---
title: "Who cites Shengmin Jiang — 66 papers of our library"
description: "66 papers of the Elamur Research library cite the works of Shengmin Jiang, found in their bibliographies; the most cited first."
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---
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# Who cites Shengmin Jiang

75 citations of their works from 66 papers of our library (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · [← Shengmin Jiang](https://md.research.elamur.ai/free/en/authors/shengmin-jiang/)

1. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
2. **[Recent Advances in Speech Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/cui-2025-recent-advances-speech-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao, et al.*2025 · 69 citations*
3. [**GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot arXiv:2412.02612**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-glm-4-voice-intelligent/)
4. [**Kimi-Audio Technical Report arXiv:2504.18425**KimiTeam, Ding Ding, Zeqian Ju, et al.*2025 · 57 citations*](https://md.research.elamur.ai/free/en/papers/kimiteam-2025-kimi-audio-technical-report/)
5. [**Step-Audio 2 Technical Report arXiv:2507.16632**Boyong Wu, Chao Yan, Chen Hu, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-step-audio-2-technical/)
6. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
7. **[OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation](https://md.research.elamur.ai/free/en/papers/zhang-2025-omniflatten-end-end-gpt-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinglin Zhang, Luyao Cheng, Chong Deng, et al.*2025 · 27 citations*
8. [**Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction arXiv:2502.11946**Ailin Huang, Boyong Wu, Bruce Wang, et al.*2025 · 25 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-step-audio-unified-understanding/)
9. [**MiMo-Audio: Audio Language Models are Few-Shot Learners arXiv:2512.23808**Xiaomi LLM-Core Team, Dong Zhang, Gang Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-llm-mimo-audio-audio-language/)
10. **[LLaMA-Omni 2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis](https://md.research.elamur.ai/free/en/papers/fang-2025-llama-omni-2-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingkai Fang, Yan Zhou, Shoutao Guo, et al.*2025 · 20 citations*
11. [**Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction arXiv:2502.17239**Tianpeng Li, Jun Liu, Tao Zhang, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-audio-unified-framework/)
12. **[VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models](https://md.research.elamur.ai/free/en/papers/cui-2025-voxeval-benchmarking-knowledge-understanding-capabilities/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqian Cui, Xiaoqi Jiao, Ziqiao Meng, et al.*2025 · 9 citations*
13. **[XY-Tokenizer: Mitigating the Semantic-Acoustic Conflict in Low-Bitrate Speech Codecs](https://md.research.elamur.ai/free/en/papers/gong-2026-xy-tokenizer-mitigating-semantic-acoustic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yitian Gong, Luozhijie Jin, Kuangwei Chen, et al.*2026 · 4 citations*
14. **[Chronological Thinking in Full-Duplex Spoken Dialogue Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-chronological-thinking-full-duplex-spoken/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Donghang Wu, Haoyang Zhang, Chen Chen, et al.*2026 · 3 citations*
15. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations*
16. **[Do We Need Distinct Representations for Every Speech Token? Unveiling and Exploiting Redundancy in Large Speech Language Models](https://md.research.elamur.ai/free/en/papers/xiang-2026-do-we-need-distinct-representations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bajian Xiang, Tingwei Guo, Xuan Chen, et al.*2026 · 2 citations*
17. **[Efficient Training for Cross-lingual Speech Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-efficient-training-cross-lingual-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yan Zhou, Qingkai Fang, Yun Hong, et al.*2026 · 2 citations*
18. **[UltraEval-Audio: A Unified Framework for Comprehensive Evaluation of Audio Foundation Models](https://md.research.elamur.ai/free/en/papers/shi-2026-ultraeval-audio-unified-framework-comprehensive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qundong Shi, Jie Zhou, Biyuan Lin, et al.*2026 · 1 citation*
19. **[AffectCodec: Emotion-Preserving Neural Speech Codec for Expressive Speech Modeling](https://md.research.elamur.ai/free/en/papers/shi-2026-affectcodec-emotion-preserving-neural-speech/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Shi, Hongfei Du, Xinyuan Song, et al.*2026*
20. **[BatonVoice: An Operationalist Framework for Enhancing Controllable Speech Synthesis with Linguistic Intelligence from LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-batonvoice-operationalist-framework-enhancing-controllable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Wang, Ruotian Ma, Xingyu Chen, et al.*2026*
21. **[Beyond Transcription: Unified Audio Schema for Perception-Aware AudioLLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-transcription-unified-audio-schema/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linhao Zhang, Yuhan Song, Aiwei Liu, et al.*2026*
22. **[DIFFA-2: A Practical Diffusion Large Language Model for General Audio Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-diffa-2-practical-diffusion-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaming Zhou, Xuxin Cheng, Shiwan Zhao, et al.*2026*
23. **[ORCA: Open-ended Response Correctness Assessment for Audio Question Answering](https://md.research.elamur.ai/free/en/papers/sedlacek-2026-orca-open-ended-response-correctness/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Šimon Sedláček, Sara Barahona, Cecilia Bolaños, et al.*2026*
24. **[RealTalk-CN: A Realistic Chinese Speech Task-Oriented Dialogue Benchmark with Cross-Modal Analysis](https://md.research.elamur.ai/free/en/papers/wang-2026-realtalk-cn-realistic-chinese-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Enzhi Wang, Jiaming Zhou, Yuhang Jia, et al.*2026*
25. **[SpeechLM for Automatic Speech Recognition in Low-resource Languages](https://md.research.elamur.ai/free/en/papers/riyadh-2026-speechlm-automatic-speech-recognition-low/) [Speech Language Models in Low-Resource Settings: Performance, Evaluation, and Bias Analysis (SPEAKABLE) @ LREC](https://md.research.elamur.ai/free/en/venues/speakable/)**Md Abdur Razzaq Riyadh, Eneko Agirre, Eva Navas, et al.*2026*

41 more citing papers of our library have no page here yet.

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