Step-Opt: Boosting Optimization Modeling in LLMs through Iterative Data Synthesis and Structured Validation
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Yang, Zhang, Yifan, Wu, Yurong, Wang, Yuran, Zhang, Junkai, Cheng, Jian |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Training LLMs for Multi-Step Tool Orchestration with Constrained Data Synthesis and Graduated Rewards
by: Jiayang, Cheng, et al.
Published: (2026)
by: Jiayang, Cheng, et al.
Published: (2026)
Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement
by: Xiong, Weimin, et al.
Published: (2024)
by: Xiong, Weimin, et al.
Published: (2024)
Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs
by: Wu, Yang, et al.
Published: (2025)
by: Wu, Yang, et al.
Published: (2025)
AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
by: Zhang, Genghan, et al.
Published: (2025)
by: Zhang, Genghan, et al.
Published: (2025)
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
by: Shi, Ruxue, et al.
Published: (2025)
by: Shi, Ruxue, et al.
Published: (2025)
OptScale: Probabilistic Optimality for Inference-time Scaling
by: Wang, Youkang, et al.
Published: (2025)
by: Wang, Youkang, et al.
Published: (2025)
Can Performant LLMs Be Ethical? Quantifying the Impact of Web Crawling Opt-Outs
by: Fan, Dongyang, et al.
Published: (2025)
by: Fan, Dongyang, et al.
Published: (2025)
BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning
by: Zhang, Beichen, et al.
Published: (2025)
by: Zhang, Beichen, et al.
Published: (2025)
OptMATH: A Scalable Bidirectional Data Synthesis Framework for Optimization Modeling
by: Lu, Hongliang, et al.
Published: (2025)
by: Lu, Hongliang, et al.
Published: (2025)
Enhancing Multi-Step Reasoning Abilities of Language Models through Direct Q-Function Optimization
by: Ji, Kaixuan, et al.
Published: (2024)
by: Ji, Kaixuan, et al.
Published: (2024)
StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion
by: Wu, Yutong, et al.
Published: (2025)
by: Wu, Yutong, et al.
Published: (2025)
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
by: Lai, Xin, et al.
Published: (2024)
by: Lai, Xin, et al.
Published: (2024)
Aligning Frozen LLMs by Reinforcement Learning: An Iterative Reweight-then-Optimize Approach
by: Zhang, Xinnan, et al.
Published: (2025)
by: Zhang, Xinnan, et al.
Published: (2025)
OptLLM: Optimal Assignment of Queries to Large Language Models
by: Liu, Yueyue, et al.
Published: (2024)
by: Liu, Yueyue, et al.
Published: (2024)
Iterative Self-Tuning LLMs for Enhanced Jailbreaking Capabilities
by: Sun, Chung-En, et al.
Published: (2024)
by: Sun, Chung-En, et al.
Published: (2024)
A Strategic Coordination Framework of Small LLMs Matches Large LLMs in Data Synthesis
by: Gao, Xin, et al.
Published: (2025)
by: Gao, Xin, et al.
Published: (2025)
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
by: Zhou, Xiangxin, et al.
Published: (2024)
by: Zhou, Xiangxin, et al.
Published: (2024)
Training and Evaluating Language Models with Template-based Data Generation
by: Zhang, Yifan
Published: (2024)
by: Zhang, Yifan
Published: (2024)
Augmenting Math Word Problems via Iterative Question Composing
by: Liu, Haoxiong, et al.
Published: (2024)
by: Liu, Haoxiong, et al.
Published: (2024)
OptPO: Optimal Rollout Allocation for Test-time Policy Optimization
by: Wang, Youkang, et al.
Published: (2025)
by: Wang, Youkang, et al.
Published: (2025)
DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrails
by: Deng, Yihe, et al.
Published: (2025)
by: Deng, Yihe, et al.
Published: (2025)
Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection
by: Tan, Xuwei, et al.
Published: (2025)
by: Tan, Xuwei, et al.
Published: (2025)
SAC-Opt: Semantic Anchors for Iterative Correction in Optimization Modeling
by: Zhang, Yansen, et al.
Published: (2025)
by: Zhang, Yansen, et al.
Published: (2025)
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
by: Liu, Yuliang, et al.
Published: (2025)
by: Liu, Yuliang, et al.
Published: (2025)
An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs
by: Zhang, Hengran, et al.
Published: (2024)
by: Zhang, Hengran, et al.
Published: (2024)
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
by: Zhu, Dawei, et al.
Published: (2023)
by: Zhu, Dawei, et al.
Published: (2023)
Table-LLM-Specialist: Language Model Specialists for Tables using Iterative Generator-Validator Fine-tuning
by: Xing, Junjie, et al.
Published: (2024)
by: Xing, Junjie, et al.
Published: (2024)
Promoting Data and Model Privacy in Federated Learning through Quantized LoRA
by: Zhu, JianHao, et al.
Published: (2024)
by: Zhu, JianHao, et al.
Published: (2024)
MPO: Boosting LLM Agents with Meta Plan Optimization
by: Xiong, Weimin, et al.
Published: (2025)
by: Xiong, Weimin, et al.
Published: (2025)
InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models
by: Gu, Yanggan, et al.
Published: (2025)
by: Gu, Yanggan, et al.
Published: (2025)
Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model
by: Wu, Minghao, et al.
Published: (2026)
by: Wu, Minghao, et al.
Published: (2026)
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization
by: Zhang, Ruiqi, et al.
Published: (2024)
by: Zhang, Ruiqi, et al.
Published: (2024)
Evolving LLMs' Self-Refinement Capability via Synergistic Training-Inference Optimization
by: Zeng, Yongcheng, et al.
Published: (2025)
by: Zeng, Yongcheng, et al.
Published: (2025)
Reasoning Boosts Opinion Alignment in LLMs
by: Berdoz, Frédéric, et al.
Published: (2026)
by: Berdoz, Frédéric, et al.
Published: (2026)
Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment
by: Zhang, Yifan, et al.
Published: (2024)
by: Zhang, Yifan, et al.
Published: (2024)
ADOPT: Adaptive Dependency-Guided Joint Prompt Optimization for Multi-Step LLM Pipelines
by: Zhao, Minjun, et al.
Published: (2025)
by: Zhao, Minjun, et al.
Published: (2025)
Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
by: Wei, Anjiang, et al.
Published: (2025)
by: Wei, Anjiang, et al.
Published: (2025)
Offline Reinforcement Learning for LLM Multi-Step Reasoning
by: Wang, Huaijie, et al.
Published: (2024)
by: Wang, Huaijie, et al.
Published: (2024)
Zero-to-Strong Generalization: Eliciting Strong Capabilities of Large Language Models Iteratively without Gold Labels
by: Liu, Chaoqun, et al.
Published: (2024)
by: Liu, Chaoqun, et al.
Published: (2024)
AgentPRM: Process Reward Models for LLM Agents via Step-Wise Promise and Progress
by: Xi, Zhiheng, et al.
Published: (2025)
by: Xi, Zhiheng, et al.
Published: (2025)
Similar Items
-
Training LLMs for Multi-Step Tool Orchestration with Constrained Data Synthesis and Graduated Rewards
by: Jiayang, Cheng, et al.
Published: (2026) -
Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement
by: Xiong, Weimin, et al.
Published: (2024) -
Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs
by: Wu, Yang, et al.
Published: (2025) -
AccelOpt: A Self-Improving LLM Agentic System for AI Accelerator Kernel Optimization
by: Zhang, Genghan, et al.
Published: (2025) -
Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
by: Shi, Ruxue, et al.
Published: (2025)