collaborators

6 papers

cs.CR2026

SynthGuard-ReleaseBench: Locked-Audit Evidence for Synthetic Tabular Data Releases

Jeffery Opoku, David Banahene

Synthetic tabular data are often judged by realism, privacy, or downstream-task scores. Those scores do not answer whether a proposed release is supported for a named use, populati…

stat.ML2026

Signed Evidence Flow: Conflict-Aware and Stability-Calibrated Data Analysis

Jeffery Opoku, David Banahene

Modern data analysis usually gives a prediction without showing whether the evidence behind it is clear, conflicting, or stable. Two cases can have the same fitted confidence even…

stat.ML2026

ToolChain-CRC: Conformal Risk Control for Agentic AI Under Retrieval and Tool-Use Drift

Jeffery Opoku, David Banahene

Modern AI agents retrieve documents, call tools, check intermediate information, and then produce a final answer or action. This creates a risk-control problem that is not visible…

stat.ML2026

PromptShift-CRC: Drift-Aware Conformal Risk Control for Foundation Models Under Prompt and Domain Shift

Jeffery Opoku, David Banahene

Foundation models are now used in settings where the prompts they receive can change quickly. Users change, topics change, policies change, and the model may suddenly face a kind o…

stat.ME2026

Drift-Aware Spectral Conformal Prediction for Non-Exchangeable Streaming Data

Jeffery Opoku, David Banahene

Conformal prediction provides distribution-free prediction intervals under exchangeability, but many modern data streams are neither independent nor stable. They exhibit recurring…

stat.ML2026

Spectral Adaptive Conformal Prediction for Structured Non-Exchangeable Data

Jeffery Opoku, David Banahene

Conformal prediction gives prediction intervals with finite-sample coverage when the data are exchangeable. Many time-indexed datasets are not exchangeable: they have seasons, recu…