R / 01 / Active programme
Model capability must survive contact with the workload.
We develop and study model architectures, adaptation, inference, and task-level evaluation as one system. The aim is not an isolated benchmark result, but useful behaviour within an explicit quality, latency, cost, and deployment envelope.
Research question
How can model capability remain useful, measurable, and economical inside the system that must operate it?
Workstreams
The programme is worked as a system.
Architectures & representations
Study model structures and representations against the capability and deployment boundary of a defined workload.
Adaptation & post-training
Investigate data, supervision, preference, and domain-adaptation methods without losing visibility into behavioural trade-offs.
Inference systems
Treat routing, quantization, serving, latency, memory, and cost as part of model behaviour rather than downstream plumbing.
Evaluation science
Build task-level suites that expose failure distributions, regressions, uncertainty, and the effect of system context.
Evidence gate
What would move the claim forward?
Research maturity advances through named evidence, not through the passage of time or the confidence of the presentation.
- 01Workload suite and baseline
- 02Ablation and regression results
- 03Quality, latency, and cost envelope
- 04Documented failure distribution
Current boundary
The limit is part of the result.
This programme describes an active research direction. It does not imply that a public foundation model or production model service has been released.