Image de couverture de livre

EFPC: Towards Efficient and Flexible Prompt Compression

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Cao, Yun-Hao, Wang, Yangsong, Hao, Shuzheng, Li, Zhenxing, Zhan, Chengjun, Liu, Sichao, Hu, Yi-Qi
Format:	Preprint
Publié:	2025
Sujets:	Computation and Language Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

An Empirical Study on Prompt Compression for Large Language Models
par: Zhang, Zheng, et autres
Publié: (2025)

Dynamic Compressing Prompts for Efficient Inference of Large Language Models
par: Hu, Jinwu, et autres
Publié: (2025)

From Context to EDUs: Faithful and Structured Context Compression via Elementary Discourse Unit Decomposition
par: Zhou, Yiqing, et autres
Publié: (2025)

Efficient and Effective Prompt Tuning via Prompt Decomposition and Compressed Outer Product
par: Lan, Pengxiang, et autres
Publié: (2025)

Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
par: Ali, Muhammad Asif, et autres
Publié: (2024)

ConsPrompt: Exploiting Contrastive Samples for Fewshot Prompt Learning
par: Weng, Jinta, et autres
Publié: (2022)

The Prompt Alchemist: Automated LLM-Tailored Prompt Optimization for Test Case Generation
par: Gao, Shuzheng, et autres
Publié: (2025)

ICPC: In-context Prompt Compression with Faster Inference
par: Yu, Ziyang, et autres
Publié: (2025)

PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression
par: Chen, Lizhe, et autres
Publié: (2025)

Application and Optimization of Large Models Based on Prompt Tuning for Fact-Check-Worthiness Estimation
par: Yu, Yinglong, et autres
Publié: (2025)

Adapting LLMs for Efficient Context Processing through Soft Prompt Compression
par: Wang, Cangqing, et autres
Publié: (2024)

InjecGuard: Benchmarking and Mitigating Over-defense in Prompt Injection Guardrail Models
par: Li, Hao, et autres
Publié: (2024)

SCOPE: A Generative Approach for LLM Prompt Compression
par: Zhang, Tinghui, et autres
Publié: (2025)

PromptEmbedder:: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting
par: Tsai, Yu-Che, et autres
Publié: (2026)

Learning to Compress Prompt in Natural Language Formats
par: Chuang, Yu-Neng, et autres
Publié: (2024)

Compressing Sequences in the Latent Embedding Space: $K$-Token Merging for Large Language Models
par: Xu, Zihao, et autres
Publié: (2026)

Prompt Chaining or Stepwise Prompt? Refinement in Text Summarization
par: Sun, Shichao, et autres
Publié: (2024)

Focus on the Core: Efficient Attention via Pruned Token Compression for Document Classification
par: Yun, Jungmin, et autres
Publié: (2024)

Discrete Prompt Compression with Reinforcement Learning
par: Jung, Hoyoun, et autres
Publié: (2023)

Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression
par: Zhang, Yong, et autres
Publié: (2025)

URL: Universal Referential Knowledge Linking via Task-instructed Representation Compression
par: Li, Zhuoqun, et autres
Publié: (2024)

Examples as the Prompt: A Scalable Approach for Efficient LLM Adaptation in E-Commerce
par: Zeng, Jingying, et autres
Publié: (2025)

Evaluating LLM Understanding via Structured Tabular Decision Simulations
par: Li, Sichao, et autres
Publié: (2025)

RhinoInsight: Improving Deep Research through Control Mechanisms for Model Behavior and Context
par: Lei, Yu, et autres
Publié: (2025)

InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
par: Bai, Yuzhuo, et autres
Publié: (2026)

GRL-Prompt: Towards Knowledge Graph based Prompt Optimization via Reinforcement Learning
par: Liu, Yuze, et autres
Publié: (2024)

R$^3$Mem: Bridging Memory Retention and Retrieval via Reversible Compression
par: Wang, Xiaoqiang, et autres
Publié: (2025)

Recurrent Context Compression: Efficiently Expanding the Context Window of LLM
par: Huang, Chensen, et autres
Publié: (2024)

Metacognitive Prompting Improves Understanding in Large Language Models
par: Wang, Yuqing, et autres
Publié: (2023)

Parse Trees Guided LLM Prompt Compression
par: Mao, Wenhao, et autres
Publié: (2024)

Hypothesis Testing Prompting Improves Deductive Reasoning in Large Language Models
par: Li, Yitian, et autres
Publié: (2024)

ALPS: Attention Localization and Pruning Strategy for Efficient Alignment of Large Language Models
par: Chen, Hao, et autres
Publié: (2025)

Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
par: Hong, Junyuan, et autres
Publié: (2024)

RuPLaR : Efficient Latent Compression of LLM Reasoning Chains with Rule-Based Priors From Multi-Step to One-Step
par: Luo, Xiaocheng, et autres
Publié: (2026)

PGSO: Prompt-based Generative Sequence Optimization Network for Aspect-based Sentiment Analysis
par: Dong, Hao, et autres
Publié: (2024)

Look Before You Leap: Problem Elaboration Prompting Improves Mathematical Reasoning in Large Language Models
par: Liao, Haoran, et autres
Publié: (2024)

ArcAligner: Adaptive Recursive Aligner for Compressed Context Embeddings in RAG
par: Li, Jianbo, et autres
Publié: (2026)

ConMax: Confidence-Maximizing Compression for Efficient Chain-of-Thought Reasoning
par: Hu, Minda, et autres
Publié: (2026)

A Survey on Collaborative Mechanisms Between Large and Small Language Models
par: Chen, Yi, et autres
Publié: (2025)

One-Shot Learning as Instruction Data Prospector for Large Language Models
par: Li, Yunshui, et autres
Publié: (2023)