ReSearch_SSH shows how specialised research platforms can combine domain adaptation, behavioural retrieval, knowledge graphs, expert evaluation, and legal controls without discarding their existing infrastructure.
A precise operator view shows why attention maps capture token routing but omit the feature transformations that determine what the layer actually computes.
A hidden-state monitor can detect alignment-faking signals, but only after controls separate strategic compliance from prompt identity, query leakage, and configuration artifacts.
PosterHarness shows how to make scientific poster generation auditable by separating visual composition from evidence-bearing figures.
A hierarchical agent architecture sharply reduces tool-schema exposure at scale, but only when taxonomy, validation, and latency controls are engineered with equal care.
MemTools shows why agent-memory evaluation must separate component quality from interface compatibility, execution timing, and representation coordination.
Controlled experiments show that a fact can remain statistically present in an LLM’s weights while becoming inaccessible, unusable, and vulnerable to later updates.
StoryTeller shows why coherent long-form narration depends on verified external state, not only a stronger vision-language model or a longer prompt.
CRISTAL shows why analyst systems may need LLMs for interpretation but explicit probabilistic code for evidence weighting, updating, and final decisions.
A recommender can pass a clean-data fairness review and still develop larger subgroup gaps after coordinated fake profiles enter its retraining data.