◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Congkun Ai

2 papers hereh-index 00 citations2 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.DC1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

collaborators

2 papers

cs.LG2026

DeaMoE: Efficient MoE Structure for Fast Small-Batch Decoding

Zewen Jin, Shen Fu, Zeping Duan +8

Mixture-of-Experts (MoE) models have been widely adopted in real-time interactive applications such as coding assistants, real-time audio-video interaction systems. To meet the ext…

cs.DC2026

HyperParallel-MoE: Multi-Core Interleaved Scheduling for Fast MoE Training on Ascend NPUs

Zewen Jin, Congkun Ai, Guangpeng Zhang +7

Modern Mixture-of-Experts (MoE) models increasingly rely on large-scale AI accelerator clusters for efficient training. Ascend NPUs expose heterogeneous on-chip compute resources,…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.