---
title: "Who cites Mike Chrzanowski — 440 papers of our library"
description: "440 papers of the Elamur Research library cite the works of Mike Chrzanowski, found in their bibliographies; the most cited first."
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---
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# Who cites Mike Chrzanowski

459 citations of their works from 440 papers of our library (of the 149,439 whose bibliographies we read) · 75 with a page here, the most cited first · [← Mike Chrzanowski](https://md.research.elamur.ai/free/en/authors/mike-chrzanowski/)

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. [**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/)
3. [**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/)
4. [**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/)
5. [**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/)
6. [**Unified Language Model Pre-training for Natural Language Understanding and Generation arXiv:1905.03197**Li Dong, Nan Yang, Wenhui Wang, et al.*2019 · 1,422 citations*](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/)
7. [**Calibrate Before Use: Improving Few-Shot Performance of Language Models arXiv:2102.09690**Tony Z. Zhao, Eric Wallace, Shi Feng, et al.*2021 · 825 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2021-calibrate-before-use-improving-few/)
8. [**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/)
9. **[Generating Radiology Reports via Memory-driven Transformer](https://md.research.elamur.ai/free/en/papers/chen-2020-generating-radiology-reports-memory-driven/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhihong Chen, Yan Song, Tsung-Hui Chang, et al.*2020 · 715 citations*
10. [**Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model arXiv:2201.11990**Shaden Smith, Mostofa Patwary, Brandon Norick, et al.*2022 · 615 citations*](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/)
11. [**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/)
12. **[Pretrained Transformers Improve Out-of-Distribution Robustness](https://md.research.elamur.ai/free/en/papers/hendrycks-2020-pretrained-transformers-improve-out-distribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Hendrycks, Xiaoyuan Liu, Eric Wallace, et al.*2020 · 452 citations*
13. **[oLMpics — On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 440 citations*
14. **[Information-Theoretic Probing with Minimum Description Length](https://md.research.elamur.ai/free/en/papers/voita-2020-information-theoretic-probing-minimum-description/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Elena Voita, Ivan Titov*2020 · 345 citations*
15. [**Compressive Transformers for Long-Range Sequence Modelling arXiv:1911.05507**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
16. **[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*
17. [**Analysing Mathematical Reasoning Abilities of Neural Models arXiv:1904.01557**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/)
18. [**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/)
19. [**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/)
20. [**Perceiver: General Perception with Iterative Attention arXiv:2103.03206**Andrew Jaegle, Felix Gimeno, Andrew Brock, et al.*2021 · 269 citations*](https://md.research.elamur.ai/free/en/papers/jaegle-2021-perceiver-general-perception-iterative-attention/)
21. **[Can You Unpack That? Learning to Rewrite Questions-in-Context](https://md.research.elamur.ai/free/en/papers/elgohary-2019-can-you-unpack-that-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber*2019 · 245 citations*
22. [**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/)
23. **[Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling](https://md.research.elamur.ai/free/en/papers/han-2019-unsupervised-domain-adaptation-contextualized-embeddings/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaochuang Han, Jacob Eisenstein*2019 · 241 citations*
24. **[MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension](https://md.research.elamur.ai/free/en/papers/talmor-2019-multiqa-empirical-investigation-generalization-transfer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alon Talmor, Jonathan Berant*2019 · 236 citations*
25. [**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/)
26. **[Syntactic Data Augmentation Increases Robustness to Inference Heuristics](https://md.research.elamur.ai/free/en/papers/min-2020-syntactic-data-augmentation-increases-robustness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junghyun Min, R. Thomas McCoy, Dipanjan Das, et al.*2020 · 220 citations*
27. **[What Happens To BERT Embeddings During Fine-tuning?](https://md.research.elamur.ai/free/en/papers/merchant-2020-what-happens-bert-embeddings-during/) [BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/blackboxnlp/)**Amil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.*2020 · 220 citations*
28. **[CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://md.research.elamur.ai/free/en/papers/ye-2021-crossfit-few-shot-learning-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qinyuan Ye, Bill Yuchen Lin, Xiang Ren*2021 · 210 citations*
29. [**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/)
30. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
31. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
32. [**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/)
33. **[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*
34. **[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*
35. [**Small Language Models are the Future of Agentic AI arXiv:2506.02153**Peter Belcak, Greg Heinrich, Shizhe Diao, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/belcak-2025-small-language-models-future-agentic/)
36. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 76 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
37. **[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*
38. **[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*
