ACCEPT: Adaptive Codebook for Composite and Efficient Prompt Tuning
Fuente:
arXiv
Saved in:
| Main Authors: | Lin, Yu-Chen, Li, Wei-Hua, Chen, Jun-Cheng, Chen, Chu-Song |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
APrompt4EM: Augmented Prompt Tuning for Generalized Entity Matching
by: Xia, Yikuan, et al.
Published: (2024)
by: Xia, Yikuan, et al.
Published: (2024)
CodeBind: Decoupled Representation Learning for Multimodal Alignment with Unified Compositional Codebook
by: Chen, Zeyu, et al.
Published: (2026)
by: Chen, Zeyu, et al.
Published: (2026)
PromptEmbedder:: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting
by: Tsai, Yu-Che, et al.
Published: (2026)
by: Tsai, Yu-Che, et al.
Published: (2026)
Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction
by: Peng, Cheng, et al.
Published: (2023)
by: Peng, Cheng, et al.
Published: (2023)
Fine-Tuned Language Models for Domain-Specific Summarization and Tagging
by: Wang, Jun, et al.
Published: (2025)
by: Wang, Jun, et al.
Published: (2025)
SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation
by: Chen, Yi-Chia, et al.
Published: (2024)
by: Chen, Yi-Chia, et al.
Published: (2024)
PromptRad: Knowledge-Enhanced Multi-Label Prompt-Tuning for Low-Resource Radiology Report Labeling
by: Lin, Ying-Jia, et al.
Published: (2026)
by: Lin, Ying-Jia, et al.
Published: (2026)
Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation
by: Dong, Harry, et al.
Published: (2024)
by: Dong, Harry, et al.
Published: (2024)
MAPO: Boosting Large Language Model Performance with Model-Adaptive Prompt Optimization
by: Chen, Yuyan, et al.
Published: (2024)
by: Chen, Yuyan, et al.
Published: (2024)
Mask-aware Text-to-Image Retrieval: Referring Expression Segmentation Meets Cross-modal Retrieval
by: Shen, Li-Cheng, et al.
Published: (2025)
by: Shen, Li-Cheng, et al.
Published: (2025)
PAFT: Prompt-Agnostic Fine-Tuning
by: Wei, Chenxing, et al.
Published: (2025)
by: Wei, Chenxing, et al.
Published: (2025)
Using LLMs for Automated Privacy Policy Analysis: Prompt Engineering, Fine-Tuning and Explainability
by: Chen, Yuxin, et al.
Published: (2025)
by: Chen, Yuxin, et al.
Published: (2025)
MARS: Multi-Agent Adaptive Reasoning with Socratic Guidance for Automated Prompt Optimization
by: Zhang, Jian, et al.
Published: (2025)
by: Zhang, Jian, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning With Adapters
by: Chen, Keyu, et al.
Published: (2024)
by: Chen, Keyu, et al.
Published: (2024)
CrossIn: An Efficient Instruction Tuning Approach for Cross-Lingual Knowledge Alignment
by: Lin, Geyu, et al.
Published: (2024)
by: Lin, Geyu, et al.
Published: (2024)
Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product
by: Lan, Pengxiang, et al.
Published: (2025)
by: Lan, Pengxiang, et al.
Published: (2025)
A Parameter-Efficient Transfer Learning Approach through Multitask Prompt Distillation and Decomposition for Clinical NLP
by: Peng, Cheng, et al.
Published: (2026)
by: Peng, Cheng, et al.
Published: (2026)
TsqLoRA: Towards Sensitivity and Quality Low-Rank Adaptation for Efficient Fine-Tuning
by: Chen, Yu, et al.
Published: (2025)
by: Chen, Yu, et al.
Published: (2025)
PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression
by: Chen, Lizhe, et al.
Published: (2025)
by: Chen, Lizhe, et al.
Published: (2025)
Robustness of Prompting: Enhancing Robustness of Large Language Models Against Prompting Attacks
by: Mu, Lin, et al.
Published: (2025)
by: Mu, Lin, et al.
Published: (2025)
Enhancing Few-Shot Transfer Learning with Optimized Multi-Task Prompt Tuning through Modular Prompt Composition
by: Pouramini, Ahmad, et al.
