Author

M. Habib

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Preprint Aug 2026

ORACLE: A Multi-Objective Reinforcement Learning-Based Analog Circuit Design Optimizer with Large Language Models-Guided Exploration

ORACLE is an open-source RL-based framework for MO analog circuit design optimization that replaces scalar reward optimization with vector-valued learning and preference-aware conditioning, and incorporates a large language model (LLM)-guided action selection mechanism to filter actions that are likely to lead to subop...

Osei Brempong, M. Habib, V. Poddar et al. · 1 citation

Preprint Aug 2026

AaLLM: An End-to-End Analog Circuit Design Framework from Topology Generation to Sizing Using Large Language Models

An open-source end-to-end multi-agent LLM workflow that takes user specs as input and outputs the appropriate netlist, encompassing both topology generation and circuit sizing, and achieves a figure of merit (FoM) comparable to that of known topologies, and up to 3x higher for certain circuits.

M. Habib, R. Hart, Morteza Fayazi · 0 citations