4 papers
Competing at Every Price Point with Agentic Evolution over a Menu of LLMs
Andrew Borthwick
Consider a firm that surveys its competition for a particular agentic task and seeks to offer superior accuracy at every price point. A firm that Pareto-dominated its competitors w…
RoboPhD: Evolving Diverse Complex Agents Under Tight Evaluation Budgets
Andrew Borthwick, Stephen Ash, Anthony Galczak
2026 has brought an explosion of interest in LLM-guided evolution of agentic artifacts, with systems like GEPA and Autoresearch demonstrating that LLMs can iteratively improve prom…
RoboPhD: Self-Improving Text-to-SQL Through Autonomous Agent Evolution
Andrew Borthwick, Stephen Ash
We present RoboPhD, a system where AI agents autonomously conduct research to improve Text-to-SQL performance. RoboPhD implements a closed-loop evolution cycle with two coordinated…
Scalable Blocking for Very Large Databases
Andrew Borthwick, Stephen Ash, Bin Pang +2
In the field of database deduplication, the goal is to find approximately matching records within a database. Blocking is a typical stage in this process that involves cheaply find…