🧑‍🔬 Haoze Sun

🏛️ Affiliations

🏢BaichuanBeijing · China2024–2025 · 3 paperscurrent🏢MeituanBeijing · China2025 · 2 paperscurrent🎓Qingdao University of TechnologyQingdao · China2025 · 2 paperscurrent🏢Huawei TechnologiesShenzhen · China2025 · 1 papercurrent🎓Peking UniversityBeijing · China2013–2023 · 6 papers🎓Nanjing University of Posts and TelecommunicationsNanjing · China2021–2024 · 4 papers🎓Zhejiang UniversityHangzhou · China2013–2016 · 3 papers🎓Hangzhou Dianzi UniversityHangzhou · China2019 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Baichuan-Omni Technical Report (2024 · 18 citations)
   GPT-4o showed what a single model handling several input types can do, but the open-source community had no comparable system.
2. Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction (2025 · 16 citations)
   Cascaded voice assistants chain ASR, an LLM and TTS. This adds latency, compounds errors and discards paralinguistic cues. End-to-end alternatives such as Moshi and GLM-4-Voice tend to lose reasoning ability once speech is added. Baichuan-Audio is a 7B end-to-end audio LLM for real-time bilingual (Chinese/English)…
3. Baichuan Alignment Technical Report (2024 · 5 citations)
   Alignment methods for large language models are usually kept proprietary or described only in fragments. This technical report from Baichuan Inc. and Peking University sets out the full alignment pipeline behind the Baichuan models. The pipeline has three stages. A Prompt Augmentation System (PAS) automatically…
4. BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline (2024 · 2 citations)
   Pre-training corpora largely determine what a large language model can do. Yet many developers, including some that release open weights, keep their data collection and mixing recipes private. Some models are also tuned toward particular benchmarks, which hides their real abilities.

All works

6 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

1. Variational Autoencoder for Semi-Supervised Text Classification ↗Proceedings of the AAAI Conference on Artificial Intelligence · no summary yetWeidi Xu et al.2017 · 203 citations
2. ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning ↗arXiv:2503.19470 · no summary yetMingyang Chen et al.2025 · 99 citations
3. Baichuan-Omni Technical ReportarXiv:2410.08565Yadong Li, Haoze Sun, Mingan Lin, et al.2024 · 18 citations
4. Baichuan-Audio: A Unified Framework for End-to-End Speech InteractionarXiv:2502.17239Tianpeng Li, Jun Liu, Tao Zhang, et al.2025 · 16 citations
5. Baichuan Alignment Technical ReportarXiv:2410.14940Mingan Lin, Fan Yang, Yanjun Shen, et al.2024 · 5 citations
6. BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model BaselinearXiv:2408.15079Guosheng Dong, Da Pan, Yiding Sun, et al.2024 · 2 citations

🤝 Co-authors here

12 of 22 co-authors with a page, the most papers together first.

• Mingan Lin ×4
• Tianpeng Li ×4
• Guosheng Dong ×3
• Tao Zhang ×3
• Da Pan ×2
• Fan Yang ×2
• Jianhua Xu ×2
• Xu Li ×2
• Yanjun Shen ×2
• Zheng Liang ×2
• Bowen Ding
• Chenzheng Zhu

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Proceedings of the AAAI Conference on Artificial Intelligence

🔗 Cited by

Papers of our library cite their works 539 times (of the 149,439 papers whose bibliographies we read); 127 citing papers with a page here →.

Updated 31 October 2026

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