ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2408.01505
  4. Cited By
MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a
  Mixture of Dyadic Experts

MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts

2 August 2024
Lin Ning
Harsh Lara
Meiqi Guo
Abhinav Rastogi
    MoMe
    MoE
ArXivPDFHTML

Papers citing "MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts"

1 / 1 papers shown
Title
MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture
  of Shards
MoS: Unleashing Parameter Efficiency of Low-Rank Adaptation with Mixture of Shards
Sheng Wang
Liheng Chen
Pengan Chen
Jingwei Dong
Boyang Xue
Jiyue Jiang
Lingpeng Kong
Chuan Wu
MoE
29
8
0
01 Oct 2024
1