LLM Based
Large language model (LLM)-based systems are rapidly advancing, aiming to improve efficiency and accuracy across diverse applications. Current research focuses on optimizing LLM performance through techniques like multi-agent systems, adaptive reward model selection (e.g., using multi-armed bandits), and integrating LLMs with symbolic methods for enhanced reasoning and planning capabilities. This work is significant because it addresses limitations of existing LLMs, such as inconsistency, hallucination, and computational cost, leading to more robust and reliable AI systems for various domains including healthcare, robotics, and software engineering.
170papers
Papers
May 6, 2025
Divide, Optimize, Merge: Fine-Grained LLM Agent Optimization at Scale
Jiale Liu, Yifan Zeng, Shaokun Zhang, Chi Zhang, Malte Højmark-Bertelsen, Marie Normann Gadeberg, Huazheng Wang, Qingyun WuPennsylvania State University●Oregon State University●The University of Texas at Austin●Beyond WorkScientific Hypothesis Generation and Validation: Methods, Datasets, and Future Directions
Adithya Kulkarni, Fatimah Alotaibi, Xinyue Zeng, Longfeng Wu, Tong Zeng, Barry Menglong Yao, Minqian Liu, Shuaicheng Zhang, Lifu Huang, Dawei ZhouVirginia Tech●Davis
May 1, 2025
The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)
Zihao Wang, Yibo Jiang, Jiahao Yu, Heqing HuangUniversity of Chicago●Northwestern University●ByteDance Inc.Urban Air Mobility as a System of Systems: An LLM-Enhanced Holonic Approach
Ahmed R. Sadik, Muhammad Ashfaq, Niko Mäkitalo, Tommi MikkonenHonda Research Institute Europe●University of Jyväskylä
April 28, 2025
BLADE: Benchmark suite for LLM-driven Automated Design and Evolution of iterative optimisation heuristics
Niki van Stein, Anna V. Kononova, Haoran Yin, Thomas BäckLeiden UniversityFrom LLM Reasoning to Autonomous AI Agents: A Comprehensive Review
Mohamed Amine Ferrag, Norbert Tihanyi, Merouane DebbahGuelma University●Technology Innovation Institute●E¨otv¨os Lor ´and University●Khalifa University of Science and TechnologyFitness Landscape of Large Language Model-Assisted Automated Algorithm Search
Fei Liu, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan, Kun MaoCity University of Hong Kong●HUAWEI Noah’s Ark Lab●Huawei Cloud EI Service Product DepartmentEvolution of Cooperation in LLM-Agent Societies: A Preliminary Study Using Different Punishment Strategies
Kavindu Warnakulasuriya, Prabhash Dissanayake, Navindu De Silva, Stephen Cranefield, Bastin Tony Roy Savarimuthu, Surangika Ranathunga+1University of Moratuwa●University of Otago●Massey University
April 24, 2025
Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
Isadora White, Kolby Nottingham, Ayush Maniar, Max Robinson, Hansen Lillemark, Mehul Maheshwari, Lianhui Qin, Prithviraj AmmanabroluUniversity of California●Latitude Games●Emergent GardenExploring Context-aware and LLM-driven Locomotion for Immersive Virtual Reality
Süleyman Özdel, Kadir Burak Buldu, Enkelejda Kasneci, Efe BozkirTechnical University of MunichPaper2Code: Automating Code Generation from Scientific Papers in Machine Learning
Minju Seo, Jinheon Baek, Seongyun Lee, Sung Ju HwangKAIST●DeepAuto.ai