Large-scale Chinese spelling correction (CSC) remains critical for real-world text processing, yet existing LLMs and supervised methods lack robustness to novel errors and rely on costly annotations. We introduce CEC-Zero, a zero-supervision reinforcement learning framework that addresses this by enabling LLMs to correct their own mistakes. CEC-Zero synthesizes errorful inputs from clean text, computes cluster-consensus rewards via semantic similarity and candidate agreement, and optimizes the policy with PPO. It outperforms supervised baselines by 10--13 F$_1$ points and strong LLM fine-tunes by 5--8 points across 9 benchmarks, with theoretical guarantees of unbiased rewards and convergence. CEC-Zero establishes a label-free paradigm for robust, scalable CSC, unlocking LLM potential in noisy text pipelines.
Better Process Supervision with Bi-directional Rewarding Signals
School of Computer Science, Fudan University（复旦大学计算机科学学院）；Cognitive AI Lab, Shanghai Huawei Technologies（华为技术有限公司上海认知人工智能实验室）；Institute of Modern Languages and Linguistics, Fudan University（复旦大学现代语言与语言学研究所）
Rewarding Novel Deductions: Solver-guided Process Supervision for Logical Reasoning
Information Technology University（信息技术大学）；Huazhong Agricultural University（华中农业大学）；Qatar Computing Research Institute, Hamad Bin Khalifa University（卡塔尔计算研究所，哈马德·本·哈利法大学）
Enhancing Agentic Textual Graph Retrieval with Synthetic Stepwise Supervision
Institute for AI Industry Research (AIR), Tsinghua University（人工智能产业研究院（AIR），清华大学）；Peking University（北京大学）；School of Information, Renmin University of China（中国人民大学信息学院）；Harbin Institute of Technology（哈尔滨工业大学）；North China Electric Power University（华北电力大学）；GDS Holdings Limited（GDS控股有限公司）
VRPO: Rethinking Value Modeling for Robust RL under Noisy Supervision in LLM Post-Training
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）；Honor Device Co., Ltd（荣耀设备有限公司）；Institute of Trustworthy Embodied AI, Fudan University（复旦大学可信具身人工智能研究院）；Shanghai Key Laboratory of Multimodal Embodied AI（上海多模态具身人工智能重点实验室）
Rewarding Beliefs, Not Actions: Consistency-Guided Credit Assignment for Long-Horizon Agents
College of Computer, National University of Defense Technology（国防科技大学计算机学院）；Intelligent Game and Decision Lab (IGDL)（智能游戏与决策实验室）；Institute of Artificial Intelligence, Xiamen University（厦门大学人工智能研究院）
LogicReward: Incentivizing LLM Reasoning via Step-Wise Logical Supervision
National University of Singapore（新加坡国立大学）；University College London（伦敦大学学院）；University of Manchester（曼彻斯特大学）；University of Melbourne（墨尔本大学）；University of California, Santa Barbara（加州大学圣巴巴拉分校）
FARCA: Fact-Aligned Reliability-Aware Credit Assignment for Reinforcement Learning with Factual Supervision
School of Computer Science and Engineering, Nanjing University of Science and Technology（南京理工大学计算机科学与工程学院）；School of Intelligence Science and Technology, Nanjing University（南京大学智能科学与技术学院）
Two is better than one: A Collapse-free Multi-Reward RLIF Training Framework
Bangladesh University of Engineering and Technology（孟加拉工程科技大学）；West Virginia University（西弗吉尼亚大学）；University of Aberdeen（阿伯丁大学）；Fogsphere (Redev.AI Ltd, UK)（Fogsphere（Redev.AI Ltd，英国））；University College London（伦敦大学学院）
An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
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）
Instructions are all you need: Self-supervised Reinforcement Learning for Instruction Following
Shanghai Key Laboratory of Data Science, College of Computer Science and Artificial Intelligence, Fudan University（上海数据科学 key laboratory，复旦大学计算机科学与人工智能学院）；School of Data Science, Fudan University（复旦大学数据科学学院）；Ant Group（蚂蚁集团）
Cheems: A Practical Guidance for Building and Evaluating Chinese Reward Models from Scratch
Chinese Information Processing Laboratory, Institute of Software, Chinese Academy of Sciences（中国科学院软件研究所信息处理实验室）；University of Chinese Academy of Sciences（中国科学院大学）
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
School of Computer Science, Fudan University（复旦大学计算机科学学院）；ByteDance Research（字节跳动研究部）；Institute of Modern Languages and Linguistics, Fudan University（复旦大学现代语言与语言学研究所）
KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；State Key Laboratory of AI Safety（人工智能安全国家重点实验室）；School of Computer Science, University of Chinese Academy of Sciences（中国科学院大学计算机科学学院）
SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards
Gaoling School of Artificial Intelligence, Renmin University of China（中国人民大学人工智能学院）；School of Computer Science（计算机科学学院）；Baidu Inc.（百度公司）；School of Computer Science, Wuhan University（武汉大学计算机学院）
