Image de couverture de livre

MoPE: Mixture of Prefix Experts for Zero-Shot Dialogue State Tracking

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tang, Tianwen, Zhu, Tong, Liu, Haodong, Bai, Yin, Cheng, Jia, Chen, Wenliang
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

MoPE: Mixture of Prompt Experts for Parameter-Efficient and Scalable Multimodal Fusion
par: Jiang, Ruixiang, et autres
Publié: (2024)

MoPE: A Mixture of Password Experts for Improving Password Guessing
par: Duan, Mingjian, et autres
Publié: (2025)

Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts
par: Zhu, Tong, et autres
Publié: (2024)

GEM: Graph-Enhanced Mixture-of-Experts with ReAct Agents for Dialogue State Tracking
par: Zhu, Ziqi, et autres
Publié: (2026)

Zero-Shot Cross-Domain Dialogue State Tracking via Dual Low-Rank Adaptation
par: Luo, Xiang, et autres
Publié: (2024)

DiffusionDialog: A Diffusion Model for Diverse Dialog Generation with Latent Space
par: Xiang, Jianxiang, et autres
Publié: (2024)

UNO-DST: Leveraging Unlabelled Data in Zero-Shot Dialogue State Tracking
par: Li, Chuang, et autres
Publié: (2023)

Schema Augmentation for Zero-Shot Domain Adaptation in Dialogue State Tracking
par: Richardson, Christopher, et autres
Publié: (2024)

Understanding and Leveraging the Expert Specialization of Context Faithfulness in Mixture-of-Experts LLMs
par: Bai, Jun, et autres
Publié: (2025)

Diverse and Effective Synthetic Data Generation for Adaptable Zero-Shot Dialogue State Tracking
par: Finch, James D., et autres
Publié: (2024)

Controllable and Diverse Data Augmentation with Large Language Model for Low-Resource Open-Domain Dialogue Generation
par: Liu, Zhenhua, et autres
Publié: (2024)

LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-training
par: Zhu, Tong, et autres
Publié: (2024)

Linear-MoE: Linear Sequence Modeling Meets Mixture-of-Experts
par: Sun, Weigao, et autres
Publié: (2025)

Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
par: Wei, Tianwen, et autres
Publié: (2024)

ReacTOD: Bounded Neuro-Symbolic Agentic NLU for Zero-Shot Dialogue State Tracking
par: Lin, Yanjun, et autres
Publié: (2026)

MoBiLE: Efficient Mixture-of-Experts Inference on Consumer GPU with Mixture of Big Little Experts
par: Zhao, Yushu, et autres
Publié: (2025)

Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity
par: Tang, Yehui, et autres
Publié: (2025)

LLaMA-MoE v2: Exploring Sparsity of LLaMA from Perspective of Mixture-of-Experts with Post-Training
par: Qu, Xiaoye, et autres
Publié: (2024)

EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models
par: Jing, Linglin, et autres
Publié: (2025)

DiaMoE-TTS: A Unified IPA-Based Dialect TTS Framework with Mixture-of-Experts and Parameter-Efficient Zero-Shot Adaptation
par: Chen, Ziqi, et autres
Publié: (2025)

MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric
par: Lin, Haokun, et autres
Publié: (2024)

MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation
par: Yuan, Zheng, et autres
Publié: (2026)

Enhancing Dialogue State Tracking Models through LLM-backed User-Agents Simulation
par: Niu, Cheng, et autres
Publié: (2024)

Mixture of insighTful Experts (MoTE): The Synergy of Thought Chains and Expert Mixtures in Self-Alignment
par: Liu, Zhili, et autres
Publié: (2024)

MoDEM: Mixture of Domain Expert Models
par: Simonds, Toby, et autres
Publié: (2024)

MoMoE: Mixture of Moderation Experts Framework for AI-Assisted Online Governance
par: Goyal, Agam, et autres
Publié: (2025)

RotMoLE: Enhancing Mixture of Low-Rank Experts through Rotational Gating Mechanism
par: Sun, Mengyang, et autres
Publié: (2026)

$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts
par: Chen, Guanjie, et autres
Publié: (2024)

CorrectionLM: Self-Corrections with SLM for Dialogue State Tracking
par: Lee, Chia-Hsuan, et autres
Publié: (2024)

MH-MoE: Multi-Head Mixture-of-Experts
par: Huang, Shaohan, et autres
Publié: (2024)

$\infty$-MoE: Generalizing Mixture of Experts to Infinite Experts
par: Takashiro, Shota, et autres
Publié: (2026)

MaskMoE: Boosting Token-Level Learning via Routing Mask in Mixture-of-Experts
par: Su, Zhenpeng, et autres
Publié: (2024)

MobileMoE: Scaling On-Device Mixture of Experts
par: Chen, Yanbei, et autres
Publié: (2026)

MoFE: Mixture of Frozen Experts Architecture
par: Seo, Jean, et autres
Publié: (2025)

OrchestraLLM: Efficient Orchestration of Language Models for Dialogue State Tracking
par: Lee, Chia-Hsuan, et autres
Publié: (2023)

Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models
par: Wang, Zihan, et autres
Publié: (2025)

DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
par: Dai, Damai, et autres
Publié: (2024)

Mixture of Neuron Experts
par: Cheng, Runxi, et autres
Publié: (2025)

TiMoE: Time-Aware Mixture of Language Experts
par: Faro, Robin, et autres
Publié: (2025)

Router Upcycling: Leveraging Mixture-of-Routers in Mixture-of-Experts Upcycling
par: Ran, Junfeng, et autres
Publié: (2025)