Thought leadership in AI safety and responsible AI development
The first large-scale safety dataset with 99.5% multi-dimensional annotation coverage across 8 ethical dimensions, enabling measurable improvements in AI safety and responsible behavior.
Understanding the 8 dimensions of RAIL Score: Fairness, Safety, Reliability, Transparency, Privacy, Accountability, Inclusivity, and User Impact (each 0-10 with confidence 0-1).
How gradient surgery, safety-aware probing, and token-level weighting preserve AI safety during model customization.
Comprehensive guide to evaluating LLMs including HELM, HuggingFace datasets, and the RAIL-HH-10K dataset.
Full research paper detailing the methodology, evaluation framework, and empirical results of RAIL Score across 10k+ real-world AI interactions. Published on arXiv.
Our research focuses on multidimensional safety evaluation (8 dimensions), safety datasets, and advanced alignment techniques.