---
title: "Who cites Barak Lenz — 229 papers of our library"
description: "229 papers of the Elamur Research library cite the works of Barak Lenz, found in their bibliographies; the most cited first."
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---
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# Who cites Barak Lenz

242 citations of their works from 229 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Barak Lenz](https://md.research.elamur.ai/free/en/authors/barak-lenz/)

1. [**Pre-trained Models for Natural Language Processing: A Survey arXiv:2003.08271 · SCIENCE CHINA Technological Sciences,2020, 63, 1872-1897**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
2. [**K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters arXiv:2002.01808**Ruize Wang, Duyu Tang, Nan Duan, et al.*2020 · 666 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/)
3. **[Entities as Experts: Sparse Memory Access with Entity Supervision](https://md.research.elamur.ai/free/en/papers/fevry-2020-entities-as-experts-sparse-memory/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, et al.*2020 · 208 citations*
4. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 202 citations*
5. **[Knowledge Enhanced Masked Language Model for Stance Detection](https://md.research.elamur.ai/free/en/papers/kawintiranon-2021-knowledge-enhanced-masked-language-model/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kornraphop Kawintiranon, Lisa Singh*2021 · 119 citations*
6. [**Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing**Kaixin Ma, Jonathan Francis, Quanyang Lu, et al.*2019 · 105 citations*](https://md.research.elamur.ai/free/en/papers/ma-2019-generalizable-neuro-symbolic-systems-commonsense/)
7. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
8. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 66 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
9. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
10. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
11. [**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/)
12. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
13. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
14. [**Hymba: A Hybrid-head Architecture for Small Language Models arXiv:2411.13676**Xin Dong, Yonggan Fu, Shizhe Diao, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-hymba-hybrid-head-architecture-small/)
15. **[Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models](https://md.research.elamur.ai/free/en/papers/haber-2024-polysemy-evidence-linguistics-behavioral-science/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Janosch Haber, Massimo Poesio*2024 · 44 citations*
16. **[Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models](https://md.research.elamur.ai/free/en/papers/land-2024-fishing-magikarp-automatically-detecting-under/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sander Land, Max Bartolo*2024 · 42 citations*
17. [**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/)
18. [**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/)
19. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
20. **[The Hidden Attention of Mamba Models](https://md.research.elamur.ai/free/en/papers/ali-2025-hidden-attention-mamba-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ameen Ali Ali, Itamar Zimerman, Lior Wolf*2025 · 32 citations*
21. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
22. [**Jamba-1.5: Hybrid Transformer-Mamba Models at Scale arXiv:2408.12570**Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lenz-2024-jamba-1-5-hybrid-transformer/)
23. **[RAW-C: Relatedness of Ambiguous Words in Context (A New Lexical Resource for English)](https://md.research.elamur.ai/free/en/papers/trott-2021-raw-c-relatedness-ambiguous-words/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sean Trott, Benjamin Bergen*2021 · 29 citations*
24. [**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/)
25. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
26. [**GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity? arXiv:2502.05252**Yang Zhou, Hongyi Liu, Zhuoming Chen, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-gsm-infinite-llms-behave-over/)
27. [**Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance arXiv:2507.22448**Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-falcon-h1-family-hybrid-head/)
28. [**Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase Pretraining arXiv:2412.15285**Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-maximize-data-s-potential-enhancing/)
29. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
30. **[On Many-Shot In-Context Learning for Long-Context Evaluation](https://md.research.elamur.ai/free/en/papers/zou-2025-many-shot-context-learning-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaijian Zou, Muhammad Khalifa, Lu Wang*2025 · 8 citations*
31. **[Lotus at SemEval-2021 Task 2: Combination of BERT and Paraphrasing for English Word Sense Disambiguation](https://md.research.elamur.ai/free/en/papers/ranjbar-2021-lotus-semeval-2021-task-2/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Niloofar Ranjbar, Hossein Zeinali*2021 · 4 citations*
32. **[GitChameleon 2.0: Evaluating AI Code Generation Against Python Library Version Incompatibilities](https://md.research.elamur.ai/free/en/papers/misra-2026-gitchameleon-2-0-evaluating-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Diganta Misra, Nizar Islah, Victor May, et al.*2026 · 2 citations*
33. **[Preference Learning Unlocks LLMs' Psycho-Counseling Skills](https://md.research.elamur.ai/free/en/papers/zhang-2026-preference-learning-unlocks-llms-psycho/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mian Zhang, Shaun M. Eack, Zhiyu Chen*2026 · 2 citations*
34. **[Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists](https://md.research.elamur.ai/free/en/papers/pietruszka-2026-can-models-help-us-create/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz, et al.*2026 · 1 citation*
35. **[Diversity and Homogenisation in Generative AI Translation: A Comparative Study of English-Dutch Translation Across Domains](https://md.research.elamur.ai/free/en/papers/shterionov-2026-diversity-homogenisation-generative-ai-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Dimitar Shterionov, Noa van Helleman, Eva Vanmassenhove*2026*
36. **[FlowHN: Adaptive Token Routing for Efficient Parallel Hybrid Networks](https://md.research.elamur.ai/free/en/papers/moradi-2026-flowhn-adaptive-token-routing-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammad Mahdi Moradi, Walid Ahmed, Shuangyue Wen, et al.*2026*
37. **[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*
38. [**Annotating the French Wiktionary with supersenses for large scale lexical analysis: a use case to assess form-meaning relationships within the nominal lexicon COLING 2025 (Abu Dhabi)**Nicolas Angleraud, Lucie Barque, Marie Candito*2025*](https://md.research.elamur.ai/free/en/papers/angleraud-2025-french-wiktionary-supersenses/)

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

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