---
title: "Who cites Pengyu Wang — 169 papers of our library"
description: "169 papers of the Elamur Research library cite the works of Pengyu Wang, found in their bibliographies; the most cited first."
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---
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# Who cites Pengyu Wang

169 citations of their works from 169 papers of our library (of the 149,439 whose bibliographies we read) · 52 with a page here, the most cited first · [← Pengyu Wang](https://md.research.elamur.ai/free/en/authors/pengyu-wang/)

1. **[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 · 320 citations*
2. [**Qwen2-Audio Technical Report arXiv:2407.10759**Yunfei Chu, Jin Xu, Qian Yang, et al.*2024 · 238 citations*](https://md.research.elamur.ai/free/en/papers/chu-2024-qwen2-audio-technical-report/)
3. [**Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding arXiv:2306.02858**Hang Zhang, Xin Li, Lidong Bing*2023 · 238 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-video-llama-instruction-tuned-audio/)
4. [**SALMONN: Towards Generic Hearing Abilities for Large Language Models arXiv:2310.13289**Changli Tang, Wenyi Yu, Guangzhi Sun, et al.*2023 · 209 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-salmonn-towards-generic-hearing-abilities/)
5. [**NExT-GPT: Any-to-Any Multimodal LLM arXiv:2309.05519**Shengqiong Wu, Hao Fei, Leigang Qu, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-next-gpt-any-any-multimodal/)
6. [**Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models arXiv:2311.07919**Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/)
7. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 157 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
8. [**PandaGPT: One Model To Instruction-Follow Them All arXiv:2305.16355**Yixuan Su, Tian Lan, Huayang Li, et al.*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/su-2023-pandagpt-one-model-instruction-follow/)
9. **[AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension](https://md.research.elamur.ai/free/en/papers/yang-2024-air-bench-benchmarking-large-audio/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Yang, Jin Xu, Wenrui Liu, et al.*2024 · 112 citations*
10. [**LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding arXiv:2306.17107**Yanzhe Zhang, Ruiyi Zhang, Jiuxiang Gu, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llavar-enhanced-visual-instruction-tuning/)
11. **[AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling](https://md.research.elamur.ai/free/en/papers/zhan-2024-anygpt-unified-multimodal-llm-discrete/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jun Zhan, Junqi Dai, Jiasheng Ye, et al.*2024 · 95 citations*
12. [**CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language Models arXiv:2412.10117**Zhihao Du, Yuxuan Wang, Qian Chen, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/du-2024-cosyvoice-2-scalable-streaming-speech/)
13. [**LLaMA-Omni: Seamless Speech Interaction with Large Language Models arXiv:2409.06666**Qingkai Fang, Shoutao Guo, Yan Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/fang-2024-llama-omni-seamless-speech-interaction/)
14. **[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 · 77 citations*
15. **[VoiceBench: Benchmarking LLM-Based Voice Assistants](https://md.research.elamur.ai/free/en/papers/chen-2026-voicebench-benchmarking-llm-based-voice/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yiming Chen, Xianghu Yue, Chen Zhang, et al.*2026 · 74 citations*
16. [**Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming arXiv:2408.16725**Zhifei Xie, Changqiao Wu*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-mini-omni-language-models-hear/)
17. **[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*
18. [**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/)
19. **[SLM: Bridge the thin gap between speech and text foundation models](https://md.research.elamur.ai/free/en/papers/wang-2023-slm-bridge-thin-gap-between/) [IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)](https://md.research.elamur.ai/free/en/venues/ieee-automatic-speech-recognition-and-understanding-workshop-asru/)**Mingqiu Wang, Wei Han, Izhak Shafran, et al.*2023 · 54 citations*
20. [**SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models arXiv:2308.16692**Xin Zhang, Dong Zhang, Shimin Li, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechtokenizer-unified-speech-tokenizer-speech/)
21. [**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/)
22. [**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/)
23. **[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*
24. **[Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xie Zhifei, Mingbao Lin, Zihang Liu, et al.*2025 · 25 citations*
25. [**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/)
26. **[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*
27. **[Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs](https://md.research.elamur.ai/free/en/papers/xia-2025-beyond-chain-thought-survey-chain/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yu Xia, Rui Wang, Xu Liu, et al.*2025 · 19 citations*
