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This survey classifies 78 joint OFDM-RIS optimization works into four paradigms, from convex relaxation to foundation models, and identifies open challenges for 6G networks.
This paper introduces an autoresearch paradigm using LLM agents (coding and theory agents) to discover convex relaxations for sharp-constant inequalities, improving certified lower bounds on two optimization constants.
Introduces DisjunctiveNet, a unified end-to-end framework for enforcing hard, input-dependent mixed integer linear constraints within neural networks via differentiable convexified optimization layers, achieving perfect rule satisfaction on real-world datasets.