13 citations · 15 across the 12 of their papers we have counts for
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cs.LG2026
LLMs as Adaptive Meta-Solvers: Strategy-Diverse RL for Industrial-Scale Optimization
Shihao Zhang, Weiting Liu, Siyu Shao +4
Scaling LLM-based optimization from textbook-scale instances to real-world, industrial tasks remains a critical open challenge. Existing approaches are predominantly evaluated on s…
cs.LG2026
Automated Optimization Modeling via a Localizable Error-Driven Perspective
Weiting Liu, Han Wu, Yufei Kuang +4
Automated optimization modeling via Large Language Models (LLMs) has emerged as a promising approach to assist complex human decision-making. While post-training has become a pivot…
cs.LG2025
Stochastic Forward-Forward Learning through Representational Dimensionality Compression
Zhichao Zhu, Yang Qi, Hengyuan Ma +2
The Forward-Forward (FF) learning algorithm provides a bottom-up alternative to backpropagation (BP) for training neural networks, relying on a layer-wise "goodness" function with…