feedback-driven

Verilog-Evolve is a feedback-driven framework that iteratively refines Verilog code generated by large language models, using functional simulation, synthesis, and timing metrics to promote better candidates and evolve reusable repair skills across tasks.

The paper proposes FBOS-RL, a feedback-driven bi-objective synergistic reinforcement learning framework that improves training efficiency and performance ceiling over GRPO in LLM alignment and reasoning by using feedback-guided exploration and two mutually reinforcing training objectives: Exploitation-oriented Policy Alignment and Exploration-oriented Capability Cultivation.

FD-NL2SQL is a feedback-driven natural language to SQL system for clinical oncology databases that improves with use through clinician edits and logic-based SQL augmentation. The system decomposes natural language questions into predicates, retrieves expert-verified exemplars, and synthesizes executable SQL with continuous learning capabilities.