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M. Liu

3 papers here

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

author position
  • first author1

Across the 1 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • physics.plasm-ph1
ORCID 0000-0001-8028-1049
same name
  • M. Liu — 280 papers
  • M. Liu — 29 papers, h 52
  • M. Liu — 23 papers, h 51
  • M. Liu — 23 papers
  • M. Liu — 16 papers, h 25
  • M. Liu — 14 papers, h 43

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

most citedChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

180 citations · 195 across the 3 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024★ 3 cited

GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot

Aohan Zeng, Zhengxiao Du, Mingdao Liu +5

We introduce GLM-4-Voice, an intelligent and human-like end-to-end spoken chatbot. It supports both Chinese and English, engages in real-time voice conversations, and varies vocal…

cs.CL2024

Scaling Speech-Text Pre-training with Synthetic Interleaved Data

Aohan Zeng, Zhengxiao Du, Mingdao Liu +4

Speech language models (SpeechLMs) accept speech input and produce speech output, allowing for more natural human-computer interaction compared to text-based large language models…

cs.CL2024★ 180 cited

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Team GLM, :, Aohan Zeng +56

We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes…

cs.CL2024

APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Mingdao Liu, Aohan Zeng, Bowen Wang +3

The massive adoption of large language models (LLMs) demands efficient deployment strategies. However, the auto-regressive decoding process, which is fundamental to how most LLMs g…

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