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Long Zhou

24 papers hereh-index 2811.2k citations68 works total

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

author position
  • first author4
  • middle author18

Across the 22 of 24 papers where every author was matched, so the position is known.

fields
  • cs.CL9
  • eess.AS7
  • cs.SD4
  • cs.SE2
  • cs.CV1
  • cs.LG1
same name
  • Long Zhou — 5 papers
  • Long Zhou — 4 papers, h 9
  • Long Zhou — 2 papers, h 2
  • Long Zhou — 2 papers, h 11
  • Long Zhou — 2 papers, h 1
  • Long Zhou — 1 paper

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
20172026
most citedCodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

416 citations · 640 across the 20 of their papers we have counts for

collaborators
Showing cs.SDShow all

4 papers · 1 filter

cs.SD2025

U-Codec: Ultra Low Frame-rate Neural Speech Codec for Fast High-fidelity Speech Generation

Xusheng Yang, Long Zhou, Wenfu Wang +6

We propose \textbf{U-Codec}, an \textbf{U}ltra low frame-rate neural speech \textbf{Codec} that achieves high-fidelity reconstruction and fast speech generation at an extremely low…

cs.SD2024

Investigating Neural Audio Codecs for Speech Language Model-Based Speech Generation

Jiaqi Li, Dongmei Wang, Xiaofei Wang +13

Neural audio codec tokens serve as the fundamental building blocks for speech language model (SLM)-based speech generation. However, there is no systematic understanding on how the…

cs.SD2022★ 2 cited

Joint Pre-Training with Speech and Bilingual Text for Direct Speech to Speech Translation

Kun Wei, Long Zhou, Ziqiang Zhang +5

Direct speech-to-speech translation (S2ST) is an attractive research topic with many advantages compared to cascaded S2ST. However, direct S2ST suffers from the data scarcity probl…

cs.SD2022

Speech Pre-training with Acoustic Piece

Shuo Ren, Shujie Liu, Yu Wu +2

Previous speech pre-training methods, such as wav2vec2.0 and HuBERT, pre-train a Transformer encoder to learn deep representations from audio data, with objectives predicting eithe…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.