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20232026
most citedLarge Language Model for Multi-objective Evolutionary Optimization

21 citations · 62 across the 17 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

Understanding Evolution Strategies for LLM Reasoning: Broader Reasoning Coverage than GRPO

Yunpeng Ba, Zhi Zheng, Yue Xie +7

Evolution Strategies (ES) have recently emerged as a memory-efficient post-training paradigm for LLM reasoning. However, the optimization behavior of ES remains understudied, makin…

cs.LG2025

Multimodal LLM-assisted Evolutionary Search for Programmatic Control Policies

Qinglong Hu, Xialiang Tong, Mingxuan Yuan +3

Deep reinforcement learning has achieved impressive success in control tasks. However, its policies, represented as opaque neural networks, are often difficult for humans to unders…

cs.LG2024★ 2 cited

A Systematic Survey on Large Language Models for Algorithm Design

Fei Liu, Yiming Yao, Ping Guo +9

Algorithm design is crucial for effective problem-solving across various domains. The advent of Large Language Models (LLMs) has notably enhanced the automation and innovation with…

cs.LG2024

DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems

Zhi Zheng, Shunyu Yao, Zhenkun Wang +3

The min-max vehicle routing problem (min-max VRP) traverses all given customers by assigning several routes and aims to minimize the length of the longest route. Recently, reinforc…

cs.LG2024

Prompt Learning for Generalized Vehicle Routing

Fei Liu, Xi Lin, Weiduo Liao +4

Neural combinatorial optimization (NCO) is a promising learning-based approach to solving various vehicle routing problems without much manual algorithm design. However, the curren…

cs.LG2024★ 2 cited

Self-Improved Learning for Scalable Neural Combinatorial Optimization

Fu Luo, Xi Lin, Zhenkun Wang +3

The end-to-end neural combinatorial optimization (NCO) method shows promising performance in solving complex combinatorial optimization problems without the need for expert design.…

cs.LG2024★ 2 cited

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization

Fei Liu, Xi Lin, Zhenkun Wang +3

Vehicle routing problems (VRPs), which can be found in numerous real-world applications, have been an important research topic for several decades. Recently, the neural combinatori…