论物理研究所）；School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS（杭州高等研究院基础物理与数学科学学院）；DP Technology（DP技术）；Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, Key Laboratory of Quantum Theory and Applications of MoE, Gansu Provincial Research Center for Basic Disciplines of Quantum Physics, Lanzhou University（兰州理论物理中心、甘肃省理论物理重点实验室、教育部量子理论与应用重点实验室、甘肃省量子物理基础学科省重点实验室、兰州大学）；AI for Science Institute, Beijing（北京人工智能科学研究院）
IoT-Brain: Grounding LLMs for Semantic-Spatial Sensor Scheduling
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（合肥综合性国家科学中心人工智能研究院）；The Chinese University of Hong Kong（香港中文大学）；The Hong Kong University of Science and Technology（香港科技大学）
TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
College of Computer Science and Artificial Intelligence, Fudan University（复旦大学计算机科学与人工智能学院）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；School of Artificial Intelligence, Shanghai Jiao Tong University（上海交通大学人工智能学院）
Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
School of Computer Science and Engineering, Beihang University（北京航空航天大学计算机科学与工程学院）；School of Artificial Intelligence, Beihang University（北京航空航天大学人工智能学院）；Huawei（华为）
Correct Answers, Invalid Traces: What Verifiable Grade-School Math Reveals About Chain-of-Thought Traces
IT University of Copenhagen（哥本哈根信息技术大学）；Chennai Mathematical Institute（金奈数学研究所）；Indian Institute of Technology Jammu（印度理工学院贾姆穆分校）；Arizona State University（亚利桑那州立大学）
SMH-Bench: Benchmarking LLM Agents for Environment-Grounded Reasoning and Action in Smart Homes
Midea Group（美的集团）；Beijing University of Posts and Telecommunications（北京邮电大学）；Donghua University（东华大学）；The University of Sydney（悉尼大学）；Peking University（北京大学）
Performative Thinking? The Brittle Correlation Between CoT Length and Problem Complexity
School of Computing and AI（计算与人工智能学院）；Arizona State University（亚利桑那州立大学）；Dept. of Computer Science and Wu Tsai Institute（计算机科学系和吴泰教授研究所）；Yale University（耶鲁大学）
Scheduling Your LLM Reinforcement Learning with Reasoning Trees
Cranberry-Lemon University（Cranberry-Lemon 大学）；University of the Witwatersrand（独立研究者）；Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州））
From Intent to Infrastructure: LLM-Driven Agent Compilers for ISAC Networks
School of Computer Science and Technology, Xidian University（西安电子科技大学计算机科学与技术学院）；Institute of Systems General, Academy of Systems Engineering, Academy of Military Sciences（系统工程院系统一般研究所）
Evaluating and Inducing Personality in Pre-trained Language Models
Institute for Artificial Intelligence, Peking University（北京大学人工智能研究院）；Yuanpei College, Peking University（北京大学元培学院）；National Key Laboratory of General Artificial Intelligence, BIGAI（北京通用人工智能研究院通用人工智能全国重点实验室）；Beijing Jiaotong University（北京交通大学）
University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；University of California, San Diego（加州大学圣地亚哥分校）；Texas A&M University（德克萨斯A&M大学）；Stevens Institute of Technology（史蒂文斯理工学院）
Ask, Relax, or Act? Evaluating Actionable Indeterminacy in LLM Preference Reasoning
The Chinese University of Hong Kong Shenzhen（香港中文大学（深圳））；Beijing University of Posts and Telecommunications（北京邮电大学）；Halmstad University College（哈尔姆斯塔德大学学院）；Tongji University（同济大学）；University of Waterloo（滑铁卢大学）
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；OPPO AI Center, OPPO Inc.（OPPO人工智能中心，OPPO公司）
