---
title: "Who cites Benjamin Bolte"
description: "549 papers of the Elamur Research library cite the works of Benjamin Bolte, found in their bibliographies; the most cited first."
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---
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# Who cites Benjamin Bolte

612 citations of their works from 549 papers of our library (of the 140,884 whose bibliographies we read) · 39 with a page here, the most cited first · [← Benjamin Bolte](https://md.research.elamur.ai/free/en/authors/benjamin-bolte/)

1. [**Robust Speech Recognition via Large-Scale Weak Supervision**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,497 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
2. [**The Rise and Potential of Large Language Model Based Agents: A Survey**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,262 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)
3. [**AudioLM: a Language Modeling Approach to Audio Generation**Zalan Borsos, Raphael Marinier, Damien Vincent, et al.*2022 · 570 citations*](https://md.research.elamur.ai/free/en/papers/borsos-2022-audiolm-language-modeling-approach-audio/)
4. [**High Fidelity Neural Audio Compression**Alexandre Defossez, Jade Copet, Gabriel Synnaeve, et al.*2022 · 412 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2022-high-fidelity-neural-audio-compression/)
5. [**SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities**Dong Zhang, Shimin Li, Xin Zhang, et al.*2023 · 346 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechgpt-empowering-large-language-models/)
6. [**Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers**Chengyi Wang, Sanyuan Chen, Yu Wu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-neural-codec-language-models-zero/)
7. [**SeamlessM4T: Massively Multilingual & Multimodal Machine Translation**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/)
8. [**Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models**Yunfei Chu, Jin Xu, Xiaohuan Zhou, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-qwen-audio-advancing-universal/)
9. [**Seamless: Multilingual Expressive and Streaming Speech Translation**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/)
10. [**AudioPaLM: A Large Language Model That Can Speak and Listen**Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, et al.*2023 · 169 citations*](https://md.research.elamur.ai/free/en/papers/rubenstein-2023-audiopalm-large-language-model-that/)
11. [**Moshi: a speech-text foundation model for real-time dialogue**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/)
12. [**FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN**Milind Agarwal, Sweta Agrawal, Antonios Anastasopoulos, et al.*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/)
13. [**SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models**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/)
14. [**Scaling Laws for Generative Mixed-Modal Language Models**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)
15. [**N-Shot Benchmarking of Whisper on Diverse Arabic Speech Recognition**Bashar Talafha, Abdul Waheed, Muhammad Abdul-Mageed*2023 · 30 citations*](https://md.research.elamur.ai/free/en/papers/talafha-2023-n-shot-benchmarking-whisper-diverse/)
16. [**How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech**Aditya Yedetore, Tal Linzen, Robert Frank, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/yedetore-2023-how-poor-is-stimulus-evaluating/)
17. [**On the Robustness of Arabic Speech Dialect Identification**Peter Sullivan, AbdelRahim Elmadany, Muhammad Abdul-Mageed*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/sullivan-2023-robustness-arabic-speech-dialect-identification/)
18. [**ADI-20: Arabic Dialect Identification dataset and models**Haroun Elleuch, Salima Mdhaffar, Yannick Esteve, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/elleuch-2025-adi-20-arabic-dialect-identification/)
19. [**Towards a Unified Benchmark for Arabic Pronunciation Assessment: Quranic Recitation as Case Study**Yassine El Kheir, Omnia Ibrahim, Amit Meghanani, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/kheir-2025-towards-unified-benchmark-arabic-pronunciation/)
20. [**Open Universal Arabic ASR Leaderboard**Yingzhi Wang, Anas Alhmoud, Muhammad Alqurishi*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-open-universal-arabic-asr-leaderboard/)
