Cover Image

LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Xinrui, Ban, Yikun, Zou, Jiaru, Wei, Tianxin, Cook, Curtiss B., He, Jingrui
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Transformer Copilot: Learning from The Mistake Log in LLM Fine-tuning
by: Zou, Jiaru, et al.
Published: (2025)

Meta Clustering of Neural Bandits
by: Ban, Yikun, et al.
Published: (2024)

RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking
by: Zou, Jiaru, et al.
Published: (2025)

Panda: Test-Time Adaptation with Negative Data Augmentation
by: Deng, Ruxi, et al.
Published: (2025)

Heterogeneous Scientific Foundation Model Collaboration
by: Li, Zihao, et al.
Published: (2026)

MLP Fusion: Towards Efficient Fine-tuning of Dense and Mixture-of-Experts Language Models
by: Ai, Mengting, et al.
Published: (2023)

EvoSelect: Data-Efficient LLM Evolution for Targeted Task Adaptation
by: Li, Ting-Wei, et al.
Published: (2026)

Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization
by: Wei, Tianxin, et al.
Published: (2025)

Neural Exploitation and Exploration of Contextual Bandits
by: Ban, Yikun, et al.
Published: (2023)

Graph4MM: Weaving Multimodal Learning with Structural Information
by: Ning, Xuying, et al.
Published: (2025)

Can we Soft Prompt LLMs for Graph Learning Tasks?
by: Liu, Zheyuan, et al.
Published: (2024)

AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning
by: Zou, Jiaru, et al.
Published: (2025)

PageRank Bandits for Link Prediction
by: Ban, Yikun, et al.
Published: (2024)

Influence-Preserving Proxies for Gradient-Based Data Selection in LLM Fine-tuning
by: Chen, Sirui, et al.
Published: (2026)

TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning
by: Zou, Jiaru, et al.
Published: (2025)

PromptIntern: Saving Inference Costs by Internalizing Recurrent Prompt during Large Language Model Fine-tuning
by: Zou, Jiaru, et al.
Published: (2024)

NIRVANA: Structured pruning reimagined for large language models compression
by: Ai, Mengting, et al.
Published: (2025)

PyG-SSL: A Graph Self-Supervised Learning Toolkit
by: Zheng, Lecheng, et al.
Published: (2024)

GCL-OT: Graph Contrastive Learning with Optimal Transport for Heterophilic Text-Attributed Graphs
by: Ren, Yating, et al.
Published: (2025)

Neural Active Learning Beyond Bandits
by: Ban, Yikun, et al.
Published: (2024)

Recursive Multi-Agent Systems
by: Yang, Xiyuan, et al.
Published: (2026)

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning
by: Bao, Wenxuan, et al.
Published: (2025)

Can Graph Neural Networks Learn Language with Extremely Weak Text Supervision?
by: Li, Zihao, et al.
Published: (2024)

When Self-Belief Misleads: Active Label Acquisition for Reinforcement Learning with Verifiable Rewards
by: Wang, Li, et al.
Published: (2026)

Latent Collaboration in Multi-Agent Systems
by: Zou, Jiaru, et al.
Published: (2025)

Co-clustering for Federated Recommender System
by: He, Xinrui, et al.
Published: (2024)

Prompting Test-Time Scaling Is A Strong LLM Reasoning Data Augmentation
by: Bsharat, Sondos Mahmoud, et al.
Published: (2025)

RouteLLM: Learning to Route LLMs with Preference Data
by: Ong, Isaac, et al.
Published: (2024)

Learning to Rewrite Prompts for Bootstrapping LLMs on Downstream Tasks
by: Zhou, Qinhao, et al.
Published: (2025)

CoCoST: Automatic Complex Code Generation with Online Searching and Correctness Testing
by: He, Xinyi, et al.
Published: (2024)

Does Prompt Formatting Have Any Impact on LLM Performance?
by: He, Jia, et al.
Published: (2024)

Harnessing Consistency for Robust Test-Time LLM Ensemble
by: Zeng, Zhichen, et al.
Published: (2025)

Saffron-1: Safety Inference Scaling
by: Qiu, Ruizhong, et al.
Published: (2025)

Geometric-disentangelment Unlearning
by: Zhou, Duo, et al.
Published: (2025)

Rethinking LLM Evaluation: Can We Evaluate LLMs with 200x Less Data?
by: Wang, Shaobo, et al.
Published: (2025)

AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs
by: Cui, Chengming, et al.
Published: (2026)

Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models
by: He, Kang, et al.
Published: (2024)

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)

Does Prompt Design Impact Quality of Data Imputation by LLMs?
by: Srinivasan, Shreenidhi, et al.
Published: (2025)

LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity
by: Tekin, Selim Furkan, et al.
Published: (2024)