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Undisclosed

Singapore

Posted
20 days ago
Undisclosed

Singapore, Singapore

  • Research on foundation models and frontier generative technologies: Explore the capability boundaries of large language models (LLMs) and multimodal large models (MLLMs), especially the evolution of foundation capabilities for agentic scenarios. Conduct in-depth research and propose innovative post-training paradigms, tackling challenges in complex reasoning such as CoT reasoning and long-horizon planning, tool use, reinforcement learning alignment such as innovative applications of PPO, GRPO, and other new RLHF algorithms for agent behavior alignment, reward model design, and AI safety. Build model capabilities for autonomous decision-making and reflection from the underlying architecture. Explore and break through the underlying architectures of frontier visual generation algorithms such as diffusion and flow matching, building a strong perception and environment simulation foundation for multimodal agents.
  • Frontier breakthroughs in large model agents: Lead underlying algorithmic innovation for Agentic AI. Focus on academic challenges such as agentic reinforcement learning, complex logical reasoning and planning, long-term memory mechanisms, and knowledge injection. Explore the theoretical foundations of emergent multi-agent collaboration and optimal interaction strategies in highly complex, open-ended environments.
  • Forward-looking technical evaluation and theoretical construction: Define and build the evaluation system for next-generation AIGC and agent systems. Identify fundamental problems with core academic value in real-world, large-scale commercial scenarios such as advertising and e-commerce content ecosystems, and design new algorithmic frameworks to address long-tail generalization, interpretability, and multimodal alignment challenges. ...
Posted
20 days ago