:: Library Catalog

Saved in:

Bibliographic Details
Main Authors:	Zhu, Rongjie, Zhang, Cong, Cao, Zhiguang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.11121
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
by: Zhang, Cong, et al.
Published: (2022)

Learning to Search for Vehicle Routing with Multiple Time Windows
by: Xu, Kuan, et al.
Published: (2025)

Diversity Optimization for Travelling Salesman Problem via Deep Reinforcement Learning
by: Li, Qi, et al.
Published: (2025)

Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
by: Zhang, Cong, et al.
Published: (2024)

RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
by: Xiao, Xiangjie, et al.
Published: (2026)

Efficient Reinforcement Finetuning via Adaptive Curriculum Learning
by: Shi, Taiwei, et al.
Published: (2025)

Beyond Parameter Finetuning: Test-Time Representation Refinement for Node Classification
by: Zhang, Jiaxin, et al.
Published: (2026)

ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning
by: Guo, Hongshu, et al.
Published: (2024)

Representation Finetuning for Continual Learning
by: Luo, Haihua, et al.
Published: (2026)

Learning Dynamics of LLM Finetuning
by: Ren, Yi, et al.
Published: (2024)

Enhancing the Cross-Size Generalization for Solving Vehicle Routing Problems via Continual Learning
by: Li, Jingwen, et al.
Published: (2025)

Towards Fast Safe Online Reinforcement Learning via Policy Finetuning
by: Chen, Keru, et al.
Published: (2024)

Holdout-Loss-Based Data Selection for LLM Finetuning via In-Context Learning
by: Zhang, Ling, et al.
Published: (2025)

Bias-Restrained Prefix Representation Finetuning for Mathematical Reasoning
by: Liang, Sirui, et al.
Published: (2025)

When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
by: Zhang, Biao, et al.
Published: (2024)

Reinforcement Learning Finetunes Small Subnetworks in Large Language Models
by: Mukherjee, Sagnik, et al.
Published: (2025)

Invisible Safety Threat: Malicious Finetuning for LLM via Steganography
by: Wan, Guangnian, et al.
Published: (2026)

Mechanical Strength Prediction of Steel-Polypropylene Fiber-based High-Performance Concrete Using Hybrid Machine Learning Algorithms
by: Chakma, Jagaran, et al.
Published: (2025)

Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations
by: Huang, Han, et al.
Published: (2024)

Tree Search for LLM Agent Reinforcement Learning
by: Ji, Yuxiang, et al.
Published: (2025)

Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
by: Zhu, Jianghan, et al.
Published: (2025)

Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers
by: Yan, Kai, et al.
Published: (2024)

Learning Dynamics of VLM Finetuning
by: Zhang, Jusheng, et al.
Published: (2025)

NCO4CVRP: Neural Combinatorial Optimization for the Capacitated Vehicle Routing Problem
by: Dihan, Mahir Labib, et al.
Published: (2026)

CARE-RFT: Confidence-Anchored Reinforcement Finetuning for Reliable Reasoning in Large Language Models
by: Li, Shuozhe, et al.
Published: (2026)

MLE-STAR: Machine Learning Engineering Agent via Search and Targeted Refinement
by: Nam, Jaehyun, et al.
Published: (2025)

RADAR: Learning to Route with Asymmetry-aware DistAnce Representations
by: Yi, Hang, et al.
Published: (2026)

Shape it Up! Restoring LLM Safety during Finetuning
by: Peng, ShengYun, et al.
Published: (2025)

Stratified GRPO: Handling Structural Heterogeneity in Reinforcement Learning of LLM Search Agents
by: Zhu, Mingkang, et al.
Published: (2025)

Refining Few-Step Text-to-Multiview Diffusion via Reinforcement Learning
by: Zhang, Ziyi, et al.
Published: (2025)

Search over Self-Edit Strategies for LLM Adaptation
by: Cheong, Alistair, et al.
Published: (2026)

TreeRL: LLM Reinforcement Learning with On-Policy Tree Search
by: Hou, Zhenyu, et al.
Published: (2025)

Stable Continual Reinforcement Learning via Diffusion-based Trajectory Replay
by: Chen, Feng, et al.
Published: (2024)

ABG-NAS: Adaptive Bayesian Genetic Neural Architecture Search for Graph Representation Learning
by: Wang, Sixuan, et al.
Published: (2025)

Iterative Refinement of Flow Policies in Probability Space for Online Reinforcement Learning
by: Sun, Mingyang, et al.
Published: (2025)

Vanishing Gradients in Reinforcement Finetuning of Language Models
by: Razin, Noam, et al.
Published: (2023)

Adversarial Generative Flow Network for Solving Vehicle Routing Problems
by: Zhang, Ni, et al.
Published: (2025)

Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
by: Nguyen, Manh, et al.
Published: (2025)

LLM-Inspired Pretrain-Then-Finetune for Small-Data, Large-Scale Optimization
by: Zhang, Zishi, et al.
Published: (2026)

LLM-NAS: LLM-driven Hardware-Aware Neural Architecture Search
by: Zhu, Hengyi, et al.
Published: (2025)