Search results for International Conference on Machine Learning
AI & Enterprise
KAIST develops AI that creates executable plans, from delivery routing to logistics
KAIST said a research team led by computer science professor Minsoo Kim developed a reinforcement-learning technique, RL-SPH, that trains AI to produce plans that satisfy real-world constraints without external optimisation software. The system searches first for a feasible plan and then reduces cost and time while keeping constraints. In benchmark tests it found feasible plans in all cases, improved solution-quality metrics and reduced search and training time versus other AI methods.
AI & Enterprise
KAIST develops red-teaming tech to find 7 times more diverse AI vulnerabilities
Korea Advanced Institute of Science and Technology said it developed a safety verification technology that can uncover about seven times more diverse hidden vulnerabilities in generative AI than existing methods. The team built a new red-teaming framework, Stable-GFlowNet, to verify large language model safety. Tests found 134 unique attack types versus 17 previously, while maintaining a 92 percent attack success rate. The work was selected as an ICML 2026 spotlight paper.
AI & Enterprise
Team Naver showcases AI full-stack technology at ICML 2026
Team Naver said on Sunday it took part in the International Conference on Machine Learning (ICML) 2026, presenting research results ranging from advanced AI models to physical AI. The event was held at Seoul\'s COEX from July 6 to 11. It showcased work across AI safety, model and agent operations, and 3D spatial understanding. Highlights included red-teaming using Stable-GFlowNet, a model-merging method called SyMerge, and a Seoul World Model developed jointly with partners.
