SingaX Team Places Second at NeurIPS 2025 EAI Challenge

The SingaX team, comprising researchers from NUS Computing, A*STAR, and NTU, has placed second at the Embodied Agent Interface (EAI) Challenge at NeurIPS 2025, developing a method that improves AI performance by learning from past errors – without additional model training.

Competing against 48 international teams, the team achieved an average score of 84.32, ranking among the top performers in the challenge.

The competition focused on developing embodied, agentic systems capable of interpreting natural language instructions and executing complex tasks in simulated environments. These systems must reason over long-horizon instructions, track intermediate states, and generate executable action sequences – challenges where existing approaches can fall short due to brittle prompt design and inconsistent outputs.

SingaX proposed an iterative prompt induction framework that analyses failure patterns during development and refines task instructions accordingly. This approach improves performance on new tasks without requiring additional model training, and offers a cost-efficient method applicable across different evaluation settings.

Team members include A*STAR Computing and Information Science (ACIS) Scholars: Niu Xinyuan and Chen Zhiliang (both NUS Computing PhD students in Computer Science), as well as Vernon Toh (NTU) and Li Yanchao (NTU).

Congratulations to the team on this achievement!

More information:
https://foundation-models-meet-embodied-agents.github.io/eai_challenge/#winners