Reference sources
Primary references used in the research collection. Titles and bibliographic details retain their original language.
References 409–432 of 766
Longformer: The Long-Document Transformer
Beltagy et al.
2020-04-10Source location: v2 abstract and architecture description
Source scope: Local window attention combines with selected global attention; inference limits depend on architecture.
Inspected on: 2026-10-15
Open original source ↗Referenced in (2)
LoRA: Low-Rank Adaptation of Large Language Models
Edward J. Hu; Yelong Shen; Phillip Wallis; Zeyuan Allen-Zhu; Yuanzhi Li; Shean Wang; Lu Wang; Weizhu ChenOpen original source ↗
2021Referenced in (1)
LoRA: Low-Rank Adaptation of Large Language Models
Hu et al.
2021-06-17Source location: v2; low-rank update formulation
Source scope: A frozen matrix W receives a trainable low-rank BA update. The number of trainable values r(d_in+d_out) differs from the full matrix size.
Inspected on: 2026-10-15
Open original source ↗Referenced in (2)
Lost in the Middle: How Language Models Use Long Contexts
Nelson F. Liu; Kevin Lin; John Hewitt; Ashwin Paranjape; Michele Bevilacqua; Fabio Petroni; Percy LiangOpen original source ↗
2023Lost in the Middle: How Language Models Use Long Contexts
Liu et al.
2023-07-06Source location: v3 abstract; multi-document QA and key-value retrieval
Source scope: In studied models and tasks, placement of relevant information affects accuracy; this is not a universal failure rate for later models.
Inspected on: 2026-10-15
Open original source ↗Referenced in (1)
Low latency via redundancy
Ashish Vulimiri; Philip Brighten Godfrey; Radhika Mittal; Justine Sherry; Sylvia Ratnasamy; Scott ShenkerOpen original source ↗
2013Referenced in (1)
Low-Rank Bottleneck in Multi-head Attention Models
Srinadh Bhojanapalli; Chulhee Yun; Ankit Singh Rawat; Sashank J. Reddi; Sanjiv KumarOpen original source ↗
2020Lower Bounds for Oblivious Data Structures
Riko Jacob; Kasper Green Larsen; Jesper Buus NielsenOpen original source ↗
2018Machine learning-aided engineering of hydrolases for PET depolymerization
Hongyuan Lu; Daniel J. Diaz; Natalie J. Czarnecki; Congzhi Zhu; Wantae Kim; Raghav Shroff; et al.
2022-04-27Source location: Abstract; Extended Data Figs. 5–9
Source scope: 底物几何、结晶与温度影响;质量损失不等于闭环回收产率。
Open original source ↗Referenced in (1)
Machine Unlearning
Lucas Bourtoule; Varun Chandrasekaran; Christopher A. Choquette-Choo; Hengrui Jia; Adelin Travers; Baiwu Zhang; David Lie; Nicolas PapernotOpen original source ↗
2019Referenced in (1)
Magnetic control of tokamak plasmas through deep reinforcement learning
Degrave et al.
2022Source location: TCV magnetic shape-control experiments, simulator training and device-specific control scope.
Inspected on: 2026-10-22
Open original source ↗Referenced in (1)
Maintenance of datalog materialisations revisited
Boris Motik; Yavor Nenov; Robert Piro; Ian HorrocksOpen original source ↗
2019Major role of particle fragmentation in regulating biological sequestration of CO2 by the oceans
Nathan Briggs; Giorgio Dall’Olmo; Hervé Claustre
2020-02-14Source location: Abstract; particle fragmentation results
Source scope: 颗粒破碎影响输送;不把颗粒浓度当沉降通量。
Open original source ↗Referenced in (1)
Majorana quantization and half-integer thermal quantum Hall effect in a Kitaev spin liquid
Y. Kasahara; T. Ohnishi; Y. Mizukami; O. Tanaka; Sixiao Ma; K. Sugii; N. Kurita; H. Tanaka; J. Nasu; Y. Motome; T. Shibauchi; Y. MatsudaOpen original source ↗
2018Making Deep Neural Networks Robust to Label Noise: A Loss Correction Approach
Giorgio Patrini; Alessandro Rozza; Aditya Krishna Menon; Richard Nock; Lizhen QuOpen original source ↗
2017Referenced in (1)
Making snapshot isolation serializable
Alan Fekete; Dimitrios Liarokapis; Elizabeth O'Neil; Patrick O'Neil; Dennis ShashaOpen original source ↗
2005Referenced in (1)
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
,
2023-12-01Source location: Abstract; 原文方法、理论和实验章节见作者原始论文链接
Source scope: 一手论文;原文研究归属原作者。本文的推导示例与建议实验方案另行标注,不冒充原论文或本站实测。
Inspected on: 2026-10-21
Open original source ↗Referenced in (1)
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Albert Gu; Tri DaoOpen original source ↗
2023Manifold Mixup: Better Representations by Interpolating Hidden States
Vikas Verma; Alex Lamb; Christopher Beckham; Amir Najafi; Ioannis Mitliagkas; David Lopez-Paz; Yoshua BengioOpen original source ↗
2019Referenced in (1)
Marine heatwaves under global warming
Thomas L. Frölicher; Erich M. Fischer; Nicolas GruberOpen original source ↗
2018Masked Autoencoders Are Scalable Vision Learners
Kaiming He; Xinlei Chen; Saining Xie; Yanghao Li; Piotr Dollár; Ross GirshickOpen original source ↗
2022Referenced in (1)
MaskGIT: Masked Generative Image Transformer
Huiwen Chang; Han Zhang; Lu Jiang; Ce Liu; William T. FreemanOpen original source ↗
2022Massively parallel single-cell mitochondrial DNA genotyping and chromatin profiling
Caleb A. Lareau; Leif S. Ludwig; Christoph Muus; Satyen H. Gohil; Tongtong Zhao; Zachary Chiang; Karin Pelka; Jeffrey M. Verboon; Wendy Luo; Elena Christian; Daniel Rosebrock; Gad Getz; Genevieve M. Boland; Fei Chen; Jason D. Buenrostro; Nir Hacohen; Catherine J. Wu; Martin J. Aryee; Aviv Regev; Vijay G. SankaranOpen original source ↗
2020Mathematical discoveries from program search with large language models
Romera-Paredes et al.
2023Source location: Program generation, evaluation function, population database and search; evaluator validity is part of the system.
Inspected on: 2026-10-22
Open original source ↗Referenced in (1)