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1. MAGMAX: Leveraging Model Merging for Seamless Continual Learning NSTL国家科技图书文献中心

Daniel Marczak |  Bartlomiej Twardowsk...... -  《Computer Vision - ECCV 2024,Part LXXXV》 -  European Conference on Computer Vision - 2025, - 379~395 - 共17页

摘要: approach named MagMax, which utilizes model merging to |  contribution is an extensive examination of model merging |  importantly, we present MagMax, a novel model-merging | This paper introduces a continual learning |  enable large pre-trained models to continuously learn
关键词: Continual learning |  Model merging

2. Uncertainty merging with basic uncertain information in probability environment NSTL国家科技图书文献中心

Jin L. |  Yang Y.... -  《Fuzzy sets and systems》 - 2025,498(Jan.1) - 1.1~1.16 - 共16页

摘要: cognition merging, which effectively combines basic |  merging methods and thoroughly compare and analyze their | © 2024 Elsevier B.V.Basic uncertain |  information is a recently introduced and significant type of |  uncertainty that proves particularly valuable in decision
关键词: Aggregation |  Basic uncertain information |  Information fusion |  Probabilistic uncertainty |  Probability merging |  Uncertainty merging

3. Sequential merging and construction of rankings as cognitive logic NSTL国家科技图书文献中心

Sauerwald K. |  Ismail-Tsaous E.... -  《International journal of approximate reasoning》 - 2025,176(Jan.) - 1.1~1.27 - 共27页

摘要: merging operator and a ranking construction operator |  epistemic state is obtained by merging the prior ranking |  sequential merging approach. The approach abstracts from |  the concrete merging operation and abstracts from |  sequential merging is capable of predicting with
关键词: Cognitive logic |  Epistemic state |  Human reasoning |  Merging |  Prediction |  Ranking construction function |  Ranking function |  Sequential merging |  Theoretical maximum accuracy

4. A Novel Merging Framework for Homogeneous and Heterogeneous Blockchain Systems NSTL国家科技图书文献中心

Liehuang Zhu |  Sadaf Bukhari... -  《Wireless Artificial Intelligent Computing Systems and Applications,Part II》 -  International Conference on Wireless Artificial Intelligent Computing Systems and Applications - 2025, - 304~315 - 共12页

摘要:This paper presents two solutions for merging |  into merging blockchains, addressing critical |  diverse blockchain systems: Homogeneous Chain |  Consolidation (HCC) and Heterogeneous Multi-chain Integration |  Architecture (HMIA). As blockchain networks expand
关键词: Blockchain networks |  BC merging |  Distributed ledger

5. Model Breadcrumbs: Scaling Multi-task Model Merging with Sparse Masks NSTL国家科技图书文献中心

MohammadReza Davari |  Eugene Belilovsky -  《Computer Vision - ECCV 2024,Part LXXV》 -  European Conference on Computer Vision - 2025, - 270~287 - 共18页

摘要: work focuses on the problem of merging multiple fine | The rapid development of AI systems has been |  greatly influenced by the emergence of foundation models | . A common approach for targeted problems involves |  fine-tuning these pre-trained foundation models for
关键词: Model merging |  Transfer learning |  Foundation models

6. Improving daily precipitation estimation using a double triple collocation-based (DTC) merging framework NSTL国家科技图书文献中心

Gu, Jingjing |  Ye, Yuntao... -  《Journal of Hydrology》 - 2025,648 - 共19页

摘要: precipitation estimation. The merging of multi-source gridded |  rely on gauge observations to estimate the merging |  novel Double Triple Collocation-based (DTC) merging |  precipitation rate merging with categorical triple collocation |  (CTC)-based rain/norain merging. The objective is to
关键词: Precipitation merging |  Rain/no-rain merging |  Triple collocation analysis |  2D error estimation

7. Depression Classification Using Token Merging-Based Speech Spectrotemporal Transformer NSTL国家科技图书文献中心

Lokesh Kumar |  Kumar Kaustubh... -  《Speech and Computer,Part I》 -  International Conference on Speech and Computer - 2025, - 324~335 - 共12页

摘要: merging (ToMe) within a speech spectrotemporal | This paper introduces a novel approach for |  depression classification, utilizing multimodal token |  transformer framework. The model's efficacy is evaluated |  with log-mel spectrograms and autocorrelation
关键词: Log-mel spectrogram |  Autocorrelation tempogram |  Vision transformer |  Token merging (ToMe)

8. Deep reinforcement learning algorithm based ramp merging decision model NSTL国家科技图书文献中心

Chen, Zeyu |  Du, Yu... -  《Proceedings of the Institution of Mechanical Engineers,Part D.Journal of Automobile Engineering》 - 2025,239(1) - 70~84 - 共15页

摘要: such a problem. This paper designs a ramp merging |  gradient algorithm (DDPG) to solve the vehicle merging |  merging and poor robustness of previous deep |  vehicle ramp merging leading to the low success rate of |  intelligent vehicle merging, first, we introduce a simple
关键词: Intelligent vehicles |  ramp merging |  simple recurrent unit |  prioritized experience replay |  deep reinforcement learning |  multi-objective reward functions

9. Neighbor patches merging reduces spatial redundancy to accelerate vision transformer NSTL国家科技图书文献中心

Jiang K. |  Peng P.... -  《Neurocomputing》 - 2025,613(Jan.14) - 1.1~1.13 - 共13页

摘要:, we introduce Neighbor Patches Merging (NEPAM), a | © 2024Vision Transformers (ViTs) deliver |  outstanding performance but often require substantial |  computational resources. Various token pruning methods have |  been developed to enhance throughput by removing
关键词: Position embeddings |  Spatial redundancy |  Token merging |  Vision transformer

10. Large-Scale Multi-Session Point-Cloud Map Merging NSTL国家科技图书文献中心

Hairuo Wei |  Rundong Li... -  《IEEE robotics and automation letters》 - 2025,10(1) - 88~95 - 共8页

摘要: cloud map merging. LAMM can automatically integrate |  merging. The first novelty is a temporal bidirectional | -quality map merging results. The second novelty is a |  environments during large-scale merging. We evaluate our | This paper introduces LAMM, an open-source
关键词: Merging |  Laser radar |  Point cloud compression |  Three-dimensional displays |  Feature extraction |  Heuristic algorithms |  Simultaneous localization and mapping |  Sensors |  Accuracy |  Semantics
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