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* {{cite web |last=Morales |first=Jowi |title=Microsoft researchers build 1-bit AI LLM with 2B parameters |website=Tom's Hardware |date=2025-04-17 |url=https://www.tomshardware.com/tech-industry/artificial-intelligence/microsoft-researchers-build-1-bit-ai-llm-with-2b-parameters-model-small-enough-to-run-on-some-cpus |access-date=2025-04-21}}
* {{cite |last=Ouyang |first=Xu |last2=Ge |first2=Tao |last3=Hartvigsen |first3=Thomas |last4=Zhang |first4=Zhisong |last5=Mi |first5=Haitao |last6=Yu |first6=Dong |title=Low-Bit Quantization Favors Undertrained LLMs: Scaling Laws for Quantized LLMs with 100T Training Tokens |date=2024 |doi=10.48550/ARXIV.2411.17691 |doi-access=free |url=http://arxiv.org/pdf/2411.17691 |access-date=2025-04-22}}
* {{cite |last=Wang |first=Hongyu |last2=Ma |first2=Shuming |last3=Dong |first3=Li |last4=Huang |first4=Shaohan |last5=Wang |first5=Huaijie |last6=Ma |first6=Lingxiao |last7=Yang |first7=Fan |last8=Wang |first8=Ruiping |last9=Wu |first9=Yi |last10=Wei |first10=Furu |title=BitNet: Scaling 1-bit Transformers for Large Language Models |date=2023 |doi=10.48550/ARXIV.2310.11453 |doi-access=free |url=https://arxiv.org/abs/2310.11453 |access-date=2025-04-23}}
[[Category:Large language models]]
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