🧑‍🔬 Who cites Paolo Glorioso

113 citations of their works from 112 papers of our library (of the 149,439 whose bibliographies we read) · 20 with a page here, the most cited first · ← Paolo Glorioso

1. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
2. An Empirical Study of Mamba-based Language ModelsarXiv:2406.07887Roger Waleffe, Wonmin Byeon, Duncan Riach, et al.2024 · 67 citations
3. MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning AttentionarXiv:2506.13585MiniMax, Aili Chen, Aonian Li, et al.2025 · 66 citations
4. A Comprehensive Survey on Long Context Language ModelingarXiv:2503.17407Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.2025 · 64 citations
5. MiniMax-01: Scaling Foundation Models with Lightning AttentionarXiv:2501.08313MiniMax, Aonian Li, Bangwei Gong, et al.2025 · 50 citations
6. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
7. LLM Pruning and Distillation in Practice: The Minitron ApproacharXiv:2408.11796Sharath Turuvekere Sreenivas, Saurav Muralidharan, Raviraj Joshi, et al.2024 · 44 citations
8. Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?International Conference on Computational Linguistics (COLING)Mingyu Jin, Qinkai Yu, Jingyuan Huang, et al.2025 · 36 citations
9. A Survey on Latent ReasoningarXiv:2507.06203Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.2025 · 15 citations
10. Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and PerformancearXiv:2507.22448Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.2025 · 15 citations
11. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
12. Puzzle: Distillation-Based NAS for Inference-Optimized LLMsarXiv:2411.19146Akhiad Bercovich, Tomer Ronen, Talor Abramovich, et al.2024 · 10 citations
13. Faster MoE LLM Inference for Extremely Large ModelsFindings of the Association for Computational LinguisticsHaoqi Yang, Luohe Shi, Qiwei Li, et al.2026 · 8 citations
14. Kuwain 1.5B: An Arabic SLM via Language InjectionarXiv:2504.15120Khalil Hennara, Sara Chrouf, Mohamed Motaism Hamed, et al.2025 · 4 citations
15. Cross-layer Attention Sharing for Pre-trained Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Yongyu Mu, Yuzhang Wu, Yuchun Fan, et al.2026 · 2 citations
16. Lizard: An Efficient Linearization Framework for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Chien Van Nguyen, Huy Huu Nguyen, Ruiyi Zhang, et al.2026 · 2 citations
17. FlowHN: Adaptive Token Routing for Efficient Parallel Hybrid NetworksAnnual Meeting of the Association for Computational Linguistics (ACL)Mohammad Mahdi Moradi, Walid Ahmed, Shuangyue Wen, et al.2026
18. Understanding In-Context Learning Beyond Transformers: An Investigation of State Space and Hybrid ArchitecturesFindings of the Association for Computational LinguisticsShenran Wang, Timothy Tin-Long Tse, Jian Zhu2026
19. When depth is redundant: Efficient transformer-based speech anti-spoofingFindings of the Association for Computational LinguisticsHoan My Tran, Damien Lolive, Aghilas Sini, et al.2026
20. XLSR-MamBo: Scaling the Hybrid Mamba-Attention Backbone for Audio Deepfake DetectionFindings of the Association for Computational LinguisticsKwok-Ho Ng, Tingting Song, Yongdong WU, et al.2026

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