Cover Image

GRIP: In-Parameter Graph Reasoning through Fine-Tuning Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Feng, Jiarui, Cai, Donghong, Chen, Yixin, Zhang, Muhan
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
by: Cai, Donghong, et al.
Published: (2026)

Toward Graph-Tokenizing Large Language Models with Reconstructive Graph Instruction Tuning
by: Zhang, Zhongjian, et al.
Published: (2026)

Supervised Fine-Tuning versus Reinforcement Learning: A Study of Post-Training Methods for Large Language Models
by: Jiang, Haitao, et al.
Published: (2026)

Parameter-Efficient Fine-Tuning of Large Language Models via Deconvolution in Subspace
by: Zhang, Jia-Chen, et al.
Published: (2025)

Pramana: Fine-Tuning Large Language Models for Epistemic Reasoning through Navya-Nyaya
by: Sathish, Sharath
Published: (2026)

Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning
by: Zhang, Xinlu, et al.
Published: (2024)

MoA: Heterogeneous Mixture of Adapters for Parameter-Efficient Fine-Tuning of Large Language Models
by: Cao, Jie, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
by: Wang, Luping, et al.
Published: (2024)

Parrot Mind: Towards Explaining the Complex Task Reasoning of Pretrained Large Language Models with Template-Content Structure
by: Yang, Haotong, et al.
Published: (2023)

Parameter-Efficient Fine-Tuning for Foundation Models
by: Zhang, Dan, et al.
Published: (2025)

Memorization in Fine-Tuned Large Language Models
by: Savine, Danil
Published: (2025)

Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
by: Cai, Hengrui, et al.
Published: (2023)

Unveiling Reasoning Thresholds in Language Models: Scaling, Fine-Tuning, and Interpretability through Attention Maps
by: Hsiao, Yen-Che, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning With Adapters
by: Chen, Keyu, et al.
Published: (2024)

LFTF: Locating First and Then Fine-Tuning for Mitigating Gender Bias in Large Language Models
by: Qin, Zhanyue, et al.
Published: (2025)

LIFT: Improving Long Context Understanding Through Long Input Fine-Tuning
by: Mao, Yansheng, et al.
Published: (2024)

Safety-Aware Fine-Tuning of Large Language Models
by: Choi, Hyeong Kyu, et al.
Published: (2024)

Phased Instruction Fine-Tuning for Large Language Models
by: Pang, Wei, et al.
Published: (2024)

Reasoning Towards Fairness: Mitigating Bias in Language Models through Reasoning-Guided Fine-Tuning
by: Kabra, Sanchit, et al.
Published: (2025)

Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law
by: Bashir, Ali Hamza, et al.
Published: (2026)

Reinforcement Fine-Tuning Powers Reasoning Capability of Multimodal Large Language Models
by: Sun, Haoyuan, et al.
Published: (2025)

Improving Large Language Models with Concept-Aware Fine-Tuning
by: Chen, Michael K., et al.
Published: (2025)

Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
by: Leong, Hui Yi, et al.
Published: (2024)

Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
by: Barnett, Scott, et al.
Published: (2024)

Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
by: Jang, Chaeyun, et al.
Published: (2024)

KnowTuning: Knowledge-aware Fine-tuning for Large Language Models
by: Lyu, Yougang, et al.
Published: (2024)

Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning
by: Guo, Chenyou, et al.
Published: (2026)

Reversing Large Language Models for Efficient Training and Fine-Tuning
by: Gal, Eshed, et al.
Published: (2025)

Impact of Fine-Tuning Methods on Memorization in Large Language Models
by: Hou, Jie, et al.
Published: (2025)

Boosting Large Language Models with Mask Fine-Tuning
by: Zhang, Mingyuan, et al.
Published: (2025)

GraphGPT: Graph Instruction Tuning for Large Language Models
by: Tang, Jiabin, et al.
Published: (2023)

LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
by: Zheng, Yaowei, et al.
Published: (2024)

Hyperbolic Fine-Tuning for Large Language Models
by: Yang, Menglin, et al.
Published: (2024)

DLoRA: Distributed Parameter-Efficient Fine-Tuning Solution for Large Language Model
by: Gao, Chao, et al.
Published: (2024)

Fine-grained Stateful Knowledge Exploration: Effective and Efficient Graph Retrieval with Large Language Models
by: Tao, Dehao, et al.
Published: (2024)

Taiyi: A Bilingual Fine-Tuned Large Language Model for Diverse Biomedical Tasks
by: Luo, Ling, et al.
Published: (2023)

RoSA: Enhancing Parameter-Efficient Fine-Tuning via RoPE-aware Selective Adaptation in Large Language Models
by: Pan, Dayan, et al.
Published: (2025)

Investigating Instruction Tuning Large Language Models on Graphs
by: Zhu, Kerui, et al.
Published: (2024)

Noise Augmented Fine Tuning for Mitigating Hallucinations in Large Language Models
by: Khadangi, Afshin, et al.
Published: (2025)

Coevolutionary Continuous Discrete Diffusion: Make Your Diffusion Language Model a Latent Reasoner
by: Zhou, Cai, et al.
Published: (2025)