Fuentes de referencia

Referencias 385–408 de 766

385. JSON Web Token (JWT) Profile for OAuth 2.0 Access Tokens

     Vittorio Bertocci
     2021
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     • Permission Has a Time: Relationship-Based Authorization and Consistent Revocation

386. Keystone: An Open Framework for Architecting TEEs

     Dayeol Lee; David Kohlbrenner; Shweta Shinde; Dawn Song; Krste Asanovic
     2019
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     • What an Attestation Establishes: Confidential Computing and the Remaining Trust Boundary

387. Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

     Lijun Yu; José Lezama; Nitesh B. Gundavarapu; Luca Versari; Kihyuk Sohn; David Minnen; Yong Cheng; Vighnesh Birodkar; Agrim Gupta; Xiuye Gu; Alexander G. Hauptmann; Boqing Gong; Ming-Hsuan Yang; Irfan Essa; David A. Ross; Lu Jiang
     2024
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     • Before the Generator Learns: Visual Tokenization, Information Bottlenecks, and Sequence Cost

388. Language Models (Mostly) Know What They Know

     Kadavath et al.
     2022-07-11

     Ubicación en la fuente: v4 abstract

     Alcance de la consulta: Self-evaluation and calibration show encouraging task-specific findings but transfer of calibration to new tasks remains limited.

     Consulta: 2026-10-15

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     • 偏好优化的目标边界：奖励代理、参考策略与分布漂移

389. Large Language Diffusion Models

     Shen Nie; Fengqi Zhu; Zebin You; Xiaolu Zhang; Jingyang Ou; Jun Hu; Jun Zhou; Yankai Lin; Ji-Rong Wen; Chongxuan Li
     2025
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     • What a Mask Forgets: Discrete Diffusion, Joint Dependence, and Parallel Token Generation

390. Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

     Simian Luo; Yiqin Tan; Longbo Huang; Jian Li; Hang Zhao
     2023
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     • One Step Is a Budget, Not a Distribution: Consistency Models and the Evidence for Fast Generation

391. Layer Normalization

     Jimmy Lei Ba; Jamie Ryan Kiros; Geoffrey E. Hinton
     2016
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     • Normalization Changes the Geometry of Learning

392. Learned Image Compression with Discretized Gaussian Mixture Likelihoods and Attention Modules

     Zhengxue Cheng; Heming Sun; Masaru Takeuchi; Jiro Katto
     2020
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     • The Bits the Model Must Actually Send: Learned Image Compression and Entropy-Model Mismatch

393. Learning a variational network for reconstruction of accelerated MRI data

     Kerstin Hammernik; Teresa Klatzer; Erich Kobler; Michael P. Recht; Daniel K. Sodickson; Thomas Pock; Florian Knoll
     2017
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     • A Plausible Image Is Not a Measurement: Learned MRI Reconstruction and Data Consistency

394. Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

     , , ,
     2023-04-23

     Ubicación en la fuente: Abstract; 原文方法、理论和实验章节见作者原始论文链接

     Alcance de la consulta: 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。

     Consulta: 2026-10-21

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     • 扩散策略与机器人闭环：多模态动作、执行时限与安全验证

395. Learning high-accuracy error decoding for quantum processors

     Bausch et al.
     2024-11-20

     Ubicación en la fuente: Experimental distance 3/5; simulated distances through 11; Methods decoding speed distinguishes throughput and latency.

     Consulta: 2026-10-22

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     • 量子纠错的学习译码：逻辑等价类、相关噪声与实时吞吐的三重约束

396. Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics

     Albert Musaelian; Simon Batzner; Anders Johansson; Lixin Sun; Cameron J. Owen; Mordechai Kornbluth; Boris Kozinsky
     2022
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     • Handedness Is Information: Molecular Equivariance Beyond Distances

397. Learning local equivariant representations for large-scale atomistic dynamics

     Albert Musaelian; Simon Batzner; Anders Johansson; Lixin Sun; Cameron J. Owen; Mordechai Kornbluth; Boris Kozinsky
     2023
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     • The Force of a Prediction: Transferability, Stability and Uncertainty in Learned Atomic Potentials

398. Learning Transferable Visual Models From Natural Language Supervision

     Radford et al.
     2021-02-26

     Ubicación en la fuente: v1; contrastive training and zero-shot transfer

     Alcance de la consulta: CLIP contrasts image-text pairs; its reported training corpus contains 400 million pairs. Candidate text prompts define a zero-shot classification task.

     Consulta: 2026-10-15

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     • 多模态表征的可迁移性：对比目标、信息瓶颈与跨分布失效
     • 可提示分割与视频记忆：SAM 接口、掩码歧义和跨域验证

399. Learning with Noisy Labels

     Nagarajan Natarajan; Inderjit S. Dhillon; Pradeep K. Ravikumar; Ambuj Tewari
     2013
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     • Noisy Labels and the Missing Identification Assumption

400. Learning without Forgetting

     Zhizhong Li; Derek Hoiem
     2016
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     • What a Continual Learner Remembers: Replay, Constraints, and the Accounting of Forgetting

401. LegoOS: A Disseminated, Distributed OS for Hardware Resource Disaggregation

     Yizhou Shan; Yutong Huang; Yilun Chen; Yiying Zhang
     2018
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     • Memory across a Network: RDMA, Placement, and the Cost of Remote State

402. Let's Verify Step by Step

     Lightman et al.
     2023-05-31

     Ubicación en la fuente: v1 abstract; process vs outcome supervision

     Alcance de la consulta: Process supervision is compared to outcome supervision on MATH; a reported 78 percent is for a representative subset with the paper's selection procedure, not all mathematics.

     Consulta: 2026-10-15

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     • 从生成猜想到可检查证明：神经符号搜索中的验证器、规格与发现
     • 语言模型推理的验证边界：采样、搜索与正确性证据

403. Leveled Compaction

     RocksDB contributors
     2023
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     • The Price of Sorted State: Compaction, Amplification, and Value Separation

404. Lightweight Asynchronous Snapshots for Distributed Dataflows

     Paris Carbone; Gyula Fora; Stephan Ewen; Seif Haridi; Kostas Tzoumas
     2015
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     • Exactly-Once Effects Across Crashes: Where the Transaction Boundary Ends

405. Ligra: A Lightweight Graph Processing Framework for Shared Memory

     Julian Shun; Guy E. Blelloch
     2013
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     • Skew Is the Workload: Partitioning and Direction Choice in Graph Processing

406. Linear Transformers Are Secretly Fast Weight Programmers

     Imanol Schlag; Kazuki Irie; Jürgen Schmidhuber
     2021
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     • Weights as Conditional Outputs: Hypernetworks, Modulation, and the Limits of Parameter Sharing

407. LLVM: a compilation framework for lifelong program analysis & transformation

     C. Lattner; V. Adve
     2004
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     • Optimization as Refinement: Proving What a Compiler May Change

408. Local-first software: you own your data, in spite of the cloud

     Martin Kleppmann; Adam Wiggins; Peter van Hardenberg; Mark McGranaghan
     2019
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     • Convergence Is Not Intention: The Semantics of Local-First Collaboration