---
title: "Who cites Gregory Diamos — 468 papers of our library"
description: "468 papers of the Elamur Research library cite the works of Gregory Diamos, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/gregory-diamos/cited-by/"
---
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# Who cites Gregory Diamos

516 citations of their works from 468 papers of our library (of the 149,439 whose bibliographies we read) · 92 with a page here, the most cited first · [← Gregory Diamos](https://md.research.elamur.ai/free/en/authors/gregory-diamos/)

1. [**Language Models are Few-Shot Learners arXiv:2005.14165**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 14,178 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
2. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 11,325 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
3. [**LLaMA: Open and Efficient Foundation Language Models arXiv:2302.13971**Hugo Touvron, Thibaut Lavril, Gautier Izacard, et al.*2023 · 9,603 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-open-efficient-foundation-language/)
4. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,767 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
5. [**mixup: Beyond Empirical Risk Minimization arXiv:1710.09412**Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, et al.*2017 · 4,928 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-mixup-empirical-risk-minimization/)
6. **[SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition](https://md.research.elamur.ai/free/en/papers/park-2019-specaugment-simple-data-augmentation-method/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Daniel S. Park, William Chan, Yu Zhang, et al.*2019 · 3,837 citations*
7. [**Scaling Laws for Neural Language Models arXiv:2001.08361**Jared Kaplan, Sam McCandlish, Tom Henighan, et al.*2020 · 3,434 citations*](https://md.research.elamur.ai/free/en/papers/kaplan-2020-scaling-laws-neural-language-models/)
8. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
9. [**Robust Speech Recognition via Large-Scale Weak Supervision arXiv:2212.04356**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,546 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
10. [**Deep Speech 2: End-to-End Speech Recognition in English and Mandarin arXiv:1512.02595**Dario Amodei, Rishita Anubhai, Eric Battenberg, et al.*2015 · 2,341 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2015-deep-speech-2-end-end/)
11. [**Unsupervised Data Augmentation for Consistency Training arXiv:1904.12848**Qizhe Xie, Zihang Dai, Eduard Hovy, et al.*2019 · 1,871 citations*](https://md.research.elamur.ai/free/en/papers/xie-2019-unsupervised-data-augmentation-consistency-training/)
12. [**Layer Normalization arXiv:1607.06450**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
13. [**Attention-Based Models for Speech Recognition arXiv:1506.07503**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
14. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
15. **[Reproducible scaling laws for contrastive language-image learning](https://md.research.elamur.ai/free/en/papers/cherti-2022-reproducible-scaling-laws-contrastive-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Mehdi Cherti, Romain Beaumont, Ross Wightman, et al.*2022 · 769 citations*
16. [**Common Voice: A Massively-Multilingual Speech Corpus arXiv:1912.06670**Rosana Ardila, Megan Branson, Kelly Davis, et al.*2019 · 758 citations*](https://md.research.elamur.ai/free/en/papers/ardila-2019-common-voice-massively-multilingual-speech/)
17. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 729 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
18. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges arXiv:1907.05019**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 564 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
19. [**Deep Learning Scaling is Predictable, Empirically arXiv:1712.00409**Joel Hestness, Sharan Narang, Newsha Ardalani, et al.*2017 · 518 citations*](https://md.research.elamur.ai/free/en/papers/hestness-2017-deep-learning-scaling-predictable-empirically/)
20. [**GLaM: Efficient Scaling of Language Models with Mixture-of-Experts arXiv:2112.06905**Nan Du, Yanping Huang, Andrew M. Dai, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/)
21. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
22. **[Are Emergent Abilities of Large Language Models a Mirage?](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 342 citations*
23. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
24. **[SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 290 citations*
25. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
26. [**Scaling Laws for Autoregressive Generative Modeling arXiv:2010.14701**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 277 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)
27. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
28. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
29. **[Predictability and Surprise in Large Generative Models](https://md.research.elamur.ai/free/en/papers/ganguli-2022-predictability-surprise-large-generative-models/) [ACM Conference on Fairness, Accountability, and Transparency (FAccT)](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/)**Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.*2022 · 268 citations*
30. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
31. [**Concrete Problems in AI Safety arXiv:1606.06565**Dario Amodei, Chris Olah, Jacob Steinhardt, et al.*2016 · 232 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2016-concrete-problems-ai-safety/)
32. **[Beyond neural scaling laws: beating power law scaling via data pruning](https://md.research.elamur.ai/free/en/papers/sorscher-2022-neural-scaling-laws-beating-power/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.*2022 · 231 citations*
33. **[A Dataset for Multi-Target Stance Detection](https://md.research.elamur.ai/free/en/papers/sobhani-2017-dataset-multi-target-stance-detection/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Parinaz Sobhani, Diana Inkpen, Xiaodan Zhu*2017 · 190 citations*
34. [**Neural Language Correction with Character-Based Attention arXiv:1603.09727**Ziang Xie, Anand Avati, Naveen Arivazhagan, et al.*2016 · 164 citations*](https://md.research.elamur.ai/free/en/papers/xie-2016-neural-language-correction-character-based/)
35. [**Unsolved Problems in ML Safety arXiv:2109.13916**Dan Hendrycks, Nicholas Carlini, John Schulman, et al.*2021 · 151 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-unsolved-problems-ml-safety/)
36. [**Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads arXiv:2008.09213**Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, et al.*2020 · 141 citations*](https://md.research.elamur.ai/free/en/papers/narayanan-2020-heterogeneity-aware-cluster-scheduling-policies/)
37. **[Grounded Adaptation for Zero-shot Executable Semantic Parsing](https://md.research.elamur.ai/free/en/papers/zhong-2020-grounded-adaptation-zero-shot-executable/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Victor Zhong, Mike Lewis, Sida I. Wang, et al.*2020 · 136 citations*
38. [**The case for 4-bit precision: k-bit Inference Scaling Laws arXiv:2212.09720**Tim Dettmers, Luke Zettlemoyer*2022 · 123 citations*](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/)
39. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models arXiv:2408.00724**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/)
40. **[Direct Acoustics-to-Word Models for English Conversational Speech Recognition](https://md.research.elamur.ai/free/en/papers/audhkhasi-2017-direct-acoustics-word-models-english/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Kartik Audhkhasi, Bhuvana Ramabhadran, George Saon, et al.*2017 · 122 citations*
41. [**A Constructive Prediction of the Generalization Error Across Scales arXiv:1909.12673**Jonathan S. Rosenfeld, Amir Rosenfeld, Yonatan Belinkov, et al.*2019 · 120 citations*](https://md.research.elamur.ai/free/en/papers/rosenfeld-2019-constructive-prediction-generalization-error-across/)
42. [**Scaling Laws for Transfer arXiv:2102.01293**Danny Hernandez, Jared Kaplan, Tom Henighan, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2021-scaling-laws-transfer/)
43. [**ImageNet Training in Minutes arXiv:1709.05011**Yang You, Zhao Zhang, Cho-Jui Hsieh, et al.*2017 · 112 citations*](https://md.research.elamur.ai/free/en/papers/you-2017-imagenet-training-minutes/)
44. **[Building competitive direct acoustics-to-word models for English conversational speech recognition](https://md.research.elamur.ai/free/en/papers/audhkhasi-2017-building-competitive-direct-acoustics-word/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Kartik Audhkhasi, Brian Kingsbury, Bhuvana Ramabhadran, et al.*2017 · 111 citations*
