BloomWise: Enhancing Problem-Solving capabilities of Large Language Models using Bloom's-Taxonomy-Inspired Prompts
Speech and Language Processing Group, National Technical University of Athens（国家技术大学雅典语音与语言处理组）；Institute for Language and Speech Processing, Athena Research Center（雅典研究中心语言与语音处理研究所）；National Technical University of Athens（国家技术大学雅典）
Despite the remarkable capabilities of large language models (LLMs) across a range of tasks, mathematical reasoning remains a challenging frontier. Motivated by the observation that humans learn more effectively when prompted not what to think but how to think, we introduce BloomWise, a cognitively-inspired prompting technique designed to enhance LLMs' performance on mathematical problem solving while making their solutions more explainable. BloomWise encourages LLMs to generate solutions - in the form of explanations - by progressing through a sequence of cognitive operations-from basic (e.g., remembering) to more advanced reasoning skills (e.g., evaluating) - mirroring how humans build understanding. The process iterates through these levels, halting early if a convergence criterion is met: specifically, if two or more consecutive levels yield the same answer, the solution from the earliest such level is output; otherwise, the process continues until all levels are completed. Through extensive experiments across five popular math reasoning datasets, we demonstrate the effectiveness of BloomWise. We also present comprehensive ablation studies to analyze the strengths of each component within our system.
Classification of Questions and Learning Outcome Statements (LOS) Into Blooms Taxonomy (BT) By Similarity Measurements Towards Extracting Of Learning Outcome from Learning Material
Al-Quds Open University（圣城开放大学）；Al-Quds University（圣城大学）
CogRAG: Tackling Heterogeneous Cognitive Demands in RAG via Stratified Retrieval and Reasoning
School of Computer and Computing Science, Hangzhou City University（杭州城市大学计算机与计算科学学院）；Innovation Center of Yangtze River Delta, Zhejiang University（长三角创新中心，浙江大学）；Institute of Digital Twin, Eastern Institute of Technology（数字孪生研究院，东部技术研究院）
OpenLearnLM Benchmark: A Unified Framework for Evaluating Knowledge, Skill, and Attitude in Educational Large Language Models
Chosun University（chosun大学）；Korea University（韩国大学）；Ewha Womans University（成均馆大学）；Korea Institute for Curriculum and Evaluation（韩国课程评价院）；Seoul National University（首尔国立大学）；Texas A&M University（德克萨斯农工大学）；Indiana University Bloomington（印第安纳大学布卢明顿分校）
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models
Singapore Management University（新加坡管理大学）；Fudan University（复旦大学）；Tsinghua University（清华大学）；Beijing Institute of Technology（北京理工大学）；University of Science and Technology of China（中国科学技术大学）；University of Georgia（佐治亚大学）；Skywork AI（天工智芯（Skywork AI））
HelloBench: Evaluating Long Text Generation Capabilities of Large Language Models
Beihang University（北京航空航天大学）；Shanghai AI Laboratory（上海人工智能实验室）；Peking University（北京大学）；M-A-P；University of Chinese Academy of Sciences（中国科学院大学）；Nanjing University（南京大学）
Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment
School of Architecture and Urban Planning, Shenzhen University（深圳大学建筑与城市规划学院）；Shenzhen Key Laboratory of Urban Spatial Information and Intelligent Modeling（深圳市城市空间信息与智能建模重点实验室）；Department of Urban Planning and Design, The University of Hong Kong（香港大学城市规划与设计系）
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Department of Electronic Engineering, Tsinghua University, Beijing, China（清华大学电子工程系）；College of AI, Tsinghua University, Beijing, China（清华大学人工智能学院）；School of Computer Science, Beijing University of Posts and Telecommunications, Beijing, China（北京邮电大学计算机科学学院）；iFLYTEK Research, Hefei, China（iFLYTEK研究院）
Almieyar-Oryx-BloomBench: A Bilingual Multimodal Benchmark for Cognitively Informed Evaluation of Vision-Language Models
University of British Columbia（不列颠哥伦比亚大学）；Zuse School（Zuse学校）；Qatar Computing Research Institute (QCRI)（卡塔尔计算研究所）；Hamad Bin Khalifa University（哈马德·本·哈利法大学）
An Evaluation of the Pedagogical Soundness and Usability of AI-Generated Lesson Plans Across Different Models and Prompt Frameworks in High-School Physics
CogTax: A Four-Level Cognitive Taxonomy for Command-Line Computing Education
Universidade de Vigo（维戈大学）；IFCAE-Instituto de Investigación en Física, Computación y Ciencia Aeroespacial, Universidade de Vigo（IFCAE-维戈大学物理、计算与航空航天科学研究所）；Computer Science Department, IFCAE-Instituto de Investigación en Física, Computación y Ciencia Aeroespacial, Universidade de Vigo（维戈大学IFCAE物理、计算与航空航天科学研究所计算机科学系）；Universidade de Vigo, Department of Computer Science, ESEI-Escuela Superior de Ingeniería Informática（维戈大学计算机科学系ESEI高等信息工程学院）
