Learn to Think: Bootstrapping LLM Reasoning Capability Through Graph Representation Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Gao, Hang, Zhang, Chenhao, Wang, Tie, Zhao, Junsuo, Wu, Fengge, Zheng, Changwen, Liu, Huaping |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
by: Gao, Hang, et al.
Published: (2024)
by: Gao, Hang, et al.
Published: (2024)
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
by: Gao, Hang, et al.
Published: (2025)
by: Gao, Hang, et al.
Published: (2025)
Molecular Graph Representation Learning via Structural Similarity Information
by: Yao, Chengyu, et al.
Published: (2024)
by: Yao, Chengyu, et al.
Published: (2024)
A Closer Look at the Application of Causal Inference in Graph Representation Learning
by: Gao, Hang, et al.
Published: (2026)
by: Gao, Hang, et al.
Published: (2026)
MBDS: A Multi-Body Dynamics Simulation Dataset for Graph Networks Simulators
by: Yang, Sheng, et al.
Published: (2024)
by: Yang, Sheng, et al.
Published: (2024)
Graph Partial Label Learning with Potential Cause Discovering
by: Gao, Hang, et al.
Published: (2024)
by: Gao, Hang, et al.
Published: (2024)
Introducing Diminutive Causal Structure into Graph Representation Learning
by: Gao, Hang, et al.
Published: (2024)
by: Gao, Hang, et al.
Published: (2024)
Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning
by: Wu, Yicong, et al.
Published: (2025)
by: Wu, Yicong, et al.
Published: (2025)
BRiTE: Bootstrapping Reinforced Thinking Process to Enhance Language Model Reasoning
by: Zhong, Han, et al.
Published: (2025)
by: Zhong, Han, et al.
Published: (2025)
MeTHanol: Modularized Thinking Language Models with Intermediate Layer Thinking, Decoding and Bootstrapping Reasoning
by: Xi, Ningyuan, et al.
Published: (2024)
by: Xi, Ningyuan, et al.
Published: (2024)
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
by: Ji, Qirui, et al.
Published: (2023)
by: Ji, Qirui, et al.
Published: (2023)
Evaluation is All You Need: Strategic Overclaiming of LLM Reasoning Capabilities Through Evaluation Design
by: Sun, Lin, et al.
Published: (2025)
by: Sun, Lin, et al.
Published: (2025)
Towards Robust Deep Reinforcement Learning against Environmental State Perturbation
by: Wang, Chenxu, et al.
Published: (2025)
by: Wang, Chenxu, et al.
Published: (2025)
Thinking with Deltas: Incentivizing Reinforcement Learning via Differential Visual Reasoning Policy
by: Gao, Shujian, et al.
Published: (2026)
by: Gao, Shujian, et al.
Published: (2026)
HTG-GCL: Leveraging Hierarchical Topological Granularity from Cellular Complexes for Graph Contrastive Learning
by: Ji, Qirui, et al.
Published: (2025)
by: Ji, Qirui, et al.
Published: (2025)
On the Universality of Self-Supervised Learning
by: Qiang, Wenwen, et al.
Published: (2024)
by: Qiang, Wenwen, et al.
Published: (2024)
Uncovering Capabilities of Model Pruning in Graph Contrastive Learning
by: Wu, Junran, et al.
Published: (2024)
by: Wu, Junran, et al.
Published: (2024)
Enhancing Large Language Models for Time-Series Forecasting via Vector-Injected In-Context Learning
by: Zhang, Jianqi, et al.
Published: (2026)
by: Zhang, Jianqi, et al.
Published: (2026)
MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs
by: Bartmann, Christoph, et al.
Published: (2026)
by: Bartmann, Christoph, et al.
Published: (2026)
AdaptThink: Reasoning Models Can Learn When to Think
by: Zhang, Jiajie, et al.
Published: (2025)
by: Zhang, Jiajie, et al.
Published: (2025)
Flow-of-Options: Diversified and Improved LLM Reasoning by Thinking Through Options
by: Nair, Lakshmi, et al.