45. [**SemDeDup: Data-efficient learning at web-scale through semantic deduplication arXiv:2303.09540**Amro Abbas, Kushal Tirumala, Dániel Simig, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/)
46. [**The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models arXiv:2505.22617**Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-entropy-mechanism-reinforcement-learning-reasoning/)
47. [**Accelerating Sparse Deep Neural Networks arXiv 2021 (NVIDIA)**Asit Mishra, Jorge Albericio Latorre, Jeff Pool, et al.*2021 · 97 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2021-accelerating-sparse-deep-neural-networks/)
48. **[The IBM 2015 English Conversational Telephone Speech Recognition System](https://md.research.elamur.ai/free/en/papers/saon-2015-ibm-2015-english-conversational-telephone/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**George Saon, Hong-Kwang J. Kuo, Steven Rennie, et al.*2015 · 97 citations*
49. [**The Platonic Representation Hypothesis arXiv:2405.07987**Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.*2024 · 96 citations*](https://md.research.elamur.ai/free/en/papers/huh-2024-platonic-representation-hypothesis/)
50. **[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*
51. [**Scaling Laws and Interpretability of Learning from Repeated Data arXiv:2205.10487**Danny Hernandez, Tom Brown, Tom Conerly, et al.*2022 · 91 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2022-scaling-laws-interpretability-learning-repeated/)
52. **[Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding](https://md.research.elamur.ai/free/en/papers/hou-2018-sequence-sequence-data-augmentation-dialogue/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yutai Hou, Yijia Liu, Wanxiang Che, et al.*2018 · 88 citations*
53. [**Themis: Fair and Efficient GPU Cluster Scheduling arXiv:1907.01484**Kshiteej Mahajan, Arjun Balasubramanian, Arjun Singhvi, et al.*2019 · 87 citations*](https://md.research.elamur.ai/free/en/papers/mahajan-2019-themis-fair-efficient-gpu-cluster/)
54. [**Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training arXiv:2208.06102**Jie You, Jae-Won Chung, Mosharaf Chowdhury*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/you-2022-zeus-understanding-optimizing-gpu-energy/)
55. **[Arabic Speech Recognition by End-to-End, Modular Systems and Human](https://md.research.elamur.ai/free/en/papers/hussein-2021-arabic-speech-recognition-end-end/) [Computer Speech & Language](https://md.research.elamur.ai/free/en/venues/computer-speech-language/)**Amir Hussein, Shinji Watanabe, Ahmed Ali*2021 · 76 citations*
56. **[Joint Modeling of Accents and Acoustics for Multi-Accent Speech Recognition](https://md.research.elamur.ai/free/en/papers/yang-2018-joint-modeling-accents-acoustics-multi/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Xuesong Yang, Kartik Audhkhasi, Andrew Rosenberg, et al.*2018 · 73 citations*
57. **[Learning to Reason under Off-Policy Guidance](https://md.research.elamur.ai/free/en/papers/yan-2025-learning-reason-under-off-policy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianhao Yan, Yafu Li, Zican Hu, et al.*2025 · 68 citations*
58. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws arXiv:2401.00448**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/)
59. **[The Art of Saying No: Contextual Noncompliance in Language Models](https://md.research.elamur.ai/free/en/papers/brahman-2024-art-saying-no-contextual-noncompliance/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Faeze Brahman, Sachin Kumar, Vidhisha Balachandran, et al.*2024 · 56 citations*
60. **[On the limit of English conversational speech recognition](https://md.research.elamur.ai/free/en/papers/tuske-2021-limit-english-conversational-speech-recognition/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Zoltan Tuske, George Saon, Brian Kingsbury*2021 · 49 citations*
61. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
62. [**Scaling Laws for Generative Mixed-Modal Language Models arXiv:2301.03728**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)
63. **[A Hierarchical Neural Model for Learning Sequences of Dialogue Acts](https://md.research.elamur.ai/free/en/papers/tran-2017-hierarchical-neural-model-learning-sequences/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Quan Hung Tran, Ingrid Zukerman, Gholamreza Haffari*2017 · 44 citations*
64. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
