Copertina

DeMPT: Decoding-enhanced Multi-phase Prompt Tuning for Making LLMs Be Better Context-aware Translators

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lyu, Xinglin, Li, Junhui, Zhao, Yanqing, Zhang, Min, Wei, Daimeng, Tao, Shimin, Yang, Hao
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Two Intermediate Translations Are Better Than One: Fine-tuning LLMs for Document-level Translation Refinement
di: Dong, Yichen, et al.
Pubblicazione: (2025)

Improving LLM-based Document-level Machine Translation with Multi-Knowledge Fusion
di: Liu, Bin, et al.
Pubblicazione: (2025)

Cross-Preference Learning for Sentence-Level and Context-Aware Machine Translation
di: Li, Ying, et al.
Pubblicazione: (2026)

DoCIA: An Online Document-Level Context Incorporation Agent for Speech Translation
di: Lyu, Xinglin, et al.
Pubblicazione: (2025)

Loong: A Human-Like Long Document Translation Agent with Observe-and-Act Adaptive Context Selection
di: Wang, Yutong, et al.
Pubblicazione: (2026)

M-Ped: Multi-Prompt Ensemble Decoding for Large Language Models
di: Guo, Jiaxin, et al.
Pubblicazione: (2024)

Context-aware and Style-related Incremental Decoding framework for Discourse-Level Literary Translation
di: Luo, Yuanchang, et al.
Pubblicazione: (2024)

Unlocking Fine-Grained Translation Quality Estimation in LRMs through Synergistically Evolving Implicit and Explicit Reasoning
di: Dang, Renfei, et al.
Pubblicazione: (2026)

MPT: Motion Prompt Tuning for Micro-Expression Recognition
di: Liu, Jiateng, et al.
Pubblicazione: (2025)

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models
di: Wang, Xucong, et al.
Pubblicazione: (2026)

Visual Instance-aware Prompt Tuning
di: Xiao, Xi, et al.
Pubblicazione: (2025)

Speech Translation Refinement using Large Language Models
di: Dou, Huaixia, et al.
Pubblicazione: (2025)

From Handcrafted Features to LLMs: A Brief Survey for Machine Translation Quality Estimation
di: Zhao, Haofei, et al.
Pubblicazione: (2024)

R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning
di: He, Minggui, et al.
Pubblicazione: (2025)

Balance-aware Sequence Sampling Makes Multi-modal Learning Better
di: Guan, Zhi-Hao
Pubblicazione: (2025)

Enhancing Document-level Translation of Large Language Model via Translation Mixed-instructions
di: Li, Yachao, et al.
Pubblicazione: (2024)

Making Long-Context Language Models Better Multi-Hop Reasoners
di: Li, Yanyang, et al.
Pubblicazione: (2024)

R-BI: Regularized Batched Inputs enhance Incremental Decoding Framework for Low-Latency Simultaneous Speech Translation
di: Guo, Jiaxin, et al.
Pubblicazione: (2024)

A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spotting
di: Li, Yuang, et al.
Pubblicazione: (2023)

Analysis of Volatile Organic Compounds of Different Types of Peppers (Capsicum annuum L.) Using Comprehensive Two‐Dimensional Gas Chromatography With Time‐of‐Flight Mass Spectrometry
di: Huixia Zhu, et al.
Pubblicazione: (2024)

Context-aware Prompt Tuning: Advancing In-Context Learning with Adversarial Methods
di: Blau, Tsachi, et al.
Pubblicazione: (2024)

Multi-Prompting Decoder Helps Better Language Understanding
di: Cheng, Zifeng, et al.
Pubblicazione: (2024)

LLM-enhanced Action-aware Multi-modal Prompt Tuning for Image-Text Matching
di: Tian, Mengxiao, et al.
Pubblicazione: (2025)

Function-to-Style Guidance of LLMs for Code Translation
di: Zhang, Longhui, et al.
Pubblicazione: (2025)

DePT: Decoupled Prompt Tuning
di: Zhang, Ji, et al.
Pubblicazione: (2023)

Prompt, Translate, Fine-Tune, Re-Initialize, or Instruction-Tune? Adapting LLMs for In-Context Learning in Low-Resource Languages
di: Toukmaji, Christopher, et al.
Pubblicazione: (2025)

Towards Better Understanding of Cybercrime: The Role of Fine-Tuned LLMs in Translation
di: Valeros, Veronica, et al.
Pubblicazione: (2024)

Investigating Numerical Translation with Large Language Models
di: Tang, Wei, et al.
Pubblicazione: (2025)

Using Large Language Model for End-to-End Chinese ASR and NER
di: Li, Yuang, et al.
Pubblicazione: (2024)

Self-Correction Makes LLMs Better Parsers
di: Zhang, Ziyan, et al.
Pubblicazione: (2025)

Making LLMs Better Many-to-Many Speech-to-Text Translators with Curriculum Learning
di: Du, Yexing, et al.
Pubblicazione: (2024)

Enhancing Manufacturing Knowledge Access with LLMs and Context-aware Prompting
di: Monka, Sebastian, et al.
Pubblicazione: (2025)

Continuous Speech Tokens Makes LLMs Robust Multi-Modality Learners
di: Yuan, Ze, et al.
Pubblicazione: (2024)

M-Tuning: Prompt Tuning with Mitigated Label Bias in Open-Set Scenarios
di: Liao, Ning, et al.
Pubblicazione: (2023)

Cross-Domain Audio Deepfake Detection: Dataset and Analysis
di: Li, Yuang, et al.
Pubblicazione: (2024)

Hint Tuning: Less Data Makes Better Reasoners
di: Fan, Siqi, et al.
Pubblicazione: (2026)

Mitigating Context-Memory Conflicts in LLMs through Dynamic Cognitive Reconciliation Decoding
di: Zhou, Yigeng, et al.
Pubblicazione: (2026)

Towards Fine-Grained Code-Switch Speech Translation with Semantic Space Alignment
di: Gao, Yan, et al.
Pubblicazione: (2025)

UCorrect: An Unsupervised Framework for Automatic Speech Recognition Error Correction
di: Guo, Jiaxin, et al.
Pubblicazione: (2024)

Making LLMs Optimize Multi-Scenario CUDA Kernels Like Experts
di: Han, Yuxuan, et al.
Pubblicazione: (2026)