Published: (2025)
by: Nair, Lakshmi, et al.
Published: (2025)
PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning
by: Wang, Ruheng, et al.
Published: (2025)
by: Wang, Ruheng, et al.
Published: (2025)
Learning Network Representations with Disentangled Graph Auto-Encoder
by: Fan, Di, et al.
Published: (2024)
by: Fan, Di, et al.
Published: (2024)
CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Temporal Knowledge Graph Reasoning
by: Sun, Jinze, et al.
Published: (2024)
by: Sun, Jinze, et al.
Published: (2024)
DeepThinkVLA: Enhancing Reasoning Capability of Vision-Language-Action Models
by: Yin, Cheng, et al.
Published: (2025)
by: Yin, Cheng, et al.
Published: (2025)
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning
by: Xu, Junjie, et al.
Published: (2024)
by: Xu, Junjie, et al.
Published: (2024)
Learning Invariant Graph Representations Through Redundant Information
by: Halder, Barproda, et al.
Published: (2025)
by: Halder, Barproda, et al.
Published: (2025)
Knowledge Probing for Graph Representation Learning
by: Zhao, Mingyu, et al.
Published: (2024)
by: Zhao, Mingyu, et al.
Published: (2024)
GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values
by: Ke, Songyu, et al.
Published: (2025)
by: Ke, Songyu, et al.
Published: (2025)
A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases
by: Wang, Zhepeng, et al.
Published: (2024)
by: Wang, Zhepeng, et al.
Published: (2024)
Bootstrapping Expectiles in Reinforcement Learning
by: Clavier, Pierre, et al.
Published: (2024)
by: Clavier, Pierre, et al.
Published: (2024)
Imitation Bootstrapped Reinforcement Learning
by: Hu, Hengyuan, et al.
Published: (2023)
by: Hu, Hengyuan, et al.
Published: (2023)
Disentangled Generative Graph Representation Learning
by: Hu, Xinyue, et al.
Published: (2024)
by: Hu, Xinyue, et al.
Published: (2024)
A Versatile Graph Learning Approach through LLM-based Agent
by: Wei, Lanning, et al.
Published: (2023)
by: Wei, Lanning, et al.
Published: (2023)
Richer Representations for Neural Algorithmic Reasoning via Auxiliary Reconstruction
by: Huang, Jiafu, et al.
Published: (2026)
by: Huang, Jiafu, et al.
Published: (2026)
h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
by: Motwani, Sumeet Ramesh, et al.
Published: (2025)
by: Motwani, Sumeet Ramesh, et al.
Published: (2025)
Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias
by: Shi, Zhihao, et al.
Published: (2023)
by: Shi, Zhihao, et al.
Published: (2023)
rePIRL: Learn PRM with Inverse RL for LLM Reasoning
by: Wu, Xian, et al.
Published: (2026)
by: Wu, Xian, et al.
Published: (2026)
Unlocking Reasoning Capabilities in LLMs via Reinforcement Learning Exploration
by: Deng, Wenhao, et al.
Published: (2025)
by: Deng, Wenhao, et al.
Published: (2025)
Think-Augmented Function Calling: Improving LLM Parameter Accuracy Through Embedded Reasoning
by: Wei, Lei, et al.
Published: (2026)
by: Wei, Lei, et al.
Published: (2026)
Similar Items
-
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
by: Gao, Hang, et al.
Published: (2024) -
LLM Enhancers for GNNs: An Analysis from the Perspective of Causal Mechanism Identification
by: Gao, Hang, et al.
Published: (2025) -
Molecular Graph Representation Learning via Structural Similarity Information
by: Yao, Chengyu, et al.
Published: (2024) -
A Closer Look at the Application of Causal Inference in Graph Representation Learning
by: Gao, Hang, et al.
Published: (2026) -
MBDS: A Multi-Body Dynamics Simulation Dataset for Graph Networks Simulators
by: Yang, Sheng, et al.
Published: (2024)