Cognaptus Insights

TriShield shows why federated fine-tuning needs client-side controls over both downloaded adapters and uploaded updates—not just local custody of raw data.

A controlled comparison of agent memory systems shows that retrieving more history can improve factual recall while degrading action selection, making memory a routing decision rather than a universal architecture choice.

D2-ScaleAgent reframes long-document QA as a routing problem: decide whether incomplete evidence requires broader retrieval, deeper inspection, or no more computation.

VeriForge shows that AI products can create value by proactively discovering missing knowledge while leaving synthesis and judgment with the user.

Simulation-driven virtual sensing can extend traffic-data coverage, but its value depends more on preserving behavioral similarity than on maximizing geographic displacement.

HexEval suggests that better scholar assessment comes from separating evidence-backed dimensions and their uncertainty, not from constructing a more comprehensive automated ranking.

Historical specimen records can recover missing place locations by aggregating spatial clues, with probabilistic inference outperforming both hard constraints and GPT-5.1 on fine-scale precision.

LLMs can raise idea quality while narrowing the search space; the practical response is to engineer ideation as a diversified portfolio rather than standardize on one model.

VeinCast shows how scientific ML teams can encode trusted relationships without hard-coding uncertain equations—and make those relationships control how information is actually shared.

Multi-scale EEG improves subject-independent emotion recognition, but the winning time scales, value of adaptive fusion, and compute cost all depend on the task.