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Songxiang Liu

10 papers hereh-index 5426 citations10 works total

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

author position
  • middle author9
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.SD4
  • cs.CV2
  • eess.AS2
  • cs.AI1
  • cs.CL1
same name
  • Songxiang Liu — 24 papers, h 22
  • Songxiang Liu — 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
20242026
most citedKimi-Audio Technical Report

2 citations · 3 across the 10 of their papers we have counts for

collaborators
Showing cs.SDShow all

4 papers · 1 filter

cs.SD2026

UniAudio 2.0: A Unified Audio Language Model with Text-Aligned Factorized Audio Tokenization

Dongchao Yang, Yuanyuan Wang, Dading Chong +3

We study two foundational problems in audio language models: (1) how to design an audio tokenizer that can serve as an intermediate representation for both understanding and genera…

cs.SD2026

HeartMuLa: A Family of Open Sourced Music Foundation Models

Dongchao Yang, Yuxin Xie, Yuguo Yin +26

We present a family of open-source Music Foundation Models designed to advance large-scale music understanding and generation across diverse tasks and modalities. Our framework con…

cs.SD2025

ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling

Dongchao Yang, Songxiang Liu, Haohan Guo +9

Recent advancements in audio language models have underscored the pivotal role of audio tokenization, which converts audio signals into discrete tokens, thereby facilitating the ap…

cs.SD2025★ 1 cited

Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens

Xinsheng Wang, Mingqi Jiang, Ziyang Ma +22

Recent advancements in large language models (LLMs) have driven significant progress in zero-shot text-to-speech (TTS) synthesis. However, existing foundation models rely on multi-…

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