Research
Two main threads: efficient diffusion language models, and neuro-symbolic AI for scientific discovery.
Efficient Inference for Diffusion Language Models
Goal. Reduce the inference cost of diffusion-based LLMs for language generation.
Strategies
- Reduce the number of diffusion iterations via distillation.
- Develop a sparse attention mechanism for long-sequence generation.
Neuro-Symbolic AI for Scientific Discovery
Goal. Accelerate the discovery of physical knowledge from experimental data.
Strategies
- Design control-variable experiments.
- Perform active data querying guided by phase portraits.
- Learn a symbolic-equivalence–aware objective.
Related: see the Genesis Mission for context on AI-driven scientific discovery.