The authors define a taxonomy for LLM-enhanced relational operators categorized into Select, Match, Impute, Cluster and Order, and release LROBench to evaluate single and multi-operator queries on semantic database processing.
Biometrika30(1-2), 81–93 (1938)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
AICON, a gradient-descent reactive model from robotics, reproduces human difficulty orderings on the Tower of London test and outperforms planning models for impaired clinical groups while underperforming for healthy controls.
citing papers explorer
-
Large Language Model-Enhanced Relational Operators: Taxonomy, Benchmark, and Analysis
The authors define a taxonomy for LLM-enhanced relational operators categorized into Select, Match, Impute, Cluster and Order, and release LROBench to evaluate single and multi-operator queries on semantic database processing.
-
No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical Task
AICON, a gradient-descent reactive model from robotics, reproduces human difficulty orderings on the Tower of London test and outperforms planning models for impaired clinical groups while underperforming for healthy controls.