RealFeedApp HybridAgents system preserves context without loss
New agents dynamically switch between latent reasoning and text-based interaction while maintaining tool access. The HybridLink architecture enables seamless transitions between modes without losing context.
- Field
- training language models
- What they did
- Developed agents that switch between hidden internal thinking and text-based communication to reduce token usage by 35–55% and speed up inference up to 2.6 times.
- Why it matters
- This enables models to perform tasks faster and more efficiently while maintaining access to external tools and the ability to inspect their hidden reasoning.
#hybrid reasoning#llm agents#token efficiency#latent reasoning#inference speed
