Imagen de Portada

Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Lan, Pengxiang, Yang, Enneng, Liu, Yuting, Guo, Guibing, Zhao, Jianzhe, Wang, Xingwei
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product
por: Lan, Pengxiang, et al.
Publicado: (2025)

Graph Representation Learning via Causal Diffusion for Out-of-Distribution Recommendation
por: Zhao, Chu, et al.
Publicado: (2024)

ECHO: Entropy-Confidence Hybrid Optimization for Test-Time Reinforcement Learning
por: Zhao, Chu, et al.
Publicado: (2026)

Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
por: Zhao, Chu, et al.
Publicado: (2025)

Symmetric Graph Contrastive Learning against Noisy Views for Recommendation
por: Zhao, Chu, et al.
Publicado: (2024)

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
por: Yang, Enneng, et al.
Publicado: (2024)

Representation Surgery for Multi-Task Model Merging
por: Yang, Enneng, et al.
Publicado: (2024)

Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
por: Zhao, Chu, et al.
Publicado: (2025)

DynaPrompt: Dynamic Test-Time Prompt Tuning
por: Xiao, Zehao, et al.
Publicado: (2025)

Subgraph-level Universal Prompt Tuning
por: Lee, Junhyun, et al.
Publicado: (2024)

Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
por: Choi, Yunseon, et al.
Publicado: (2024)

SurgeryV2: Bridging the Gap Between Model Merging and Multi-Task Learning with Deep Representation Surgery
por: Yang, Enneng, et al.
Publicado: (2024)

Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
por: Hu, Jerry Yao-Chieh, et al.
Publicado: (2024)

Selective Prompting Tuning for Personalized Conversations with LLMs
por: Huang, Qiushi, et al.
Publicado: (2024)

PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
por: Kim, Gyeongman, et al.
Publicado: (2024)

Plug and Play with Prompts: A Prompt Tuning Approach for Controlling Text Generation
por: Ajwani, Rohan Deepak, et al.
Publicado: (2024)

All You Need is One: Capsule Prompt Tuning with a Single Vector
por: Liu, Yiyang, et al.
Publicado: (2025)

MEPT: Mixture of Expert Prompt Tuning as a Manifold Mapper
por: Zeng, Runjia, et al.
Publicado: (2025)

FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion
por: Tang, Anke, et al.
Publicado: (2024)

M$^2$PT: Multimodal Prompt Tuning for Zero-shot Instruction Learning
por: Wang, Taowen, et al.
Publicado: (2024)

Causal Direct Preference Optimization for Distributionally Robust Generative Recommendation
por: Zhao, Chu, et al.
Publicado: (2026)

Instruction Fine-Tuning: Does Prompt Loss Matter?
por: Huerta-Enochian, Mathew, et al.
Publicado: (2024)

Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration
por: Huang, Langlin, et al.
Publicado: (2026)

Efficient Prompt Optimization Through the Lens of Best Arm Identification
por: Shi, Chengshuai, et al.
Publicado: (2024)

L-TUNING: Synchronized Label Tuning for Prompt and Prefix in LLMs
por: Kowsher, Md., et al.
Publicado: (2023)

Mitigate Negative Transfer with Similarity Heuristic Lifelong Prompt Tuning
por: Wu, Chenyuan, et al.
Publicado: (2024)

Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
por: Ali, Muhammad Asif, et al.
Publicado: (2024)

An Empirical Study on Preference Tuning Generalization and Diversity Under Domain Shift
por: Karouzos, Constantinos, et al.
Publicado: (2026)

MoPE: Mixture of Prompt Experts for Parameter-Efficient and Scalable Multimodal Fusion
por: Jiang, Ruixiang, et al.
Publicado: (2024)

Adapting LLMs for Efficient Context Processing through Soft Prompt Compression
por: Wang, Cangqing, et al.
Publicado: (2024)

Large Language Model Unlearning via Embedding-Corrupted Prompts
por: Liu, Chris Yuhao, et al.
Publicado: (2024)

Prompt Engineering a Prompt Engineer
por: Ye, Qinyuan, et al.
Publicado: (2023)

Automatic Prompt Optimization with Prompt Distillation
por: Dyagin, Ernest A., et al.
Publicado: (2025)

Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
por: Schnabel, Tobias, et al.
Publicado: (2024)

Bolster Hallucination Detection via Prompt-Guided Data Augmentation
por: Li, Wenyun, et al.
Publicado: (2025)

LoPT: Low-Rank Prompt Tuning for Parameter Efficient Language Models
por: Guo, Shouchang, et al.
Publicado: (2024)

Fight Back Against Jailbreaking via Prompt Adversarial Tuning
por: Mo, Yichuan, et al.
Publicado: (2024)

Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
por: Soylu, Dilara, et al.
Publicado: (2024)

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows
por: Ayala, Orlando Marquez, et al.
Publicado: (2025)

Prompting and Fine-Tuning of Small LLMs for Length-Controllable Telephone Call Summarization
por: Thulke, David, et al.
Publicado: (2024)