Published: (2024)
by: Pouramini, Ahmad, et al.
Published: (2024)
Prompt4Vis: Prompting Large Language Models with Example Mining and Schema Filtering for Tabular Data Visualization
by: Li, Shuaimin, et al.
Published: (2024)
by: Li, Shuaimin, et al.
Published: (2024)
Adaptive Activation Steering: A Tuning-Free LLM Truthfulness Improvement Method for Diverse Hallucinations Categories
by: Wang, Tianlong, et al.
Published: (2024)
by: Wang, Tianlong, et al.
Published: (2024)
Multi-domain Knowledge Graph Collaborative Pre-training and Prompt Tuning for Diverse Downstream Tasks
by: Zhang, Yichi, et al.
Published: (2024)
by: Zhang, Yichi, et al.
Published: (2024)
MCQA-Eval: Efficient Confidence Evaluation in NLG with Gold-Standard Correctness Labels
by: Liu, Xiaoou, et al.
Published: (2025)
by: Liu, Xiaoou, et al.
Published: (2025)
Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion
by: Lan, Pengxiang, et al.
Published: (2024)
by: Lan, Pengxiang, et al.
Published: (2024)
Dynamic Task Vector Grouping for Efficient Multi-Task Prompt Tuning
by: Zhang, Pieyi, et al.
Published: (2025)
by: Zhang, Pieyi, et al.
Published: (2025)
Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
by: Shernazarov, Ulugbek, et al.
Published: (2026)
by: Shernazarov, Ulugbek, et al.
Published: (2026)
MSSR: Memory-Aware Adaptive Replay for Continual LLM Fine-Tuning
by: Lu, Yiyang, et al.
Published: (2026)
by: Lu, Yiyang, et al.
Published: (2026)
Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows
by: Ayala, Orlando Marquez, et al.
Published: (2025)
by: Ayala, Orlando Marquez, et al.
Published: (2025)
Adaptive Testing for LLM Evaluation: A Psychometric Alternative to Static Benchmarks
by: Li, Peiyu, et al.
Published: (2025)
by: Li, Peiyu, et al.
Published: (2025)
Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)
Black-box Prompt Tuning with Subspace Learning
by: Zheng, Yuanhang, et al.
Published: (2023)
by: Zheng, Yuanhang, et al.
Published: (2023)
Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives
by: Sun, Qiushi, et al.
Published: (2023)
by: Sun, Qiushi, et al.
Published: (2023)
GradPruner: Gradient-Guided Layer Pruning Enabling Efficient Fine-Tuning and Inference for LLMs
by: Huang, Wei, et al.
Published: (2026)
by: Huang, Wei, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
by: Gao, Ziqi, et al.
Published: (2024)
by: Gao, Ziqi, et al.
Published: (2024)
HUT: A More Computation Efficient Fine-Tuning Method With Hadamard Updated Transformation
by: Zhang, Geyuan, et al.
Published: (2024)
by: Zhang, Geyuan, et al.
Published: (2024)
Towards Robust Instruction Tuning on Multimodal Large Language Models
by: Han, Wei, et al.
Published: (2024)
by: Han, Wei, et al.
Published: (2024)
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
by: Ning, Xuefei, et al.
Published: (2023)
by: Ning, Xuefei, et al.
Published: (2023)
Parameter-Efficient Fine-Tuning of Large Language Models via Deconvolution in Subspace
by: Zhang, Jia-Chen, et al.
Published: (2025)
by: Zhang, Jia-Chen, et al.
Published: (2025)
Similar Items
-
APrompt4EM: Augmented Prompt Tuning for Generalized Entity Matching
by: Xia, Yikuan, et al.
Published: (2024) -
CodeBind: Decoupled Representation Learning for Multimodal Alignment with Unified Compositional Codebook
by: Chen, Zeyu, et al.
Published: (2026) -
PromptEmbedder:: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting
by: Tsai, Yu-Che, et al.
Published: (2026) -
Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extraction
by: Peng, Cheng, et al.
Published: (2023) -
Fine-Tuned Language Models for Domain-Specific Summarization and Tagging
by: Wang, Jun, et al.
Published: (2025)