---
title: "Who cites Oriol Nieto — 102 papers of our library"
description: "102 papers of the Elamur Research library cite the works of Oriol Nieto, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/oriol-nieto/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/oriol-nieto/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Oriol Nieto](https://md.research.elamur.ai/free/en/authors/oriol-nieto/) / cited by

# Who cites Oriol Nieto

121 citations of their works from 102 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · [← Oriol Nieto](https://md.research.elamur.ai/free/en/authors/oriol-nieto/)

1. [**Qwen2.5-Omni Technical Report arXiv:2503.20215**Jin Xu, Zhifang Guo, Jinzheng He, et al.*2025 · 227 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen2-5-omni-technical/)
2. [**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/)
3. [**Qwen3-Omni Technical Report arXiv:2509.17765**Jin Xu, Zhifang Guo, Hangrui Hu, et al.*2025 · 117 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-qwen3-omni-technical-report/)
4. **[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*
5. [**MMAU: A Massive Multi-Task Audio Understanding and Reasoning Benchmark arXiv:2410.19168**S Sakshi, Utkarsh Tyagi, Sonal Kumar, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/sakshi-2024-mmau-massive-multi-task-audio/)
6. [**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/)
7. [**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/)
8. [**Qwen3.5-Omni Technical Report arXiv:2604.15804**Qwen Team*2026 · 29 citations*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-5-omni-technical/)
9. **[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*
10. [**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/)
11. **[Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/yang-2025-holistic-evaluation-large-audio-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chih-Kai Yang, Neo S. Ho, Hung-yi Lee*2025 · 17 citations*
12. **[WildScore: Benchmarking MLLMs in-the-Wild Symbolic Music Reasoning](https://md.research.elamur.ai/free/en/papers/mundada-2025-wildscore-benchmarking-mllms-wild-symbolic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gagan Mundada, Yash Vishe, Amit Namburi, et al.*2025 · 10 citations*
13. **[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*
14. [**ERNIE 5.0 Technical Report arXiv:2602.04705**Haifeng Wang, Hua Wu, Tian Wu, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-ernie-5-0-technical/)
15. [**Thinking with Sound: Audio Chain-of-Thought Enables Multimodal Reasoning in Large Audio-Language Models arXiv:2509.21749**Zhen Xiong, Yujun Cai, Zhecheng Li, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-thinking-sound-audio-chain-thought/)
16. **[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*
17. **[AudioJudge: Understanding What Works in Large Audio Model Based Speech Evaluation](https://md.research.elamur.ai/free/en/papers/manakul-2026-audiojudge-understanding-what-works-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Potsawee Manakul, Woody Haosheng Gan, Michael J Ryan, et al.*2026 · 3 citations*
18. [**Step-Audio-R1 Technical Report arXiv:2511.15848**Fei Tian, Xiangyu Tony Zhang, Yuxin Zhang, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/tian-2025-step-audio-r1-technical/)
19. **[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*
20. **[Octopus: Towards Building the Arabic Speech LLM Suite](https://md.research.elamur.ai/free/en/papers/althubaiti-2025-octopus-building-arabic-speech-llm/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Sara Althubaiti, Vasista Sai Lodagala, Tjad Clark, et al.*2025 · 2 citations*
21. **[HumMusQA: A Human-written Music Understanding QA Benchmark Dataset](https://md.research.elamur.ai/free/en/papers/weck-2026-hummusqa-human-written-music-understanding/) [Workshop on NLP for Music and Audio](https://md.research.elamur.ai/free/en/venues/nlp4musa/)**Benno Weck, Pablo Puentes, Andrea Poltronieri, et al.*2026 · 1 citation*
22. **[Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-listen-pause-reason-perception-grounded/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieyi Wang, Yazhe Niu, Dexuan Xu, et al.*2026 · 1 citation*
23. **[Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation](https://md.research.elamur.ai/free/en/papers/tseng-2026-revisiting-audio-language-pretraining-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei-Cheng Tseng, Xuanru Zhou, Mingyue Huo, et al.*2026 · 1 citation*
24. **[Rubric-Guided Fine-tuning of SpeechLLMs for Multi-Aspect, Multi-Rater L2 Reading-Speech Assessment](https://md.research.elamur.ai/free/en/papers/parikh-2026-rubric-guided-fine-tuning-speechllms/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aditya Kamlesh Parikh, Cristian Tejedor-García, Catia Cucchiarini, et al.*2026 · 1 citation*
25. **[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*
26. **[Afrispeech Semantics: Evaluating Audio–Semantic Reasoning in Spoken Language Models Across Domains and Accents](https://md.research.elamur.ai/free/en/papers/okocha-2026-afrispeech-semantics-evaluating-audio-semantic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chibuzor Okocha, Christan Grant*2026*
27. **[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*
28. **[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*
29. **[Now You Hear Me: Audio Narrative Attacks Against Large Audio–Language Models](https://md.research.elamur.ai/free/en/papers/yu-2026-now-you-hear-me-audio/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ye Yu, Haibo Jin, Yaoning Yu, et al.*2026*
30. **[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*
31. **[Protecting Bystander Privacy via Selective Hearing in Audio LLMs](https://md.research.elamur.ai/free/en/papers/zhan-2026-protecting-bystander-privacy-selective-hearing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Zhan, Guangzhi Sun, Jose Such, et al.*2026*
32. [**Qwen3.8-Omni: Towards Native Omni-Modal Agents arXiv:2609.25611**Qwen Team*2026*](https://md.research.elamur.ai/free/en/papers/qwen-team-2026-qwen3-8-omni-native/)
33. **[Speech-Hands: A Self-Reflection Voice Agentic Approach to Speech Recognition and Audio Reasoning with Omni Perception](https://md.research.elamur.ai/free/en/papers/wan-2026-speech-hands-self-reflection-voice/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Wan, Chao-Han Huck Yang, Jinchuan Tian, et al.*2026*
34. **[Think Smart, Not Hard: Difficulty Adaptive Reasoning for Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/sheng-2026-think-smart-not-hard-difficulty/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Sheng, Shilin Zhou, Chen Gong, et al.*2026*
35. **[WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem](https://md.research.elamur.ai/free/en/papers/wang-2026-wenetspeech-wu-datasets-benchmarks-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengyou Wang, Mingchen Shao, Jingbin Hu, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/oriol-nieto/) — Oriol Nieto