---
title: "Who cites Peter Chen — 182 papers of our library"
description: "182 papers of the Elamur Research library cite the works of Peter Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/peter-chen/cited-by/"
---
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# Who cites Peter Chen

182 citations of their works from 182 papers of our library (of the 141,840 whose bibliographies we read) · 16 with a page here, the most cited first · [← Peter Chen](https://md.research.elamur.ai/free/en/authors/peter-chen/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
2. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 318 citations*
3. [**SALMONN: Towards Generic Hearing Abilities for Large Language Models arXiv:2310.13289**Changli Tang, Wenyi Yu, Guangzhi Sun, et al.*2023 · 203 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/)
4. [**SeamlessM4T: Massively Multilingual & Multimodal Machine Translation arXiv:2308.11596**Seamless Communication, Loic Barrault, Yu-An Chung, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/communication-2023-seamlessm4t-massively-multilingual-multimodal-machine/)
5. [**Seamless: Multilingual Expressive and Streaming Speech Translation arXiv:2312.05187**Seamless Communication, Loic Barrault, Yu-An Chung, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/communication-2023-seamless-multilingual-expressive-streaming-speech/)
6. **[When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*
7. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
8. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
9. **[Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision](https://md.research.elamur.ai/free/en/papers/kharitonov-2023-speak-read-prompt-high-fidelity/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Eugene Kharitonov, Damien Vincent, Zalán Borsos, et al.*2023 · 143 citations*
10. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 75 citations*
11. **[SpiRit-LM: Interleaved Spoken and Written Language Model](https://md.research.elamur.ai/free/en/papers/nguyen-2025-spirit-lm-interleaved-spoken-written/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tu Anh Nguyen, Benjamin Muller, Bokai Yu, et al.*2025 · 61 citations*
12. [**SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models arXiv:2308.16692**Xin Zhang, Dong Zhang, Shimin Li, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechtokenizer-unified-speech-tokenizer-speech/)
13. [**HebDB: a Weakly Supervised Dataset for Hebrew Speech Processing**Arnon Turetzky, Or Tal, Yael Segal-Feldman, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/turetzky-2024-hebdb-weakly-supervised-dataset-hebrew/)
14. **[Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?](https://md.research.elamur.ai/free/en/papers/modica-2026-do-factual-recall-mechanisms-carry/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Luca Modica, Filip Landin, Mehrdad Farahani, et al.*2026*
15. [**Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs arXiv:2601.12494**Hunzalah Hassan Bhatti, Firoj Alam, Shammur Absar Chowdhury*2026*](https://md.research.elamur.ai/free/en/papers/bhatti-2026-multi-task-instruction-tuning-data/)
16. **[PARL: Prompt-based Agents for Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/resendiz-2026-parl-prompt-based-agents-reinforcement/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yarik Menchaca Resendiz, Roman Klinger*2026*

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

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