Shaolei Zhang
Shaolei Zhang has 4 papers in our library, in 2023–2025, most of them on Language models & pretraining, Dialogue systems, Speech & spoken language; often with Yang Feng, Qingkai Fang, Yan Zhou.
OpenAlex · ORCID · h-index 10 · 33 works · 226 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 220 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5945
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksSignal Processing · 2 worksComputer Vision and Pattern Recognition · 1 work
🧭 Topics 4Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 1 workLanguage models & pretraining · 1 workDialogue systems · 1 workSpeech & spoken language · 1 work
Works by year
2020s
Papers
- LLaMA-Omni: Seamless Speech Interaction with Large Language Models (2024 · 91 citations)
Commercial systems such as GPT-4o allow spoken, real-time conversations with LLMs, but there is little open work on building similar speech interfaces on top of open-source LLMs. - BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models (2023 · 85 citations)
Most large language models are trained mainly on English text and English instructions, so they perform worse in other languages. - TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space (2024 · 57 citations)
LLMs sometimes give fluent but false answers even when their parameters hold the correct facts. TruthX is an inference-time method that reduces such hallucinations by editing the model's hidden activations. The authors build triplets of a question, a truthful answer and an untruthful answer, feed both versions to the… - LLaMA-Omni 2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis (2025 · 20 citations)
The paper addresses how to build a spoken chatbot that is smart, responds quickly, and sounds natural, without the huge speech corpora that native SpeechLMs need.
All works
- LLaMA-Omni: Seamless Speech Interaction with Large Language ModelsarXiv:2409.06666Qingkai Fang, Shoutao Guo, Yan Zhou, et al.2024 · 91 citations
- BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language ModelsarXiv:2306.10968Shaolei Zhang, Qingkai Fang, Zhuocheng Zhang, et al.2023 · 85 citations
- TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful SpaceAnnual Meeting of the Association for Computational Linguistics (ACL)Shaolei Zhang, Tian Yu, Yang Feng2024 · 57 citations
- LLaMA-Omni 2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech SynthesisAnnual Meeting of the Association for Computational Linguistics (ACL)Qingkai Fang, Yan Zhou, Shoutao Guo, et al.2025 · 20 citations
- Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translation ↗Findings of the Association for Computational Linguistics: EMNLP 2022 · no summary yetShoutao Guo, Shaolei Zhang, Yang Feng2022 · 19 citations
Co-authors here
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2025, ACL 2024
- Findings of the Association for Computational Linguistics: EMNLP 2022
Cited by
Updated
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