Cover Image

OneNet: A Fine-Tuning Free Framework for Few-Shot Entity Linking via Large Language Model Prompting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Xukai, Liu, Ye, Zhang, Kai, Wang, Kehang, Liu, Qi, Chen, Enhong
Format:	Preprint
Published:	2024
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

Leveraging Entity Information for Cross-Modality Correlation Learning: The Entity-Guided Multimodal Summarization
by: Zhang, Yanghai, et al.
Published: (2024)

Empowering Few-Shot Relation Extraction with The Integration of Traditional RE Methods and Large Language Models
by: Liu, Ye, et al.
Published: (2024)

UniMEL: A Unified Framework for Multimodal Entity Linking with Large Language Models
by: Qi, Liu, et al.
Published: (2024)

Detect, Investigate, Judge and Determine: A Knowledge-guided Framework for Few-shot Fake News Detection
by: Liu, Ye, et al.
Published: (2024)

Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models
by: Tang, Haoyu, et al.
Published: (2024)

Layer-Order Inversion: Rethinking Latent Multi-Hop Reasoning in Large Language Models
by: Liu, Xukai, et al.
Published: (2026)

LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
by: Ye, Junjie, et al.
Published: (2024)

Prompt Tuning for Few-Shot Continual Learning Named Entity Recognition
by: Ren, Zhe
Published: (2025)

Large Language Models for Few-Shot Named Entity Recognition
by: Zhao, Yufei, et al.
Published: (2018)

In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning
by: Duan, Yifei, et al.
Published: (2024)

Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models
by: Xie, Tingyu, et al.
Published: (2023)

Fact4ac at the Financial Misinformation Detection Challenge Task: Reference-Free Financial Misinformation Detection via Fine-Tuning and Few-Shot Prompting of Large Language Models
by: Hoang, Cuong, et al.
Published: (2026)

Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
by: Kaddour, Jean, et al.
Published: (2023)

Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies
by: Kuila, Alapan, et al.
Published: (2024)

TLoRA+: A Low-Rank Parameter-Efficient Fine-Tuning Method for Large Language Models
by: Cao, Yarui, et al.
Published: (2026)

Efficient Response Generation Strategy Selection for Fine-Tuning Large Language Models Through Self-Aligned Perplexity
by: Ren, Xuan, et al.
Published: (2025)

Know3-RAG: A Knowledge-aware RAG Framework with Adaptive Retrieval, Generation, and Filtering
by: Liu, Xukai, et al.
Published: (2025)

Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning
by: Xie, Kaige, et al.
Published: (2023)

CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition
by: Zhang, Yafeng, et al.
Published: (2024)

Editing Knowledge Representation of Language Model via Rephrased Prefix Prompts
by: Cai, Yuchen, et al.
Published: (2024)

Few-Shot Adversarial Prompt Learning on Vision-Language Models
by: Zhou, Yiwei, et al.
Published: (2024)

Confidence Is All You Need: Few-Shot RL Fine-Tuning of Language Models
by: Li, Pengyi, et al.
Published: (2025)

llmNER: (Zero|Few)-Shot Named Entity Recognition, Exploiting the Power of Large Language Models
by: Villena, Fabián, et al.
Published: (2024)

Few-Shot Joint Multimodal Entity-Relation Extraction via Knowledge-Enhanced Cross-modal Prompt Model
by: Yuan, Li, et al.
Published: (2024)

Enhancing Large Language Model Reasoning via Selective Critical Token Fine-Tuning
by: Ruan, Zhiwen, et al.
Published: (2025)

Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning
by: Guo, Yanhui, et al.
Published: (2024)

Structured Gradient Guidance for Few-Shot Adaptation in Large Language Models
by: Zheng, Hongye, et al.
Published: (2025)

Retrieval-Augmented Few-Shot Prompting Versus Fine-Tuning for Code Vulnerability Detection
by: Trad, Fouad, et al.
Published: (2025)

Instruction Tuning Vs. In-Context Learning: Revisiting Large Language Models in Few-Shot Computational Social Science
by: Wang, Taihang, et al.
Published: (2024)

Few-Shot and Training-Free Review Generation via Conversational Prompting
by: Kusano, Genki
Published: (2025)

Mixture-of-Instructions: Aligning Large Language Models via Mixture Prompting
by: Xu, Bowen, et al.
Published: (2024)

LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking
by: Xin, Amy, et al.
Published: (2024)

DIM: Dynamic Integration of Multimodal Entity Linking with Large Language Model
by: Song, Shezheng, et al.
Published: (2024)

Large-Scale Label Interpretation Learning for Few-Shot Named Entity Recognition
by: Golde, Jonas, et al.
Published: (2024)

Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
by: Hu, Yan, et al.
Published: (2023)

One-Shot Learning as Instruction Data Prospector for Large Language Models
by: Li, Yunshui, et al.
Published: (2023)

OneNet: A Channel-Wise 1D Convolutional U-Net
by: Byun, Sanghyun, et al.
Published: (2024)

Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction
by: Wang, Xiaokai, et al.
Published: (2025)

Few-Shot Cross-Lingual Transfer for Prompting Large Language Models in Low-Resource Languages
by: Toukmaji, Christopher
Published: (2024)

Few-Shot Prompting for Extractive Quranic QA with Instruction-Tuned LLMs
by: Basem, Mohamed, et al.
Published: (2025)