21. [**IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling**Zébulon Goriely, Paula Buttery*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/goriely-2025-ipa-childes-g2p-feature-rich/)
22. [**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/)
23. [**Beyond Orthography: Automatic Recovery of Short Vowels and Dialectal Sounds in Arabic**Yassine El Kheir, Hamdy Mubarak, Ahmed Ali, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kheir-2024-beyond-orthography-automatic-recovery-short/)
24. [**LinTO Audio and Textual Datasets to Train and Evaluate Automatic Speech Recognition in Tunisian Arabic Dialect**Hedi Naouara, Jean-Pierre Lorre, Jerome Louradour*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/naouara-2025-linto-audio-textual-datasets-train/)
25. [**Arabic Multimodal Machine Learning: Datasets, Applications, Approaches, and Challenges**Abdelhamid Haouhat, Slimane Bellaouar, Attia Nehar, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/haouhat-2025-arabic-multimodal-machine-learning-datasets/)
26. [**J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling**Wataru Nakata, Kentaro Seki, Hitomi Yanaka, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/nakata-2026-j-chat-japanese-large-scale/)
27. [**SAGE: Spliced-Audio Generated Data for Enhancing Foundational Models in Low-Resource Arabic-English Code-Switched Speech Recognition**Muhammad Umar Farooq, Oscar Saz*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/farooq-2025-sage-spliced-audio-generated-data/)
28. [**Arabic Speech Recognition of zero-resourced Languages: A case of Shehri (Jibbali) Language**Norah A. Alrashoudi, Omar Said Alshahri, Hend Al-Khalifa*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/alrashoudi-2024-arabic-speech-recognition-zero-resourced/)
29. [**Ara-Best-RQ: Multi Dialectal Arabic SSL**Haroun Elleuch, Ryan Whetten, Salima Mdhaffar, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elleuch-2026-ara-best-rq-multi-dialectal/)
30. [**Enhancing TTS Stability in Hebrew using Discrete Semantic Units**Ella Zeldes, Or Tal, Yossi Adi*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zeldes-2024-enhancing-tts-stability-hebrew-using/)
31. [**A framework for analyzing concept representations in neural models**Burin Naowarat, Hao Tang, Sharon Goldwater*2026*](https://md.research.elamur.ai/free/en/papers/naowarat-2026-framework-analyzing-concept-representations-neural/)
32. [**A Fusion-Aware Two-Stage Framework for Mispronunciation Detection and Diagnosis in Low-Resource Modern Standard Arabic**Jing Yang, Shuqing Zhang, Yongyi Deng, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yang-2026-fusion-aware-two-stage-framework/)
33. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
34. [**ChildTalk: A Multi-Dialect Chinese Child Speech Corpus with Full-Length Child–Caregiver Conversations for Speech Recognition**Jiaming Zhou, Yujie Guo, Shiwan Zhao, et al.*2026*](https://md.research.elamur.ai/free/en/papers/zhou-2026-childtalk-multi-dialect-chinese-child/)
35. [**Do Factual Recall Mechanisms Carry over from Text to Speech in Multimodal Language Models?**Luca Modica, Filip Landin, Mehrdad Farahani, et al.*2026*](https://md.research.elamur.ai/free/en/papers/modica-2026-do-factual-recall-mechanisms-carry/)
36. [**Dynamic Layer Selection for Efficient Tone Recognition in Self-Supervised Speech Models**Saint Germes B. BENGONO OBIANG, Norbert TSOPZE, Paulin MELATAGIA YONTA*2026*](https://md.research.elamur.ai/free/en/papers/obiang-2026-dynamic-layer-selection-efficient-tone/)
37. [**IQRA 2026: Interspeech Challenge on Automatic Pronunciation Assessment for Modern Standard Arabic (MSA)**Yassine El Kheir, Amit Meghanani, Mostafa Shahin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kheir-2026-iqra-2026-interspeech-challenge-automatic/)
38. [**Probing Discrete Speech Tokens of Spoken Language Models**Sven Naber, Julia Koch, Pranav Singh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/naber-2026-probing-discrete-speech-tokens-spoken/)
39. [**Tools for Estimating the Perceived Level of Phonetic Reduction**Nigel Ward, Javier Vazquez, Emma (Danny) R. Boushka, et al.*2026*](https://md.research.elamur.ai/free/en/papers/ward-2026-tools-estimating-perceived-level-phonetic/)

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

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