We propose a major revision of the format XCSP 2.1, called XCSP3, to build integrated representations of combinatorial constrained problems. This new format is able to deal with mono/multi optimization, many types of variables, cost functions, reification, views, annotations, variable quantification, distributed, probabilistic and qualitative reasoning. The new format is made compact, highly readable, and rather easy to parse. Interestingly, it captures the structure of the problem models, through the possibilities of declaring arrays of variables, and identifying syntactic and semantic groups of constraints. The number of constraints is kept under control by introducing a limited set of basic constraint forms, and producing almost automatically some of their variations through lifting, restriction, sliding, logical combination and relaxation mechanisms. As a result, XCSP3 encompasses practically all constraints that can be found in major constraint solvers developed by the CP community. A website, which is developed conjointly with the format, contains many models and series of instances. The user can make sophisticated queries for selecting instances from very precise criteria. The objective of XCSP3 is to ease the effort required to test and compare different algorithms by providing a common test-bed of combinatorial constrained instances.
Reasoning in a Combinatorial and Constrained World: Benchmarking LLMs on Natural-Language Combinatorial Optimization
Eindhoven University of Technology（埃因霍温理工大学）；Brandenburg University of Technology（勃兰登堡工业大学）；Nanyang Technological University（南洋理工大学）；Delft University of Technology（代尔夫特理工大学）；Southeast University（东南大学）
CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics
Academy of Mathematics and Systems Science, University of Chinese Academy of Sciences（中国科学院数学与系统科学研究院）；Sun Yat-sen University（中山大学）；University of Cambridge（剑桥大学）；East China Normal University（华东师范大学）；Imperial College London（伦敦帝国理工学院）；Stockholm Universitet（斯德哥尔摩大学）；Numina；Moonshot AI
Instance Configuration for Sustainable Job Shop Scheduling
Universitat Politècnica de València（巴塞罗那理工大学）；valgrAI - Valencian Graduate School and Research Network of Artificial Intelligence（瓦伦西亚人工智能研究生学院和研究网络）；Research Network of Artificial Intelligence（人工智能研究网络）
ReFormBench: Benchmarking the Stability of Response-Conditioned Format Correction in Large Language Models
School of Artificial Intelligence, Jilin University（吉林大学人工智能学院）；College of Software, Jilin University（吉林大学软件学院）；Xingchen AGI Lab, China Telecom Artificial Intelligence Technology (Beijing) Co., Ltd（中国电信人工智能技术（北京）有限公司星辰AGI实验室）；BiliBili Inc.（哔哩哔哩股份有限公司）；University of Ottawa（渥太华大学）；Engineering Research Center of Knowledge-Driven Human-Machine Intelligence, Jilin University（吉林大学知识驱动人机智能工程研究中心）；International Center of Future Science, Jilin University（吉林大学未来科学国际中心）
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges
Southern University of Science and Technology（南方科技大学）；Tsinghua University（清华大学）；Peking University（北京大学）；University of Bristol（布里斯托大学）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；Xi’an Jiaotong University（西安交通大学）
StructEval: Benchmarking LLMs' Capabilities to Generate Structural Outputs
University of Waterloo（滑铁卢大学）；University of Toronto（多伦多大学）；HKUST（香港科技大学）；Shanghai University（上海大学）；Independent Contributor（独立贡献者）；Vector Institute（向量研究所）；University of British Columbia（不列颠哥伦比亚大学）
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
Leuphana University（吕贝克大学）；MIT（麻省理工学院）；Southeast University（东南大学）；Peking University（北京大学）；Bielefeld University（比勒菲尔德大学）；Nanyang Technological University（南洋理工大学）；Soochow University（苏州大学）；City University of Hong Kong（香港城市大学）；University of Brescia（布雷西亚大学）；ORTEC（ORTEC公司）；Singapore Management University（新加坡管理学院）；Brandenburg University of Technology（勃兰登堡技术大学）