39. **[English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too](https://md.research.elamur.ai/free/en/papers/phang-2020-english-intermediate-task-training-improves/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Jason Phang, Iacer Calixto, Phu Mon Htut, et al.*2020 · 70 citations*
40. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/)
41. **[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*
42. **[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*
43. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
44. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
45. **[Investigating Language Relationships in Multilingual Sentence Encoders Through the Lens of Linguistic Typology](https://md.research.elamur.ai/free/en/papers/choenni-2022-investigating-language-relationships-multilingual-sentence/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Rochelle Choenni, Ekaterina Shutova*2022 · 24 citations*
46. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/)
47. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
48. [**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/)
49. [**Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation arXiv:2603.19220**Zhuolin Yang, Zihan Liu, Yang Chen, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-nemotron-cascade-2-post-training/)
50. **[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*
51. **[Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://md.research.elamur.ai/free/en/papers/akter-2026-nemotron-crossthink-scaling-self-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.*2026 · 9 citations*
52. [**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/)
53. [**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/)
54. **[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*
55. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
56. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/)
57. [**MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling arXiv:2602.11761**MiniCPM Team, Wenhao An, Yingfa Chen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2026-minicpm-sala-hybridizing-sparse/)
58. **[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*
59. **[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*
60. [**Improved Mispronunciation detection system using a hybrid CTC-ATT based approach for L2 English speakers arXiv:2201.10198**Neha Baranwal, Sharatkumar Chilaka*2022 · 2 citations*](https://md.research.elamur.ai/free/en/papers/baranwal-2022-improved-mispronunciation-detection-system-using/)
61. **[AMALIA: A Fully Open Large Language Model for European Portuguese](https://md.research.elamur.ai/free/en/papers/simplicio-2026-amalia-fully-open-large-language/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Afonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.*2026 · 1 citation*
62. **[Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers](https://md.research.elamur.ai/free/en/papers/yang-2026-mid-think-training-free-intermediate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Van Yang, Shouren Wang, Debargha Ganguly, et al.*2026 · 1 citation*
63. **[Sparse Adapter Fusion for Continual Learning in NLP](https://md.research.elamur.ai/free/en/papers/zeng-2026-sparse-adapter-fusion-continual-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Min Zeng, Xi Chen, Haiqin Yang, et al.*2026 · 1 citation*
64. [**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/)
65. [**The Marchex 2018 English Conversational Telephone Speech Recognition System arXiv:1811.02058**Seongjun Hahm, Iroro Orife, Shane Walker, et al.*2018 · 1 citation*](https://md.research.elamur.ai/free/en/papers/hahm-2018-marchex-2018-english-conversational-telephone/)
66. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
67. **[EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios](https://md.research.elamur.ai/free/en/papers/mu-2026-efficienttool-cost-effective-aligning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.*2026*
68. **[EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressions](https://md.research.elamur.ai/free/en/papers/noel-2026-eiffel-novel-benchmark-measure-bias/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.*2026*
69. **[Inverse Text Normalization for Arabic Numbers in Streaming ASR](https://md.research.elamur.ai/free/en/papers/albasiri-2026-inverse-text-normalization-arabic-numbers/) [Workshop on Computation and Written Language @ LREC](https://md.research.elamur.ai/free/en/venues/cawl/)**Enas Albasiri, Myungjong Kim, Nourchene Ferchichi, et al.*2026*
70. **[SciImpact: A Multi-Dimensional, Multi-Field Benchmark for Scientific Impact Prediction](https://md.research.elamur.ai/free/en/papers/zhu-2026-sciimpact-multi-dimensional-multi-field/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hangxiao Zhu, Yuyu Zhang, Ping Nie, et al.*2026*
71. **[SciPedia: Unlocking the Value of Scientific Data for Pre-training](https://md.research.elamur.ai/free/en/papers/qin-2026-scipedia-unlocking-value-scientific-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiwei Qin, Zhen Huang, Tiantian Mi, et al.*2026*
72. **[The Sonar Moment: An Audio Geo-Localization Benchmark for Audio-Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-sonar-moment-audio-geo-localization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruixing Zhang, Zihan Liu, Leilei Sun, et al.*2026*
73. **[Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid Architectures](https://md.research.elamur.ai/free/en/papers/wang-2026-understanding-context-learning-beyond-transformers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shenran Wang, Timothy Tin-Long Tse, Jian Zhu*2026*
74. **[XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake Detection](https://md.research.elamur.ai/free/en/papers/ng-2026-xlsr-mambo-scaling-hybrid-mamba/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kwok-Ho Ng, Tingting Song, Yongdong WU, et al.*2026*
75. [**Poem Meter Classification of Recited Arabic Poetry: Integrating High-Resource Systems for a Low-Resource Task arXiv:2504.12172**Maged S. Al-Shaibani, Zaid Alyafeai, Irfan Ahmad*2025*](https://md.research.elamur.ai/free/en/papers/al-shaibani-2025-poem-meter-classification-recited-arabic/)

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