28. **[Distilling an End-to-End Voice Assistant Without Instruction Training Data](https://md.research.elamur.ai/free/en/papers/held-2025-distilling-end-end-voice-assistant/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Held, Yanzhe Zhang, Minzhi Li, et al.*2025 · 18 citations*
29. [**Baichuan-Omni Technical Report arXiv:2410.08565**Yadong Li, Haoze Sun, Mingan Lin, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-baichuan-omni-technical-report/)
30. [**Scaling Speech-Text Pre-training with Synthetic Interleaved Data arXiv:2411.17607**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-speech-text-pre-training/)
31. **[Paralinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation](https://md.research.elamur.ai/free/en/papers/kim-2024-paralinguistics-aware-speech-empowered-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Heeseung Kim, Soonshin Seo, Kyeongseok Jeong, et al.*2024 · 13 citations*
32. **[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*
33. **[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*
34. **[Audio Jailbreak: An Open Comprehensive Benchmark for Jailbreaking Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-audio-jailbreak-open-comprehensive-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zirui Song, Qian Jiang, Mingxuan Cui, et al.*2026 · 3 citations*
35. **[SpeechLLM-as-Judges: Towards General and Interpretable Speech Quality Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2026-speechllm-as-judges-general-interpretable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wang, Jinghua Zhao, Yifan Yang, et al.*2026 · 3 citations*
36. **[Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World](https://md.research.elamur.ai/free/en/papers/sadasivan-2026-attacker-s-noise-can-manipulate/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Vinu Sankar Sadasivan, Soheil Feizi, Rajiv Mathews, et al.*2026 · 2 citations*
37. **[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*
38. [**MENASpeechBank: A Reference Voice Bank with Persona-Conditioned Multi-Turn Conversations for AudioLLMs arXiv:2602.07036**Zien Sheikh Ali, Hunzalah Hassan Bhatti, Rabindra Nath Nandi, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-menaspeechbank-reference-voice-bank-persona/)
39. **[Bias in the Ear of the Listener: Assessing Sensitivity in Audio Language Models Across Linguistic, Demographic, and Positional Variations](https://md.research.elamur.ai/free/en/papers/wei-2026-bias-ear-listener-assessing-sensitivity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sheng-Lun Wei, Yu-Ling Liao, Yen-Hua Chang, et al.*2026 · 1 citation*
40. **[CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-codeevo-interaction-driven-synthesis-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiushi Sun, Jingyang Gong, Lei Li, et al.*2026 · 1 citation*
41. **[From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models](https://md.research.elamur.ai/free/en/papers/tong-2026-static-inference-dynamic-interaction-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junlong Tong, Zilong Wang, YuJie Ren, et al.*2026 · 1 citation*
42. **[PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics](https://md.research.elamur.ai/free/en/papers/naik-2026-pbebench-multi-step-programming-examples/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Atharva Naik, Darsh Agrawal, Prakam, et al.*2026 · 1 citation*
43. **[SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-see-signal-embedding-energy-quantifying/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanhe Zhang, Jiayu Tian, Yibo Zhang, et al.*2026 · 1 citation*
44. **[Unlocking Large Audio-Language Models for Interactive Language Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-unlocking-large-audio-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongfu Liu, Zhouying Cui, Xiangming Gu, et al.*2026 · 1 citation*
45. **[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*
46. **[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*
47. **[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*
48. **[Learning Flexible Large Multimodal Models with Arbitrary Modality Combinations](https://md.research.elamur.ai/free/en/papers/zhao-2026-learning-flexible-large-multimodal-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhao, Kangqi Ni, Jie Peng, et al.*2026*
49. **[PED: Route-Decoupled Diagnostics for Persona Consistency in Spoken Agents](https://md.research.elamur.ai/free/en/papers/liu-2026-ped-route-decoupled-diagnostics-persona/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weihao Liu, Junrui Wei, Zhao Zhang, et al.*2026*
50. **[RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios](https://md.research.elamur.ai/free/en/papers/zhang-2026-rsa-bench-benchmarking-audio-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Zhang, Kaiwen Luo, Liang Lin, et al.*2026*
51. **[S2ST-Omni: Hierarchical Language-Aware SpeechLLM Adaptation for Multilingual Speech-to-Speech Translation](https://md.research.elamur.ai/free/en/papers/pan-2026-s2st-omni-hierarchical-language-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu Pan, Xiongfei Wu, Yang Yuguang, et al.*2026*
52. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026*

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

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