65. [**The Quantization Model of Neural Scaling arXiv:2303.13506**Eric J. Michaud, Ziming Liu, Uzay Girit, et al.*2023 · 30 citations*](https://md.research.elamur.ai/free/en/papers/michaud-2023-quantization-model-neural-scaling/)
66. [**Distillation Scaling Laws arXiv:2502.08606**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
67. [**Pretraining on the Test Set Is All You Need arXiv:2309.08632**Rylan Schaeffer*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-pretraining-test-set-all-need/)
68. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
69. [**Multi-Dialect Arabic Speech Recognition arXiv:2112.14678**Abbas Raza Ali*2020 · 18 citations*](https://md.research.elamur.ai/free/en/papers/ali-2021-multi-dialect-arabic-speech-recognition/)
70. **[MASRI-HEADSET: A Maltese Corpus for Speech Recognition](https://md.research.elamur.ai/free/en/papers/mena-2020-masri-headset-maltese-corpus-speech/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Carlos Daniel Hernandez Mena, Albert Gatt, Andrea DeMarco, et al.*2020 · 16 citations*
71. **[Arabic Synonym BERT-based Adversarial Examples for Text Classification](https://md.research.elamur.ai/free/en/papers/alshahrani-2024-arabic-synonym-bert-based-adversarial/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Norah Alshahrani, Saied Alshahrani, Esma Wali, et al.*2024 · 10 citations*
72. [**The Perceptimatic English Benchmark for Speech Perception Models arXiv:2005.03418**Juliette Millet, Ewan Dunbar*2020 · 10 citations*](https://md.research.elamur.ai/free/en/papers/millet-2020-perceptimatic-english-benchmark-speech-perception/)
73. [**DARTS: Dialectal Arabic Transcription System arXiv:1909.12163**Sameer Khurana, Ahmed Ali, James Glass*2019 · 7 citations*](https://md.research.elamur.ai/free/en/papers/khurana-2019-darts-dialectal-arabic-transcription-system/)
74. [**End-to-end Jordanian dialect speech-to-text self-supervised learning framework arXiv:2609.24410 · Front. Robot. AI 9:1090012 (2022)**Ali A. Safieh, Ibrahim Abu Alhaol, Rawan Ghnemat*2022 · 5 citations*](https://md.research.elamur.ai/free/en/papers/safieh-2026-end-end-jordanian-dialect-speech/)
75. **[Open Automatic Speech Recognition Models for Classical and Modern Standard Arabic](https://md.research.elamur.ai/free/en/papers/grigoryan-2025-open-automatic-speech-recognition-models/) [IEEE International Conference on Acoustics Speech and Signal Processing](https://md.research.elamur.ai/free/en/venues/ieee-international-conference-on-acoustics-speech-and-signal-processing/)**Lilit Grigoryan, Nikolay Karpov, Enas Albasiri, et al.*2025 · 4 citations*
76. **[Arabic Dysarthric Speech Recognition Using Adversarial and Signal-Based Augmentation](https://md.research.elamur.ai/free/en/papers/baali-2023-arabic-dysarthric-speech-recognition-using/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Massa Baali, Ibrahim Almakky, Shady Shehata, et al.*2023 · 4 citations*
77. [**The IBM 2016 English Conversational Telephone Speech Recognition System arXiv:1604.08242**George Saon, Tom Sercu, Steven Rennie, et al.*2016 · 3 citations*](https://md.research.elamur.ai/free/en/papers/saon-2016-ibm-2016-english-conversational-telephone/)
78. **[Scaling Laws for Code: Every Programming Language Matters](https://md.research.elamur.ai/free/en/papers/yang-2026-scaling-laws-code-every-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Yang, Shuyue Guo, Linzheng Chai, et al.*2026 · 2 citations*
79. **[UM IWSLT 2024 Low-Resource Speech Translation: Combining Maltese and North Levantine Arabic](https://md.research.elamur.ai/free/en/papers/nabhani-2024-um-iwslt-2024-low-resource/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Sara Nabhani, Aiden Williams, Miftahul Jannat, et al.*2024 · 2 citations*
80. **[UOM-Constrained IWSLT 2024 Shared Task Submission - Maltese Speech Translation](https://md.research.elamur.ai/free/en/papers/abela-2024-uom-constrained-iwslt-2024-shared/) [International Conference on Spoken Language Translation (IWSLT)](https://md.research.elamur.ai/free/en/venues/iwslt/)**Kurt Abela, Md Abdur Razzaq Riyadh, Melanie Galea, et al.*2024 · 2 citations*
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83. [**Deep segmental phonetic posterior-grams based discovery of non-categories in L2 English speech arXiv:2002.00205**Xu Li, Xixin Wu, Xunying Liu, et al.*2020 · 1 citation*](https://md.research.elamur.ai/free/en/papers/li-2020-deep-segmental-phonetic-posterior-grams/)
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