---
title: "Who cites SLM: Bridge the thin gap between — 24 citing papers"
description: "24 papers of the Elamur Research library cite «SLM: Bridge the thin gap between speech and text foundation models», found in their…"
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---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [SLM: Bridge the thin gap between speech and text…](https://md.research.elamur.ai/free/en/papers/wang-2023-slm-bridge-thin-gap-between/) / cited by

# Who cites «SLM: Bridge the thin gap between speech and text foundation models»

24 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «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/)

1. [**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/)
2. [**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/)
3. **[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*
4. **[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*
5. **[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*
6. **[QualiSpeech: A Speech Quality Assessment Dataset with Natural Language Reasoning and Descriptions](https://md.research.elamur.ai/free/en/papers/wang-2025-qualispeech-speech-quality-assessment-dataset/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siyin Wang, Wenyi Yu, Xianzhao Chen, et al.*2025 · 12 citations*
7. [**LuxSQA: Ask Me in Luxembourgish with TTS-Augmented Spoken Question Answering arXiv:2607.02763**Nina Hosseini-Kivanani, Marco Matassoni, Alessio Brutti*2026*](https://md.research.elamur.ai/free/en/papers/hosseini-kivanani-2026-luxsqa-ask-me-luxembourgish-tts/)

17 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/wang-2023-slm-bridge-thin-gap-between/) — SLM: Bridge the thin gap between speech and text foundation models