◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Lian Liu

8 papers hereh-index 450 citations14 works total

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

author position
  • first author4
  • middle author4

Across the 8 of 8 papers where every author was matched, so the position is known.

fields
  • cs.AR5
  • cs.CL1
  • cs.DC1
  • cs.LG1
same name
  • Lian Liu — 7 papers, h 5
  • Lian Liu — 5 papers, h 7
  • Lian Liu — 2 papers, h 1
  • Lian Liu — 2 papers, h 3
  • Lian Liu — 2 papers, h 2
  • Lian Liu — 2 papers, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedTowards Efficient Pre-training: Exploring FP4 Precision in Large Language Models

1 citations · 1 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.DC2025

Huawei Cloud Model-as-a-Service on the CloudMatrix384 SuperPod

Ao Xiao, Bangzheng He, Baoquan Zhang +125

Scaled-out MoE LLMs and scaled-up SuperPods create new systems challenges for production Model-as-a-Service (MaaS), requiring disaggregation, low-latency communication, and decentr…

cs.CL2025

Binary Neural Networks for Large Language Model: A Survey

Liangdong Liu, Zhitong Zheng, Cong Wang +2

Large language models (LLMs) have wide applications in the field of natural language processing(NLP), such as GPT-4 and Llama. However, with the exponential growth of model paramet…

cs.AR2025

Make LLM Inference Affordable to Everyone: Augmenting GPU Memory with NDP-DIMM

Lian Liu, Shixin Zhao, Bing Li +6

The billion-scale Large Language Models (LLMs) need deployment on expensive server-grade GPUs with large-storage HBMs and abundant computation capability. As LLM-assisted services…

cs.LG2025★ 1 cited

Towards Efficient Pre-training: Exploring FP4 Precision in Large Language Models

Jiecheng Zhou, Ding Tang, Rong Fu +8

The burgeoning computational demands for training large language models (LLMs) necessitate efficient methods, including quantized training, which leverages low-bit arithmetic opera…

◍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.