Robert Jakob

LLM agents can autonomously optimize RAG pipelines by diagnosing retrieval vs. generation failures, outperforming traditional hyperparameter tuning and achieving Pareto efficiency.

A single time-series language model now masters forecasting, contextual prediction, and temporal reasoning, outperforming specialized models on key benchmarks.

Recursive interaction with time-series data enables TimeRLM to achieve unprecedented accuracy in anomaly localization, outperforming traditional models by a wide margin.

A new deep learning model slashes the error rate for BMI estimation from smartphone photos, opening the door to more accessible and convenient health assessments.